NAVAL POSTGRADUATE

SCHOOL

MONTEREY, CALIFORNIA

JOINT APPLIED PROJECT

Standardization in Performance Assessment of

Telemetry Tracking Systems

By: Florencio Marquez

September 2013

Advisors: Michael Boudreau

Antonio Cardoso

Approved for public release; distribution is unlimited

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REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704–0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202–4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704–0188) Washington DC 20503. 1. AGENCY USE ONLY (Leave blank)

2. REPORT DATE September 2013

3. REPORT TYPE AND DATES COVERED Joint Applied Project

4. TITLE AND SUBTITLE STANDARDIZATION IN PERFORMANCE ASSESSMENT OF TELEMETRY TRACKING SYSTEMS

5. FUNDING NUMBERS

6. AUTHOR(S) Florencio Marquez

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School Monterey, CA 93943–5000

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11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government. IRB Protocol number _______N/A________.

12a. DISTRIBUTION / AVAILABILITY STATEMENT Approved for public release; distribution is unlimited

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13. ABSTRACT (maximum 200 words) In the world of missile testing, telemetry plays a vital role in the evaluation of these weapon systems. Telemetry is

defined as the process of taking measurements from a distance, or remote location. As measurements are made within the missile, the data is packetized and transmitted down to ground stations in real time. Once the data is accumulated, analysts review the data and evaluate the results of the missile test.

Launching a missile is a major test event that requires significant coordination and a considerable amount of funding. Collecting as much data as possible is crucial and always a fundamental requirement. Therefore, the telemetry tracking ground stations receiving the data play just as an important role as the missile itself. The ground stations must be reliable systems, where periodic maintenance and technical refreshing are key elements in the risk management of the receiving system.

This paper explores the effectiveness of predicting system failures by carefully analyzing antenna data metrics already made available to system users. By establishing a standard for evaluating these tracking systems, variances in the performance metrics over time may predict future system failures. By addressing potential issues preemptively, last-minute critical failures can be significantly reduced while making the system’s availability and reliability much higher.

14. SUBJECT TERMS Telemetry, tracking systems, performance assessment, system risk management 15. NUMBER OF

PAGES 69

16. PRICE CODE

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Unclassified

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Approved for public release; distribution is unlimited

STANDARDIZATION IN PERFORMANCE ASSESSMENT OF TELEMETRY TRACKING SYSTEMS

Florencio Marquez, Systems Engineer, WSMR Range Operations Directorate

Submitted in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE IN PROGRAM MANAGEMENT

from the

NAVAL POSTGRADUATE SCHOOL September 2013

Author: Florencio Marquez Approved by: Michael Boudreau Lead Advisor

Antonio Cardoso Technical Advisor

William R. Gates, Dean

Graduate School of Business and Public Policy

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STANDARDIZATION IN PERFORMANCE ASSESSMENT OF TELEMETRY TRACKING SYSTEMS

ABSTRACT

In the world of missile testing, telemetry plays a vital role in the evaluation of these

weapon systems. Telemetry is defined as the process of taking measurements from a

distance, or remote location. As measurements are made within the missile, the data is

packetized and transmitted down to ground stations in real time. Once the data is

accumulated, analysts review the data and evaluate the results of the missile test.

Launching a missile is a major test event that requires significant coordination and

a considerable amount of funding. Collecting as much data as possible is crucial and

always a fundamental requirement. Therefore, the telemetry tracking ground stations

receiving the data play just as an important role as the missile itself. The ground stations

must be reliable systems, where periodic maintenance and technical refreshing are key

elements in the risk management of the receiving systems.

This paper explores the effectiveness of predicting system failures by carefully

analyzing antenna data metrics already made available to system users. By establishing a

standard for evaluating these tracking systems, variances in the performance metrics over

time may predict future system failures. By addressing potential issues preemptively,

last-minute critical failures can be significantly reduced while making the system’s

availability and reliability much higher.

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TABLE OF CONTENTS

I.  INTRODUCTION........................................................................................................1 A.  PURPOSE .........................................................................................................1 B.  BENEFITS ........................................................................................................1 C.  SCOPE AND LIMITATIONS ........................................................................2 D.  SIGNIFICANCE ..............................................................................................2 

II.  BACKGROUND ..........................................................................................................3 A.  EVOLUTION OF MISSILE DEFENSE .......................................................3 B.  THE MISSILE DEFENSE AGENCY ............................................................4 C.  TRANSPORTABLE TELEMETRY SYSTEMS ..........................................5 D.  COLLECTING MISSILE TELEMETRY DATA ........................................8 

III.  ANTENNA TRACKING SYSTEMS .........................................................................9 A.  PARABOLIC ANTENNA BASICS ...............................................................9 B.  AUTO-TRACKING SYSTEMS ...................................................................10 C.  ANTENNA SYSTEM EVALUATION PARAMETERS ...........................14 D.  ANTENNA CONTROL UNIT (ACU) .........................................................14 

IV.  ANALYSIS .................................................................................................................19 A.  DIAGNOSIS AND PROGNOSIS .................................................................19 B.  OIL ANALYSIS–THE IMPORTANCE OF DATA ANALYSIS ..............19 C.  DATA ANALYSIS FOR FAILURE #1 .......................................................21 D.  TIMELINE AND DATA ANALYSIS FOR FAILURE #2 ........................35 E.  MISSION PERFORMANCE STANDARDIZATION ...............................42 

V.  CONCLUSION ..........................................................................................................47 A.  HYPOTHESIS................................................................................................47 B.  RECOMMENDATIONS ...............................................................................47 C.  FINAL THOUGHTS .....................................................................................48 

LIST OF REFERENCES ......................................................................................................49 

INITIAL DISTRIBUTION LIST .........................................................................................51 

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LIST OF FIGURES

Figure 1.  The Ballistic Missile Defense System ...............................................................5 Figure 2.  TTS-1 aboard the M.V. Pacific Collector ..........................................................6 Figure 3.  TTS-2 aboard the S.S. Pacific Tracker ..............................................................6 Figure 4.  Azimuth, Elevation, and Roll axis of TTS antenna ...........................................7 Figure 5.  The two 7.3m tracking antennas (with radomes removed) utilized by TTS-

1..........................................................................................................................9 Figure 6.  Reflective properties of a parabolic dish antenna ............................................10 Figure 7.  Front panel (faces antenna dish) of an electronically scanned feed

subsystem .........................................................................................................12 Figure 8.  Example of tracking beams, elevation only .....................................................13 Figure 9.  ACU graphical user interface ...........................................................................15 Figure 10.  Antenna A and B tracking status during FTG-06A support (From TTS-1,

Dec 2010) .........................................................................................................23 Figure 11.  Antenna A and B azimuth and elevation accelerations (From TTS-1, Dec

2010) ................................................................................................................24 Figure 12.  Antenna A and B roll axis acceleration during the track (From TTS-1,

Dec 2010) .........................................................................................................25 Figure 13.  Antenna A showing less signal than Antenna B (From TTS-1, Dec 2010) ....26 Figure 14.  Antenna A having trouble maintaining track prior to the FTG-06A event

(From TTS-1, Jun 2010) ..................................................................................27 Figure 15.  Comparison plots of axis acceleration during the BVT-01 event (From

TTS-1, Jun 2010) .............................................................................................28 Figure 16.  Comparison plots of roll axis acceleration during the BVT-01 event

(From TTS-1, Jun 2010) ..................................................................................29 Figure 17.  Tracking signal strength of both antennas during the BVT-01 event (From

TTS-1, Jun 2010) .............................................................................................30 Figure 18.  Tracking status plots for the SBSS mission event (From TTS-1, Oct 2010) ..31 Figure 19.  Axis acceleration plots for the SBSS mission event (From TTS-1, Oct

2010) ................................................................................................................32 Figure 20.  Roll axis acceleration plots for the SBSS mission event (From TTS-1, Oct

2010) ................................................................................................................33 Figure 21.  Tracking signal strength comparisons for the SBSS mission event (From

TTS-1, Oct 2010) .............................................................................................34 Figure 22.  Tracking status comparisons for the AHW mission event (From TTS-2,

2011) ................................................................................................................36 Figure 23.  Azimuth and Elevation axis acceleration comparisons for the AHW

mission event (From TTS-2, 2011) ..................................................................37 Figure 24.  Roll axis acceleration comparisons for the AHW mission event (From

TTS-2, 2011) ....................................................................................................38 Figure 25.  Side by side comparison of tracking status and RF signal strength for the

FTI-01 mission event (From TTS-2, 2012) .....................................................39 

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Figure 26.  Axis acceleration comparisons for the FTI-01 mission event (From TTS-2, 2012) ............................................................................................................40 

Figure 27.  Roll axis acceleration comparisons for the FTI-01 mission (From TTS-2, 2012) ................................................................................................................41 

Figure 28.  Tracking signal strength comparisons will provide a side-by-side look at how much RF energy the antenna was able to capture during the track of the target...........................................................................................................43 

Figure 29.  Pointing angles for both antennas verifies that both antennas tracked in an identical pattern. ...............................................................................................43 

Figure 30.  Tracking status will provide data on how accurately the antenna pointed to the target. This plot will also show whether or not the antenna was able to maintain auto-track. .....................................................................................44 

Figure 31.  This plot will provide azimuth and elevation axis accelerations for antenna A .........................................................................................................44 

Figure 32.  TTS Antenna Roll Axis Accelerations will provide roll axis accelerations for antenna A ....................................................................................................45 

Figure 33.  TTS roll angles will provide insight as to the ocean’s conditions endured during the mission track by the antennas and support personnel. ...................45 

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LIST OF TABLES

Table 1.  Auto-track status values ...................................................................................17 Table 2.  Timeline of mission events in 2010 .................................................................21 Table 3.  Timeline of mission events in 2011–2012 .......................................................35 

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LIST OF ACRONYMS AND ABBREVIATIONS

ACU Antenna Control Unit

AGC Automatic Gain Control

AHW-01 Advanced Hypersonic Weapon mission event #1

AOS Acquisition of Signal

BMDS Ballistic Missile Defense System

BVT-01 Booster Vehicle Test mission event #1

CSF Conical Scan Feed

CSV Comma Separated Variable

DSL Data Support Limitation

DTR Directorate of Test Resources

EKV Exo-Atmospheric Kill Vehicle

G/T Ratio of Gain over Temperature, a system sensitivity metric

GUI Graphical User Interface

Hz Hertz

ICBM Inter-Continental Ballistic Missile

ITC International Telemetry Conference

LNA Low Noise Amplifier

LOS Loss of Signal

FTG-06A Flight Test Ground-Based Interceptor mission event #6, 2nd test

FTI-01 Flight Test Integrated mission event #1

Mbps Mega bits per second – one million bits per second

MDA Missile Defense Agency

MFPG Machinery Failure Prevention Technology society

M.V. Motor Vessel

RCC Range Commander’s Council

RF Radio Frequency

RTS Ronald Reagan Test Site

SBSS Space-Based Space Surveillance satellite rocket launch

SCM Single Channel Monopulse

SDI Strategic Defense Initiative

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S.S. Steam Ship

TM Telemetry

TSZ Test Support Zone

TTS Transportable Telemetry System

VAFB Vandenberg Air Force Base

WSMR White Sands Missile Range

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ACKNOWLEDGMENTS

I would like to thank Mr. Mike Winstead for always finding the time to explain things,

and endorsing my decision to embark on earning a post-graduate degree. Working side by

side with Mike has always been an adventure.

I am also thankful to have been witness to the birth of the Transportable

Telemetry Systems at White Sands Missile Range. Working with Mr. Moises Pedroza as

an intern, as he designed these systems on paper, proved to be of invaluable experience.

I want to thank the faculty and staff of the Naval Postgraduate School’s

Department of Business and Public Policy, especially my JAP advisor Professor Mike

Boudreau. His commitment to supporting me even after having to go back to the drawing

board is priceless.

To Mr. Antonio Cardoso from the Naval Surface Warfare Center, Corona

Division, and my JAP technical advisor, thanks for all the support even in the face of all

the inundating workload you always seem to carry.

Many thanks to all my TTS shipmates and team members for continuously

inspiring me to achieve greater things. Thanks for the support.

Lastly, and most importantly, to my ever-understanding and supportive wife,

Azalia, who has been by my side through the rough ride of being a full-time student and a

full-time employee on the road. Thank you for all the love, support, and encouragement,

even when our beautiful newborn baby, Mia Victoria, did not feel like cooperating.

Thank you all.

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I. INTRODUCTION

“The goal is to turn data into information, and information into insight.”

— Carly Fiorina, former executive, president, and chair of Hewlett-Packard Co

Like the quote implies, successful management and interpretation of data can

become an accurate means for truly understanding what is going on, under any

circumstance. In this case, the focus is on data relating to the performance and health of

telemetry tracking antennas used for missile defense testing. It is the author’s hypothesis

that by collecting and analyzing relevant data made available by these telemetry systems

in the form of log files, operators will be able to establish performance trends over time

and identify symptoms that may point to potential failures. Furthermore, by standardizing

the way these metrics are organized and reported, it will be much easier to gauge and

compare performance of telemetry receiving tracking systems across the world.

A. PURPOSE

The purpose of this paper is to identify pertinent parameters for evaluating the

performance and health status of telemetry tracking systems. By studying the data

produced by two specific ship-based telemetry tracking systems, data metrics and known

past failures will be time aligned so that trends and/or symptoms pronounced in the data

can be identified. Once these trends, or symptoms, are characterized, they can be better

detected in the future and allow operators to resolve the source of the problem

preemptively, before a critical failure occurs.

B. BENEFITS

The benefits of this study extend to all users of telemetry tracking systems, and

some relevance may exist for radar as well as optics tracking systems. Operators and test

range engineers will have better insight as to the health and status of their tracking

systems. Additionally, by identifying concerning data trends and/or symptoms,

catastrophic failures can be avoided. This will, in turn, reduce system down-time and the

2

number of data support limitations, also known as DSL’s, a test range has to issue to its

customers.

For the missile programs utilizing the range for testing purposes, they can count

on data collection systems with better reliability and availability figures. Again, this

translates to less last-minute critical failures and thus a more manageable mission

schedule.

C. SCOPE AND LIMITATIONS

The scope of this project focuses on two sea-based telemetry tracking systems

employed by the Missile Defense Agency (MDA). Each system consists of two 24 ft.

dish tracking antennas and corresponding telemetry instrumentation, such as receivers,

recorders, and communications infrastructure. Of more importance are the Antenna

Control Units (ACUs) that are linked to each antenna. These units provide the graphical

user interface (GUI) necessary for controlling the antenna and its configuration. These

entire systems are deployed to various locations in the Pacific Ocean to collect missile

data for tests relating to the Ballistic Missile Defense System (BMDS).

This research paper dissects the post-mission data logs produced by the ACUs for

the two aforementioned systems. Additionally, only data from 6 missions will be

analyzed, spanning the period from January 2010 through June 2011. Known failures that

occurred during this timeframe were identified and documented. The mission data

leading up to these failures, and post repairs, will be analyzed for trends and/or symptoms

in the data that went unnoticed before. The goal is to identify specific trends or symptoms

in the data that will point to specific problems beginning to show within the system.

D. SIGNIFICANCE

The implication of this study is important because by linking certain emerging

patterns in the data to specific failures, there is a significant chance that similar systems

may show similar symptoms prior to failure. By collecting and sharing this information,

ranges across the country can, in essence, create a database of different data patterns and

corresponding failures that everyone can share and have access to.

3

II. BACKGROUND

A. EVOLUTION OF MISSILE DEFENSE

Since the dawn of the missile age in 1944, during World War II, the United States has

recognized the need for a defense system against ballistic missiles (Kaplan, 2008). Back

then the threat was realized by Germany’s V-2 rocket, the world’s first ballistic missile.

In the late 1970s, the Soviet Union’s continued growth in the quantity and quality of its

inter-continental ballistic missiles, or ICBMs, forced strategic defense planners to

examine methods of instituting a ballistic defense system.

In a nationally televised speech in 1983, President Ronald Reagan challenged the

scientific community to develop antiballistic missile technologies by launching a new

program, the Strategic Defense Initiative (SDI) (MDA, 2013). The president desired a

strategic alternative to the mutual assured destruction involved with engaging an enemy

with nuclear weapons. This is the same program that became widely identified as the

“Star Wars” program thanks to a critical comment from Senator Edward M. Kennedy of

Massachusetts (Kaplan, 2008).

“It is the policy of the United States to deploy as soon as is technologically

possible an effective National Missile Defense system capable of defending the territory

of the United States against limited ballistic missile attack (whether accidental,

unauthorized, or deliberate) with funding subject to the annual authorization of

appropriations and the annual appropriation of funds for National Missile Defense.” The

preceding statement is taken from the National Missile Defense Act of 1999 (Public Law

106–38). This act not only provided clear direction, it effectively made it official policy

for the United States Government to pursue missile defense (Thielmann, 2009).

Throughout the years, missile defense agencies have taken on different names and

have focused on different threats depending on real world events. Additionally,

technology has advanced at an exponential rate that has allowed significant

improvements in missile defense. Today, President Barrack Obama’s administration is

continuing to evolve an integrated and global ballistic missile defense capability

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(Hildreth & Woolf, 2010). Although the attention has shifted to more current and

evolving threats such as Iran and North Korea (DoD, 2010), the objective remains the

same.

B. THE MISSILE DEFENSE AGENCY

The Missile Defense Agency (MDA) is currently the research, development, and

acquisition agency within the Department of Defense (DoD) that is responsible for

developing a layered defense against limited ballistic missile attack. The MDA’s mission

is to develop a defense system to defend the U.S., our deployed troops, and our Allies

from ballistic missile attacks (Testing, 2009). “Ballistic missile” is a term that refers to

“any missile that does not rely upon aerodynamic surfaces to produce lift and

consequently follows a ballistic trajectory when thrust is terminated” (Lash, 2010). The

Ballistic Missile Defense System (BMDS), as described in Figure 1, is a sophisticated

architecture of networked sensors necessary to detect and track enemy targets, ground

and sea-based interceptor missiles to destroy the enemy targets, and a communications

infrastructure providing operational commanders with the necessary links to manage and

activate all available capabilities (MDA, 2013). In essence, MDA is responsible for

developing, testing, and integrating a grand system of systems in order to engage and

destroy the threat of ballistic missiles.

The MDA is a vast organization that breaks down into several directorates and

branches, each focusing on unique responsibilities. The MDA’s Directorate for Test (DT)

executes BMDS test policy, manages the BMDS Test Baseline, and provides

programmatic and technical direction and oversight of the test program and test resources

(MDA Fact Sheet, 2013). Missile Defense flight tests are designed to provide the BMDS

with test scenarios meant to simulate hostile conditions in order to evaluate BMDS

against the threat. These test scenarios typically involve a target missile launch toward

the BMDS in a manner that would best simulate an actual enemy engagement (Lash,

2010). Ground and flight tests offer DT an opportunity to provide valuable data for

advanced modeling and simulation processes that measure and predict future

performance of all missile defense technologies (MDA Fact Sheet, 2013). It is this data

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that demonstrates the performance of the BMDS and its elements. Because test and

evaluation is so important to the evolution and growth of the BMDS, MDA placed great

emphasis on testing in 2008 and produced notable accomplishments (Testing, 2009).

Figure 1. The Ballistic Missile Defense System

C. TRANSPORTABLE TELEMETRY SYSTEMS

Within the Directorate of Test (DT), the Test Resources Directorate (DTR) is

responsible for managing some of the assets whose primary purpose is to collect test data

during flight test missions. The Transportable Telemetry Systems (TTS) are such assets

and they are dedicated to collecting missile telemetry (TM) data. In 2003, the first TTS

systems (TTS-1 and TTS-2) were developed by MDA/DTR to support BMDS testing in

the Pacific and, when necessary, support out of any land-based range within the

continental United States. The primary purpose of these systems was to collect data from

missiles flying in their midcourse and terminal phases while requiring minimal to no

infrastructure for maintaining effective operations.

Early MDA intercept tests consisted of target missiles, emulating enemy ballistic

missiles, launched from Vandenberg Air Force Base (VAFB), in California, toward the

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Ronald Reagan Ballistic Missile Defense Test Site (RTS) located on the Kwajalein Atoll

in the Marshall Islands (Lash, 2010). More recently, the roles have been reversed and

Exo-atmospheric Kill Vehicle (EKV) interceptors have been launched out of VAFB

while the targets come from RTS. The distance between VAFB and RTS is nearly 5,600

km (Lash, 2010). This broad ocean-occupied distance creates line-of-sight issues, and

serious data collection limitations, for land-based assets. In turn, this creates data

coverage gaps along the trajectories of the missiles. It is this gap that motivated the

requirement for ship-based data collection assets (Lash, 2010). Thus, TTS-1 found a

permanent home aboard the M.V. Pacific Collector in 2006 and TTS-2 aboard the S.S.

Pacific Tracker in 2011, both depicted in Figures 2 and 3.

Figure 2. TTS-1 aboard the M.V. Pacific Collector

Figure 3. TTS-2 aboard the S.S. Pacific Tracker

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The TTS systems are fully redundant stand-alone telemetry tracking systems that

are capable of deploying to anywhere in the Pacific Ocean in order to maximize data

collection efforts for MDA mission flight tests. These systems consist of two 24 ft.

antennas each, SeaTel antennas for satellite communications for real-time telemetry

transmission, and a robust set of back-end instrumentation capable of receiving,

processing, and recording up to 12 streams of TM data redundantly (MDA, 2003). These

antennas, being sea-based, also utilize a third axis, or the roll axis, to compensate for the

rolls of the sea. Therefore, the three axes include the azimuth axis (side to side motion),

the elevation axis (up and down motion), and the roll axis at the base of the dish antenna.

Figure 4 illustrates the three antenna axes.

Figure 4. Azimuth, Elevation, and Roll axis of TTS antenna

The types of flight test missions the TTS systems support require numerous test

assets that include other types of data collection, such as weather, radar, and optics. All

these systems need to be well-coordinated, synchronized, and operational for the count-

down to reach zero, and have a missile launch. For this reason, it is critical that all

systems be as reliable as possible. TTS failures during an operation could potentially

bring the entire schedule to a grinding halt. The TTS systems loiter in the Pacific Ocean

as they await a launch and are the only assets that can collect data during certain sections

of the trajectory. Therefore, these sea assets are mandatory and a launch will not occur

AZIMUTH ELEVATION ROLL

8

without their participation. Thus, the reliability and health of these systems play a key

role in how these complex flight test missions are executed.

D. COLLECTING MISSILE TELEMETRY DATA

The word telemetry is derived from the Greek roots: tele = remote, and metron =

measure. In the case of missile testing, telemetry is the process by which a missile’s

characteristics are measured (such as velocity, spin rate, or system health), converted to

digital signals, modulated, and then transmitted down to a receiving ground station where

the TM stream is demodulated and the missile data is displayed, recorded, and analyzed

(L-3, n.d.). For a typical flight test mission, the TTS systems are assigned to a Test

Support Zone (TSZ) in the Pacific Ocean where they loiter while the mission clock

counts down. At T-0, or the moment of missile launch, land-based sensors with line-of-

sight to the launch pad track the missile and provide the TTS systems, via the

communications infrastructure, cuing information in real-time so that they know where to

expect the missile when it breaks horizon. Prior to horizon break, TTS operators maintain

the antennas in slave mode, which means the antennas orient themselves to azimuth and

elevation angle commands based on pointing cues provided by the sensors that are

actively tracking the missile. Once the missile breaks horizon for the ships, the telemetry

tracking antennas begin receiving the radio frequency (RF) signals directly from the

missile. At this point the receiving antennas deliver the RF signals to the TM

instrumentation that processes, demodulates, and records all the data. Additionally, once

the antennas have line-of-sight and have a successful acquisition of signal (AOS),

antenna operators configure the antennas to operate in auto-track mode, where the

antenna locks onto the missile and tracks it based on the RF coming in and auto-tracking

errors generated at the feed of the antenna.

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III. ANTENNA TRACKING SYSTEMS

A. PARABOLIC ANTENNA BASICS

Prior to any missile test, the missile itself is outfitted with RF transmitters that

radiate data measurements made inside the missile while in flight, much like radio

stations radiate music over certain frequencies via their antenna towers. The only

difference is that instead of music, missiles transmit the data in the form of high bit-rate

one’s and zero’s (typically ranging from 1 to 20 Mbps). Additionally, missiles are highly

dynamic and limited in how much space and power can be allocated for these

transmitters. Therefore, the signals transmitted are not strong and robust like the ones

radio stations transmit from their towers. Therefore, specialized antennas and radio

receivers are required to capture these signals and extract the data being transmitted.

In the case of the TTS systems, 7.3 meter parabolic antennas are used as the

source for tracking and receiving signals transmitted by targets under test. Each of these

antennas comes equipped with its own pedestal that houses the servo control electronics

and the servo amplifiers that provide the high currents needed to energize the antenna-

moving motors. Figure 5 illustrates the TTS tracking antennas aboard one of the sea

vessels, the M.V. Pacific Collector.

Figure 5. The two 7.3m tracking antennas (with radomes removed) utilized by TTS-1

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These antennas make use of a dish-shaped reflector that follows a parabolic

contour. This shape provides reflective properties such that all RF energy illuminating the

dish is reflected and focused at one specific point, known as the focal point of the

antenna. Figure 5 illustrates this concept. The RF energy, depicted by the lines Q1, Q2,

and Q3, illuminates the parabolic dish at points P1, P2, and P3. The parabolic dish then

reflects all this energy onto the focal point, point F. The feed of the antenna, which

encloses or houses the actual elements energized by this received energy, is carefully

located as close to the focal point as possible so as to receive the most amplified version

of the signal being transmitted.

Figure 6. Reflective properties of a parabolic dish antenna

B. AUTO-TRACKING SYSTEMS

A parabolic antenna is an effective means of receiving a weak signal when the

antenna is aligned and pointing directly toward the transmitting object, along its bore

sight. However, there is little reason to test a missile that is static and not flying off into

the sky. Therefore, a parabolic antenna must be able to maintain track, or keep a direct

line-of-sight to the target, in order for the receiving system to be of any value. There are

two ways of maintaining a parabolic dish pointed directly at a moving target: (1) by

configuring the system to track in slave mode and have outside cuing data tell the antenna

11

where to point, or (2) by outfitting the antenna system with a feed subsystem capable of

auto-tracking the transmitting source as it flies into the sky, off the launch-pad.

The first method will work so long as there is cuing data coming in from other

systems tracking the missile. However, a receiving station is of little value if it cannot

track a target, and collect its data, once other sensors can no longer see it. A tracking

antenna should be able to lock on to the signal it is receiving and track the target

throughout its trajectory based on tracking errors generated at the feed. Therefore, a self-

sufficient TM receiving station must be able to auto-track any missile radiating TM that

is within its frequency and link margin range.

In an auto-tracking system, the purpose of the feed is twofold, to receive the RF

signal from the target being tracked and to produce error signals that control the current,

and thus torque, to the azimuth and elevation drive motors that move the antenna

enabling it to follow the source of the transmitted signal automatically. There are three

basic methods for auto-tracking a target and each employs its own unique tracking feed

assembly. These feed assemblies include the conical scan feed (CSF), the single channel

monopulse (SCM), and the electronically scanned feed (RCC, 2008).

The CSF method involves a rotating antenna element within the feed, also known

as a nutator, which creates a cone-shaped scan due to its “wobble” in order to generate

tracking errors based on the amplitude of the incoming target’s signal. The SCM

generates tracking errors by scanning the feed dipoles and comparing phase angle

differences of incoming signals using a diode-switching system. Lastly, the electronically

scanned feed combines the best features of the previous two methods to generate tracking

errors (RCC, 2008). It has been found that electronically scanned feed subsystems have a

superior auto-tracking performance overall (Goswami, Sucharita, & Arya, 2003). For the

purposes of this paper, we will focus on the electronically scanned feed assembly because

the TTS antennas being analyzed for this paper utilize this type of feed assembly system.

12

Figure 7 depicts a representation of what an electronically scanned feed, along

with its five dual linear dipole antennas, looks like when it is facing the dish antenna. The

feed generates a sequence of scanned beams around the bore-sight axis. These beams are

sequentially scanned to four positions in space: beam right, beam down, beam left, and

beam up (Viasat, 2005). The difference channels provide samples of the received energy

in the four different quadrants while the sum channel is aligned with the antenna’s center

axis line, or bore sight, and receives the maximum amount of RF energy off the antenna

reflector. When the antenna is pointing directly at its target, the amplitude and phase of

the frequency received at all the difference channels is the same. As the target moves

away from the antenna bore sight, the feed generates tracking error signals by comparing

phase and amplitude differences between the four difference channels (Mahafza, 2000).

Figure 7. Front panel (faces antenna dish) of an electronically scanned feed subsystem

Difference Channels

Sum or Data Channel

13

For the TTS antennas, the ESCAN is the microwave integrated circuit within the

feed that carries out the computing and switching required for generating the four

scanned beams. By carefully activating different sets of difference channels, the feed is

able to create the four different beams. The ESCAN then uses amplitude modulation of

the received RF to resolve in what direction the antenna needs to move in order to align

itself to the target. For example, in Figure 8 the ESCAN produces a tracking beam up

configuration followed by a tracking beam down. The target is clearly above the bore

sight axis of the antenna and therefore a higher power level, or amplitude, of RF will

reach the antenna when the feed is in the tracking beam up configuration. Tracking error

pulses are generated at the ESCAN and then fed to the antenna control unit (ACU).

Additional processing instructs the antenna’s servo system to move the antenna up in

elevation in order to become aligned to the target so that the data channel receives the

maximum amount of RF again. The phase length of the data channel is matched to the

phase length of the tracking channel, ensuring that the tracking and data channels are

combined correctly to form the scanned beams (ViaSat, 2005).

Figure 8. Example of tracking beams, elevation only

14

C. ANTENNA SYSTEM EVALUATION PARAMETERS

There are multiple methods of evaluating the health of an antenna tracking

system. Figure of merit, or a G/T measurement, is defined as the sensitivity of the front

end antenna. This measurement is a ratio of system gain (G) over system temperature (T)

in dB/K and basically measures how weak a signal the antenna could still receive. Bit-

error rate (BER) tests provide a precise indication of the health of the telemetry receiving

equipment, such as the receivers, by measuring the number of bits in error during a

certain time interval given a certain power level of signal. Ultimately, there are multiple

tests that have been documented in telemetry handbooks meant to qualify a system as

operational and in top condition. However, this paper focuses on other metrics made

available by data recordings made by the antenna control unit of a tracking system.

Parameters such as antenna angular velocity, acceleration, and auto-track errors are

typically not a major focus when it comes to overall antenna assessment when the track is

nominal, i.e., operating normally.

D. ANTENNA CONTROL UNIT (ACU)

A major component of any antenna tracking system is the antenna control unit

(ACU), shown in Figure 9. For the TTS systems, this is the touch-screen computer that

runs the graphical user interface (GUI) that operators use to control the antenna. The

ACU allows operators to move and configure the antenna per the mission requirements.

The ACU is also equipped with internal built-in tests to verify system specifications and

provides data log files with detailed antenna parameter measurements for every track

(given the operator configures for it appropriately).

15

Figure 9. ACU graphical user interface

In effect, the ACU is the “brain” of the entire antenna system. For a mission

requiring a mid-range track, one where the tracking asset does not have line of sight to

the missile on the launch pad, the antenna will require pointing cues from outside sources

so that the antenna knows where the missile in flight will break horizon. The ACU is able

to process these pointing cues and point the antenna where it is being told to point. As the

elevation look angle to the missile rises shortly after horizon break, the operator must

decide when to go from a slave track to auto track. Auto-tracking a target will always

maximize the amount of power received at the feed because the antenna system is

moving based on the RF coming directly from the target. Pointing cues will always have

inaccuracies due to system discrepancies and time latencies inherent in the

communications infrastructure. During the auto-track, the ACU processes the error

signals coming from the feed and controls the servo motors so that the antenna

continually follows the missile flying across the sky.

The ACU system has the capability to record log files, also known as tab files, for

each and every track. These log files record a multitude of parameters inherent to the

antenna system, such as antenna angular velocity, acceleration, and angular positions, at a

16

rate of 10 Hz onto a CSV (comma separated variable) file. It also records the various

states that the ACU was in (standby, manual, slave, auto-track, etc.) due to operator

manual input.

The following is a list of applicable parameters recorded by the ACU tab file:

Parameters: Time: Time from an outside source (GPS timing unit)

Actual: Actual position angle in extended position degrees for each axis.

Commanded: Actual commanded angle in extended position degrees for each axis.

Offset: Dynamic position offset in degrees.

Mode: Axis mode (0= standby, 1 = manual, 2 = slave, 81 = manual mode pending, 82 = slave mode pending)

Upper: Upper limit (“F” 1 = End of travel, 2 = Soft, 4 = Primary, 8 = Secondary)

Lower: Lower limit (“F” 1 = End of travel, 2 = Soft, 4 = Primary, 8 = Secondary)

Interlock: Interlock summary (0 = OK, 1 =set)

Velocity Axis velocity in deg/sec for azimuth, elevation, and roll

Acceleration Axis acceleration in deg/sec2 for azimuth, elevation, and roll

Position Error: The difference between actual position and commanded position

Overspeed: Overspeed status (0 = OK, 1 = overspeed)

axis_stowed: Axis stowed = 1,

Axis not stowed = 0,

Axis Stow/Unstow Operation in

progress = 2

Axis Failed to Stow = -1

autotrack_stat: Autotrack status (-1=Fault, 0=Not Selected, 1=Acquisition, 2= Track (this axis is selected and tracking), 3= Re-Acquisition, 4 = Force Track, 5 = autotrack currently disabled by the Autotrack Mask function)

17

Tracking State Values

Tracking State Indication

-1 Fault

0 Not Active 1 Acquisition 2 Track 3 Re-Acquisition 4 Force Track 5 Autotrack Disabled by Mask

Table 1. Auto-track status values

slave_cmd: The command angle from the slave data port. The ACU can receive slave commands at any time, but they will be ignored unless at least one axis is in slave mode.

Sys_mode: Current system mode (0 = manual, 1 = mission, 2 = reserved, 3 = test, 4 = slave, 5 = stow, 6 = safe mode)

az_auto_error: Azimuth auto-track error in volts (voltage measurement of feed displacement from bore sight or target, i.e., the farther away the feed is from bore sight, the greater the voltage signal)

el_auto_error: Elevation auto-track error in volts (voltage measurement of feed displacement from bore sight or target, i.e., the farther away the feed is from bore sight, the greater the voltage signal)

tr1_sig: Tracking receiver 1 signal strength in dB.

tr2_sig: Tracking receiver 2 signal strength in dB.

tr3_sig: Tracking receiver 3 signal strength in dB.

tr4_sig: Tracking receiver 4 signal strength in dB.

select: Selected receiver signal strength in dB.

The focus of this paper revolves around these tab files and the wealth of

information that they hold. Typically, these files remain unobserved until a failure occurs,

and a root cause investigation begins. By carefully analyzing pertinent parameters within

these tab files following completion of every mission, it is the hypothesis of the author

that telemetry engineers and technicians may be able to identify the symptoms of an

18

oncoming failure. By preemptively assessing the symptoms, preventive maintenance

and/or an early replacement of a part would effectively eliminate the risk of a critical

failure.

19

IV. ANALYSIS

A. DIAGNOSIS AND PROGNOSIS

“Mechanical failures are a pervasive fact of life in our society. Ranging from the failure of small items that all of us have experienced and that many of us take for granted, to the failure of a large complex structure that often becomes front page news, they have undesirable consequences for our society. The large ones many times cause loss of life or cause serious injury to many people. The minor ones sometimes also cause loss of life or injury, and they always cause frustration and anger on the part of the one to whom they occur. Always they cause loss of valuable material, and have undesirable social and economic consequences.”

—Elio Passaglia, executive secretary, MFPG, 1976 (Pusey & Howard, 2008)

Diagnosis is the act of identifying a condition from its signs or symptoms, while

prognosis is the act of predicting a future condition on the basis of present signs and

symptoms (Pusey & Howard, 2008). The goal is to establish a method for identifying

patterns within the data that will provide telemetry operators a better means to achieve an

accurate prognosis when evaluating a TM system. Too often, tabulation file data is

simply not analyzed. Unless a specific need arises or a catastrophic failure occurs during

the support of an event, the tab file is archived and stored away. This chapter will provide

actual data from past events and demonstrate why analysis of this data should become

standard operating procedure for every event a tracking system supports.

B. OIL ANALYSIS–THE IMPORTANCE OF DATA ANALYSIS

Lubrication inspection has been used to help diagnose the internal condition of

oil-wetted components for many years. Most machinery involving moving parts requires

some sort of lubrication to reduce wear. This includes internal combustion and diesel

engines, along with their components such as gearboxes and transmissions. In 1946, the

Denver and Rio Grande Railroad research laboratory successfully linked diesel engine

problems to certain properties found in its used oil (Smith, 2008). By 1955, oil analysis

had matured to the point that it had gained the interest of the United States Naval Bureau

20

of Weapons. A major research program, the Joint Oil Analysis Program, was initiated

involving all the branches of the U.S. Armed Forces and early results proved

conclusively that increases in component wear could be confirmed by detecting

corresponding increases in metal content in the used oil (Smith, 2008). Additionally, in

1958, the program gained traction with two positive results. An oil sample from an R-

1340-AN airplane engine displayed abnormally high levels of iron, copper, and

aluminum. Tear-down of the engine revealed the front impeller bearing had completely

failed (Pusey & Howard, 2008). Months later, a failed cam drive gear in an R-985

airplane was discovered using the same oil inspection techniques (Pusey & Howard,

2008).

Although the oil analysis program was thought of primarily as an engine

condition monitor, the program also discovered that the same technique could identify

potential issues with other components such as gearboxes and transmissions. With time, it

was found that for transmissions and gearboxes it was relatively easy to predict condition

(Pusey & Howard, 2008). Like the same way that human diseases show up in blood

analysis, it was proven that certain malfunctioning parts will manifest themselves as

changes in the properties of a mechanical system’s oil (Pusey & Howard, 2008).

The TTS antennas are electro-mechanical systems with no oil running through

them. Nonetheless, the same concept can be applied to this system by analyzing the

various metrics made available by the ACU’s tab files. By paying close attention to data

fluctuations, TM operators should be able to identify potential problems.

The remainder of this chapter will focus on two failures experienced by each sea-

based TTS system. TTS-1 encountered anomalies during the actual launch-day mission

track of the FTG-06A event. By analyzing ACU tab files for this event, and the prior two

(BVT-01 and SBSS), signs of an oncoming failure will be looked for in the data plots.

Similarly, a year later, the TTS-2 system suffered a critical failure after supporting the

FTI-01 event. Again, ACU tab files for that mission and the one before (AHW-01) will

be analyzed for unforeseen symptoms of a potential problem.

21

The goal is to prove that over time, with enough historical data, predicting certain

failures could become a very realistic scenario like in the case of the Navy’s airplane

transmissions and gearboxes. The focus will be on raw ACU data from past mission

support events. With the advantage of hindsight, we will be able to lay out a timeline of

past anomalies and focus on tab file data leading up to these failures. The expectation is

that we will find indicators, or symptoms, in the data leading up to the system

malfunction.

C. DATA ANALYSIS FOR FAILURE #1

Back in 2010, the TTS-1 system, aboard the M.V. Pacific Collector, had a busy

and rigorous timetable of mission support. Its schedule called for it to support five events

that year, where each event took at least six weeks from planning to execution. Table 2

illustrates the timeline of events for that year.

Mission Event Launch Date

FTG-06 February 2, 2010

HTV-2A April 20, 2010 BVT-01 June 6, 2010 SBSS October 2, 2010

FTG-06A December 15, 2010

Table 2. Timeline of mission events in 2010

During the execution of FTG-06A, the last mission of the year, a failure occurred

with Antenna A during the track of the missile. The roll axis suddenly froze and the

antenna was struggling in auto-track mode, which is usually an indicator that something

is wrong with the antenna feed. The system was designed to be completely redundant for

these types of failures and Antenna B was able to collect all the data without a problem.

Nonetheless, it was a concern that such a problem would sneak up and affect the track at

the last minute since practice runs and daily checkouts found the antenna to be

operational with no exceptions.

The following plots present a subset of all the data made available by the ACU

tab files for both antennas. These plots will illustrate that Antenna A clearly experienced

22

problems throughout the track and although telemetry data was collected, the quality fell

below expectations. Additionally, since the problem with the antenna seemed mechanical

in nature, the focus was on data such as auto-tracking state, auto-tracking errors, and

variation in axis accelerations. Since both antennas are identical and had identical

tracking assignments, any significant difference between the two in performance data

would be of interest.

Figure 10 clearly illustrates that antenna A was having difficulty maintaining

track during the trajectory. The tracking state for antenna A shows that the system lost

auto-track at least six times during the track. When a system drops out of auto-track

mode, the antenna automatically slaves to an outside cueing source for pointing

information. Once the antenna reacquires the RF signal, the ACU will try to auto-track

again. Antenna B, on the other hand, had the kind of track expected of a system operating

in perfect condition. Once the system switched to auto-track mode, the antenna

maintained a clean track throughout the flight. The auto-tracking error plot for antenna A

shows significant deviations from zero, meaning the antenna was having trouble

maintaining accurate pointing. The farther from the bore-sight axis the antenna is, the

higher the voltage for the error plot. Alternatively, antenna B had a stable plot for its

auto-tracking errors, meaning that the feed pointed accurately and was aligned to the

missile in flight. It should also be noted, that errors on these types of plots are expected at

the beginning and end of a track due to the multipath and RF reflections off the ocean

experienced when the antennas are pointed at low elevations as the target breaks, or falls

below, the horizon.

23

Figure 10. Antenna A and B tracking status during FTG-06A support (From TTS-1, Dec 2010)

Figure 11, displayed below, illustrates the difference in antenna performance in

relation to the antenna acceleration along the azimuth and elevation axis. As was noted in

Figure 10, here we also see that antenna A was having difficulty maintaining a smooth

track. The antenna axis acceleration magnifies the subtle changes in antenna velocity.

Therefore, if an antenna is moving at a constant velocity, such as during a smooth track,

the acceleration is a flat line at zero. Alternatively, if the antenna is jittering or gears are

jamming at periodic intervals, the acceleration data will show spikes in the plots.

Typically, antenna movement anomalies are not observable to the naked eye. However,

these plots provide detailed insight as to the overall performance of the motors,

gearboxes, torque limiters, and any other mechanical part involved in the motion of the

antenna.

‐3

‐2

‐1

0

1

2

3

08:13.4

08:45.8

09:18.1

09:50.4

10:22.7

10:55.0

11:27.3

11:59.6

12:31.9

13:04.2

13:36.5

14:08.8

14:41.1

15:13.4

15:45.7

16:18.0

16:50.3

17:22.6

17:54.9

18:27.3

Volts (State)

FTG‐06A TTS‐1 Antenna A ‐ Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

‐2

‐1

0

1

2

3

08:13.4

08:47.9

09:22.4

09:56.9

10:31.4

11:05.9

11:40.4

12:14.9

12:49.4

13:23.9

13:58.5

14:33.0

15:07.5

15:42.0

16:16.5

16:51.0

17:25.5

18:00.0

18:34.5

19:09.0Volts (State)

FTG‐06A TTS‐1 Antenna B ‐ Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

24

Figure 11. Antenna A and B azimuth and elevation accelerations (From TTS-1, Dec 2010)

Figure 12 illustrates the plots of the antenna roll axis accelerations during the

track. As expected, antenna A depicts signs of a problem due to the inconsistent and

irregular motion of the antenna along that axis in a couple instances. Again, antenna B

data shows sign of a smooth and stable track, indicating an optimally performing antenna

system.

‐50

0

5008:13.4

08:41.6

09:09.7

09:37.8

10:05.9

10:34.0

11:02.1

11:30.2

11:58.3

12:26.4

12:54.5

13:22.6

13:50.7

14:18.8

14:46.9

15:15.0

15:43.1

16:11.2

16:39.3

17:07.4

17:35.5

18:03.7

18:31.8

Degrees / sec ^2

FTG‐06A TTS‐1 Antenna A ‐ Axis Acceleration

accelAzim

accelElev

‐40

‐20

0

20

40

60

08:13.4

08:43.4

09:13.4

09:43.4

10:13.4

10:43.4

11:13.4

11:43.4

12:13.4

12:43.4

13:13.4

13:43.4

14:13.5

14:43.5

15:13.5

15:43.5

16:13.5

16:43.5

17:13.5

17:43.5

18:13.5

18:43.5

19:13.5

Degrees / sec ^2

FTG‐06A TTS‐1 Antenna B ‐ Axis Acceleration

accelAzim

accelElev

25

Figure 12. Antenna A and B roll axis acceleration during the track (From TTS-1, Dec 2010)

Figure 13 represents the signal strength received for both antenna systems. This

metric is sometimes also known as AGC (automatic gain control) data because of the

circuitry found inside the telemetry receivers that automatically control the gain of the

signal received. Therefore, if a signal is weak more gain is applied and the AGC level is

high. If a signal is strong, then the AGC level is low. The inverted AGC level then

becomes a good representation of the signal strength received by the telemetry receiving

system. Figure 13 clearly shows that the signal strength received by antenna B is lower

than antenna A. We now have four plots suggesting that indeed antenna A, although

functional, was not operating at an optimal state.

‐20

‐10

0

10

2008:13.4

08:41.6

09:09.7

09:37.8

10:05.9

10:34.0

11:02.1

11:30.2

11:58.3

12:26.4

12:54.5

13:22.6

13:50.7

14:18.8

14:46.9

15:15.0

15:43.1

16:11.2

16:39.3

17:07.4

17:35.5

18:03.7

18:31.8

Degrees / sec ^2

FTG‐06A TTS‐1 Antenna A ‐ Roll Axis Acceleration

accelRoll

‐20

‐10

0

10

20

08:13.4

08:43.4

09:13.4

09:43.4

10:13.4

10:43.4

11:13.4

11:43.4

12:13.4

12:43.4

13:13.4

13:43.4

14:13.5

14:43.5

15:13.5

15:43.5

16:13.5

16:43.5

17:13.5

17:43.5

18:13.5

18:43.5

19:13.5

Degrees / sec ^2

FTG‐06A TTS‐1 Antenna B ‐ Roll Axis Accel

accelRoll

26

Figure 13. Antenna A showing less signal than Antenna B (From TTS-1, Dec 2010)

After a root cause investigation, it was found that the antenna system

experienced an issue when it was powered down and back up the day of the track. Once

the system booted up, the roll axis was having trouble aligning itself to zero degrees and

therefore was introducing an offset in the antenna position. Additionally, a low noise

amplifier (LNA) within the feed was found to performing below specification. This

caused the signal levels received by the antenna to be lower than expected, as seen in the

signal strength recordings in Figure 13.

This failure occurred in December of 2010. Previous missions supported

by this system took place without a problem reported by the telemetry operators. Data

quality numbers derived by counting frame sync pattern locks (once the data is

demodulated and digitized) for the previous events showed that data collection was a

success.

The next step is to plot and analyze data for the missions before FTG-06A

and hunt for potential signs of an oncoming system anomaly. The focus will now be on

the BVT-01 and SBSS mission events supported by the TTS-1 system prior to FTG-06A.

Data metrics such as auto-tracking errors, acceleration of antenna axes, and signal

strength (AGC) will be presented next, in Figures 14 through 17.

‐10

0

10

20

30

4008:13.4

08:49.3

09:25.1

10:00.9

10:36.7

11:12.5

11:48.3

12:24.1

12:59.9

13:35.7

14:11.5

14:47.3

15:23.1

15:58.9

16:34.7

17:10.5

17:46.3

18:22.2

Decibels

FTG‐06A TTS‐1 Tracking Signal Strength Comparison

Tracking AGC Antenna A

Tracking AGC Antenna B

27

Figure 14. Antenna A having trouble maintaining track prior to the FTG-06A event (From TTS-1, Jun 2010)

Not much effort is required to conclude that antenna A was having trouble

maintaining track midway through the missile’s trajectory as illustrated by Figure 14.

Unfortunately, these types of plots were never analyzed post-mission due to the fact that

the customer reported a nominal data collect. Additional plots will be presented for

further comparison.

‐4

‐3

‐2

‐1

0

1

2

3

4

5

27:34.8

28:13.7

28:52.5

29:31.3

30:10.1

30:48.9

31:27.7

32:06.5

32:45.3

33:24.1

34:02.9

34:41.7

35:20.5

35:59.3

36:38.1

37:16.9

37:55.7

38:34.6

39:13.4

39:52.2Volts (State)

BVT‐01 TTS‐1 Antenna A: Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

‐4

‐3

‐2

‐1

0

1

2

3

4

5

27:36.2

28:17.1

28:58.0

29:38.9

30:19.8

31:00.7

31:41.6

32:22.5

33:03.4

33:44.3

34:25.2

35:06.1

35:47.1

36:28.0

37:08.9

37:49.8

38:30.7

39:11.6

39:52.5

40:33.4Volts (State)

BVT‐01 TTS‐1 Antenna B: Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

28

Figure 15. Comparison plots of axis acceleration during the BVT-01 event (From TTS-1, Jun 2010)

‐60

‐40

‐20

0

20

40

60

27:34.8

28:10.2

28:45.5

29:20.8

29:56.1

30:31.4

31:06.7

31:42.0

32:17.3

32:52.6

33:27.9

34:03.2

34:38.5

35:13.8

35:49.1

36:24.4

36:59.7

37:35.0

38:10.4

38:45.7

39:21.0

39:56.3

Degrees / sec ^2

BVT‐01 TTS‐1 Antenna A: Axis Acceleration

accelAzim

accelElev

‐60

‐40

‐20

0

20

40

60

27:36.2

28:13.4

28:50.6

29:27.8

30:05.0

30:42.2

31:19.4

31:56.6

32:33.8

33:11.0

33:48.2

34:25.4

35:02.6

35:39.9

36:17.1

36:54.3

37:31.5

38:08.7

38:45.9

39:23.1

40:00.3

40:37.5

Degrees / sec ^2

BVT‐01 TTS‐1 Antenna B ‐ Axis Acceleration

accelAzim

accelElev

29

Figure 16. Comparison plots of roll axis acceleration during the BVT-01 event (From TTS-1, Jun 2010)

‐15

‐10

‐5

0

5

10

1527:34.8

28:08.6

28:42.3

29:16.0

29:49.7

30:23.4

30:57.1

31:30.8

32:04.5

32:38.2

33:11.9

33:45.6

34:19.3

34:53.0

35:26.7

36:00.4

36:34.1

37:07.8

37:41.5

38:15.3

38:49.0

39:22.7

39:56.4

Degrees/sec ^2

BVT‐01 TTS‐1 Antenna A: Roll Axis Acceleration

accelRoll

‐15

‐10

‐5

0

5

10

15

27:36.2

28:11.8

28:47.4

29:23.0

29:58.6

30:34.2

31:09.8

31:45.4

32:21.0

32:56.6

33:32.2

34:07.8

34:43.4

35:19.0

35:54.7

36:30.3

37:05.9

37:41.5

38:17.1

38:52.7

39:28.3

40:03.9

40:39.5

Degrees / sec ^2

BVT‐01 TTS‐1 Antenna B ‐ Roll Acceleration

accelRoll

30

Figure 17. Tracking signal strength of both antennas during the BVT-01 event (From TTS-1, Jun 2010)

Every plot hints at the fact that something with Antenna A was not right.

Nonetheless, the systems were believed to be in good working condition due to the

nominal readings operators were finding using the usual system checks. Next, we will

examine similar plots but for that of the SBSS event, the one prior to FTG-06A.

The SBSS mission took place in October of 2010. The data analysts reported

“pristine” data, and again the system was thought to be in perfect working condition. The

following plots, Figures 18 through 21, provide a more revealing story when the two

TTS-1 antennas are compared to each other.

0

5

10

15

20

25

30

35

40

27:36.2

28:17.1

28:58.0

29:38.9

30:19.8

31:00.7

31:41.6

32:22.5

33:03.4

33:44.3

34:25.2

35:06.1

35:47.1

36:28.0

37:08.9

37:49.8

38:30.7

39:11.6

39:52.5

40:33.4

Decibels

BVT‐01 TTS‐1 Antenna B ‐ Tracking Signal Strength

Antenna A AGC

Antenna B AGC

31

Figure 18. Tracking status plots for the SBSS mission event (From TTS-1, Oct 2010)

Figure 18 shows that both antennas had a solid track throughout the missile flight

once they both switched to auto-track mode. However, antenna A showed signs of

struggle even though it never lost track once the target was acquired. This can happen

when the antenna is slightly off bore sight, yet maintaining the target within its main

beam width. Therefore, the antenna will still collect good quality data even though it was

slightly off at times.

‐1.5

‐1

‐0.5

0

0.5

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1.5

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2.5

48:11.0

48:41.6

49:12.2

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50:44.0

51:14.6

51:45.2

52:15.8

52:46.5

53:17.1

53:47.7

54:18.3

54:48.9

55:19.5

55:50.1

56:20.7

56:51.3

57:21.9

57:52.5

Volts (State)

SBSS TTS‐1 Antenna A: Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

‐1.5

‐1

‐0.5

0

0.5

1

1.5

2

2.5

48:11.1

48:41.5

49:11.9

49:42.3

50:12.7

50:43.1

51:13.5

51:43.9

52:14.3

52:44.7

53:15.2

53:45.6

54:16.0

54:46.4

55:16.8

55:47.2

56:17.6

56:48.0

57:18.4

57:48.8

Volts (State)

SBSS TTS‐1 Antenna B: Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

32

Figure 19. Axis acceleration plots for the SBSS mission event (From TTS-1, Oct 2010)

‐60

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‐20

0

20

40

60

48:11.0

48:38.9

49:06.8

49:34.7

50:02.6

50:30.5

50:58.4

51:26.3

51:54.2

52:22.1

52:50.1

53:18.0

53:45.9

54:13.8

54:41.7

55:09.6

55:37.5

56:05.4

56:33.3

57:01.2

57:29.1

57:57.0

Degrees / sec ^ 2

SBSS TTS‐1 Antenna A: Axis Acceleration

accelAzim

accelElev

‐60

‐40

‐20

0

20

40

60

48:11.1

48:38.7

49:06.3

49:33.9

50:01.5

50:29.1

50:56.7

51:24.3

51:51.9

52:19.5

52:47.1

53:14.8

53:42.4

54:10.0

54:37.6

55:05.2

55:32.8

56:00.4

56:28.0

56:55.6

57:23.2

57:50.8

Degrees / sec ^ 2

SBSS TTS‐1 Antenna B: Axis Acceleration

accelAzim

accelElev

33

Figure 20. Roll axis acceleration plots for the SBSS mission event (From TTS-1, Oct 2010)

‐10

‐8

‐6

‐4

‐2

0

2

4

6

8

10

48:11.0

48:37.7

49:04.4

49:31.1

49:57.8

50:24.5

50:51.2

51:17.9

51:44.6

52:11.3

52:38.1

53:04.8

53:31.5

53:58.2

54:24.9

54:51.6

55:18.3

55:45.0

56:11.7

56:38.4

57:05.1

57:31.8

57:58.5

Degrees / sec ^ 2

SBSS TTS‐1 Antenna A: Roll Acceleration 

accelRoll

‐10

‐8

‐6

‐4

‐2

0

2

4

6

8

10

48:11.1

48:37.5

49:03.9

49:30.3

49:56.7

50:23.1

50:49.5

51:15.9

51:42.3

52:08.7

52:35.1

53:01.6

53:28.0

53:54.4

54:20.8

54:47.2

55:13.6

55:40.0

56:06.4

56:32.8

56:59.2

57:25.6

57:52.0

Degrees / sec ^ 2

SBSS TTS‐1 Antenna B: Roll Acceleration

accelRoll

34

Figure 21. Tracking signal strength comparisons for the SBSS mission event (From TTS-1, Oct 2010)

Like in the case of the BVT-01 mission, SBSS displayed similar results. Antenna

A was showing signs, or symptoms, of an anomaly. The periodic glitches seen in the

auto-track errors are signs of something mechanical starting to jam. Antenna A was also

showing lower levels of signal strength that could have been related to a faulty LNA

inside the feed or a direct result of the antenna struggling to maintain accurate pointing to

the missile in flight. Clearly, this is valuable information that telemetry operators could

have used at the time to begin a troubleshooting investigation as to why the performance

of antenna A was degraded.

‐5

0

5

10

15

20

25

30

35

4048:11.1

48:40.0

49:08.9

49:37.8

50:06.7

50:35.6

51:04.5

51:33.4

52:02.3

52:31.2

53:00.2

53:29.1

53:58.0

54:26.9

54:55.8

55:24.7

55:53.6

56:22.5

56:51.4

57:20.3

57:49.2

Decibels

SBSS TTS‐1 Tracking Signal Strength Comparisons

Antenna A AGC

Antenna B AGC

35

D. TIMELINE AND DATA ANALYSIS FOR FAILURE #2

Let us now focus on the TTS-2 system, which is identical to TTS-1, but on a

different ship, the S. S. Pacific Tracker. Table 3 describes the timeline of missions

supported by TTS-2.

Mission Event Launch Date

AHW-01 November 16, 2011 FTI-01 October 11, 2012

Table 3. Timeline of mission events in 2011–2012

For every mission both sea-based systems support, the ships they reside on still

have to voyage back to port once the missile has been tracked and data collected. This

can take anywhere from a few days to a couple weeks. While en route, the TM operators

run post-mission checks on the systems by performing solar calibrations and tracking

available satellites. Once the ships arrive in port, hard copies of data deliverables are

shipped out and post-mission maintenance begins. The TM operators wash down the

antennas, lubricate them when necessary, and perform every system check again to

ensure that the systems are in good health, operational, and ready for the next mission.

While TTS-2 was sailing back to port after supporting FTI-01, a problem was

discovered during the post-mission checkouts. During solar calibrations, the antenna was

not pointing at the sun when instructed to. It was off by a few degrees. After some

troubleshooting, it was discovered that the roll axis was slipping and not allowing the

antenna to compensate for the ship’s roll movement due to the ocean. Further root-cause

investigations had to wait until the ship arrived in port.

Once in port, personnel discovered that a gear in the roll axis gearbox had

cracked. When the motor tried moving the roll axis via its gearbox, the shaft simply

rotated in place. The cracked gear could hold no torque and therefore the roll axis was not

going to move. It was fortunate that this occurred after mission support, which gave the

team the time to find a solution to the problem. Like in the previous section, this paper

will analyze ACU tab file data from events leading up to this failure and see if symptoms

are apparent.

36

Data from the AHW and FTI-01 missions will be analyzed. These two missions

were supported without a record of any problems having occurred and data collection

was successful. The goal here is to identify a pattern in the data that would have been

able to alert TM operators of an oncoming failure.

Figure 22 shows that the tracking status plots for both antennas look very similar

and have no significant difference. Both antennas seem to have tracked rather well

throughout the trajectory. As stated previously, these kinds of plots will tend to be noisy

to some degree early on and late in the track. This is due to the fact that at low elevation

angles, the antennas will be affected by multi-path, or RF reflections, off the ocean that

will interfere with the actual signal.

Figure 22. Tracking status comparisons for the AHW mission event (From TTS-2, 2011)

‐3

‐2

‐1

0

1

2

3

38:20.0

38:47.4

39:14.8

39:42.2

40:09.6

40:37.0

41:04.4

41:31.8

41:59.2

42:26.6

42:54.0

43:21.4

43:48.9

44:16.3

44:43.7

45:11.1

45:38.5

46:05.9

46:33.3Axis Title

AHW TTS‐2 Antenna A: Tracking Status

autotrackErrorAxis1

autotrackErrorAxis2

trackingState

‐3

‐2

‐1

0

1

2

3

4

38:20.0

38:47.4

39:14.8

39:42.2

40:09.6

40:37.0

41:04.4

41:31.8

41:59.2

42:26.6

42:54.0

43:21.4

43:48.8

44:16.3

44:43.7

45:11.1

45:38.5

46:05.9

46:33.3Volts (State)

AHW TTS‐2 Antenna B: Tracking Status

autotrackErrorAxis1

autotrackErrorAxis2

trackingState

37

The axis acceleration plots, shown in Figure 23, also provide no proof of a grave

symptom lurking around. Although antenna A seems to be a bit noisier, it is nothing

significant and both antennas seem to have had a smooth track along the azimuth and

elevation axes. The plots for tracking signal strength (not shown) are also very similar

and have no significant differences between the two antennas. The next plots will focus

on the roll axis, which is the antenna part that experienced the failure.

Figure 23. Azimuth and Elevation axis acceleration comparisons for the AHW mission event (From TTS-2, 2011)

‐40

‐30

‐20

‐10

0

10

20

30

40

38:20.0

38:42.7

39:05.4

39:28.1

39:50.8

40:13.5

40:36.2

40:58.9

41:21.6

41:44.3

42:07.0

42:29.7

42:52.4

43:15.1

43:37.9

44:00.6

44:23.3

44:46.0

45:08.7

45:31.4

45:54.1

46:16.8

46:39.5

Degrees / sec ^ 2

AHW TTS‐2 Antenna A: Axis Acceleration

accelAzim

accelElev

‐60

‐40

‐20

0

20

40

60

38:20.0

38:42.7

39:05.4

39:28.1

39:50.8

40:13.5

40:36.2

40:58.9

41:21.6

41:44.3

42:07.0

42:29.7

42:52.4

43:15.1

43:37.8

44:00.6

44:23.3

44:46.0

45:08.7

45:31.4

45:54.1

46:16.8

46:39.5

Degrees / sec ^ 2

AHW TTS‐2 Antenna B: Axis Acceleration

accelAzim

accelElev

38

Contrary to what the previous plots have shown, the roll acceleration plots in

Figure 24 display a significant difference between antennas A and B. There is clearly

something going on with the roll axis of Antenna A, which is where the failed gearbox

came from almost a year later.

Figure 24. Roll axis acceleration comparisons for the AHW mission event (From TTS-2, 2011)

This is an exciting find that lines up with the hypothesis being presented in this

paper. With this type of advanced warning, TM operators can begin investigating what

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150

38:20.0

38:43.7

39:07.4

39:31.1

39:54.8

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40:42.2

41:05.9

41:29.6

41:53.3

42:17.0

42:40.7

43:04.4

43:28.1

43:51.9

44:15.6

44:39.3

45:03.0

45:26.7

45:50.4

46:14.1

46:37.8

Degrees / sec ^ 2

AHW TTS‐2 Antenna A: Roll Axis Acceleration

accelRoll

‐150

‐100

‐50

0

50

100

150

38:20.0

38:43.7

39:07.4

39:31.1

39:54.8

40:18.5

40:42.2

41:05.9

41:29.6

41:53.3

42:17.0

42:40.7

43:04.4

43:28.1

43:51.8

44:15.6

44:39.3

45:03.0

45:26.7

45:50.4

46:14.1

46:37.8

Degrees / Sec ^ 2

AHW TTS‐2 Antenna B: Roll Axis Acceleration

accelRoll

39

the source of the symptom is. At the very least, spare parts can be ordered and made

available in anticipation of a failure.

Next, similar plots will be presented in Figures 25 through 27 for the FTI-01

mission, which is the event TTS-2 supported just before experiencing the failure with the

roll axis on antenna A.

Figure 25. Side by side comparison of tracking status and RF signal strength for the FTI-01 mission event (From TTS-2, 2012)

‐4

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4

39:24.9

40:04.5

40:44.1

41:23.7

42:03.3

42:42.9

43:22.5

44:02.1

44:41.7

45:21.4

46:01.0

46:40.6

47:20.2

47:59.8

48:39.4

49:19.0

49:58.6

50:38.2

51:17.8

51:57.4

Volts (State)

FTI‐01 TTS‐2 Antenna A: Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

‐4

‐2

0

2

4

39:24.9

40:04.5

40:44.1

41:23.7

42:03.3

42:42.9

43:22.5

44:02.1

44:41.7

45:21.3

46:00.9

46:40.6

47:20.2

47:59.8

48:39.4

49:19.0

49:58.6

50:38.2

51:17.8

51:57.4

Volts (State)

FTI‐01 TTS‐2 Antenna B: Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

‐1001020304050

39:24.9

40:06.5

40:48.1

41:29.7

42:11.3

42:52.9

43:34.5

44:16.1

44:57.7

45:39.3

46:20.9

47:02.6

47:44.2

48:25.8

49:07.4

49:49.0

50:30.6

51:12.2

51:53.8

Signal Strenth

FTI‐01 TTS‐2 Tracking Signal Strenth  

Tracking AGC ‐ Side A

Tracking AGC ‐ Side B

40

After reviewing the previous plots for FTI-01, both antennas seemed to have

performed well with no significant difference between the two. We will continue with the

remaining plots to see if the results match what was found in the data from the AHW

mission.

Figure 26. Axis acceleration comparisons for the FTI-01 mission event (From TTS-2, 2012)

The axis acceleration plots do not show much difference in performance between

the two antennas. The two instances where the acceleration goes unstable coincide with

the auto-tracking errors displayed in Figure 25. This occurrence seems to be more of an

RF disturbance coming from the source, most likely due to the spin of the missile than a

mechanical issue with the antenna.

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39:24.9

40:00.9

40:36.9

41:12.9

41:48.9

42:24.9

43:00.9

43:36.9

44:12.9

44:48.9

45:25.0

46:01.0

46:37.0

47:13.0

47:49.0

48:25.0

49:01.0

49:37.0

50:13.0

50:49.0

51:25.0

52:01.0

Degrees / sec ^ 2

FTI‐01 TTS‐2 Antenna A: Axis Acceleration

accelAzim

accelElev

‐60

‐40

‐20

0

20

40

60

39:24.9

40:00.9

40:36.9

41:12.9

41:48.9

42:24.9

43:00.9

43:36.9

44:12.9

44:48.9

45:24.9

46:00.9

46:37.0

47:13.0

47:49.0

48:25.0

49:01.0

49:37.0

50:13.0

50:49.0

51:25.0

52:01.0

Degrees / sec ^ 2

FTI‐01 TTS‐2 Antenna B: Axis Acceleration

accelAzim

accelElecv

41

Thus far, all the FTI data depicts two healthy antennas performing a mission track

with no anomalies. The next plots in Figure 27 will be the ones depicting the roll axis

acceleration.

Figure 27. Roll axis acceleration comparisons for the FTI-01 mission (From TTS-2, 2012)

The roll axis acceleration plots once again provide a clear indication that

something is not right with the roll axis on antenna A. The results are almost identical to

what was seen in the data for the AHW mission. As stated before, shortly after the FTI-01

mission the roll axis on antenna A suffered a critical failure and the interesting fact is that

there were warnings in the data pinpointing the symptoms all along. This is another

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0

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150

39:24.9

40:02.5

40:40.1

41:17.7

41:55.3

42:32.9

43:10.5

43:48.1

44:25.7

45:03.3

45:41.0

46:18.6

46:56.2

47:33.8

48:11.4

48:49.0

49:26.6

50:04.2

50:41.8

51:19.4

51:57.0

52:34.6

53:12.2

Degrees / sec ^ 2

FTI‐01 TTS‐2 Antenna A: Roll Axis Acceleration

accelRoll

‐150

‐100

‐50

0

50

100

150

39:24.9

40:02.5

40:40.1

41:17.7

41:55.3

42:32.9

43:10.5

43:48.1

44:25.7

45:03.3

45:40.9

46:18.5

46:56.2

47:33.8

48:11.4

48:49.0

49:26.6

50:04.2

50:41.8

51:19.4

51:57.0

52:34.6

53:12.2

Degrees / sec ^ 2

FTI‐01 TTS‐2 Antenna B: Roll Axis Acceleration

accelRoll

42

example where careful analysis of the ACU tab files could have better prepared the TM

operators for this occurrence.

E. MISSION PERFORMANCE STANDARDIZATION

The previous two sections broke down two past critical failures in the history of

TTS support, one happening to each sea-based system. After analyzing the tab file data

produced prior to each failure, evidence was found that symptoms did exist prior to the

actual failure. By taking advantage of the fact that we have two identical antennas per

system performing the same exact tasks, this allows us to make valuable side-by-side

comparisons that would be impossible with any other single antenna system. Over time,

data patterns for certain failures can be identified and used for developing accurate

prognosis for different telemetry trackers everywhere.

The next step is to standardize the way the data is presented so that historical

trends can be more easily identified. This may also assist in assessing the performance of

a telemetry system when it supports mission events. As the TTS program manager at

White Sands Missile Range (WSMR), I will implement a plan for performing tab file

analysis for every event each system supports. For this to be useful, a standard way of

presenting the analysis will have to be devised. The following pages will describe the

method that the TTS team at WSMR will use to present the tab file data collected.

Each system mission lead will now have the responsibility of collecting,

analyzing, and presenting tab file results to the rest of the team. The types of plots that

will be presented at these meetings will be identified below. By maintaining the same

format, along with detailed notes of observations, lessons learned, and anomalies,

identifying trends in the long run should become a more feasible task. Every tab file

analysis will be archived for future reference.

Random sample data will be used below for illustrative purposes to show how a

power point presentation will be prepared and organized in the future. This will represent

the tab file analysis document that will be archived.

43

TAB File Data Analysis Presentation

1. Introduction slide - Text

2. Mission description and TTS system objectives - Text

3. Observations and anomalies - Text

4. Antenna A & B tracking AGC (Signal Strength) on same chart, as shown in Figure 28.

Figure 28. Tracking signal strength comparisons will provide a side-by-side look at how much RF energy the antenna was able to capture during

the track of the target.

5. Mission track antenna pointing angles for both antenna A and B, as shown in Figure 29.

Figure 29. Pointing angles for both antennas verifies that both antennas tracked in an identical pattern.

‐10

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20

30

40

48:11.1

48:44.8

49:18.5

49:52.2

50:25.9

50:59.6

51:33.3

52:07.0

52:40.7

53:14.5

53:48.2

54:21.9

54:55.6

55:29.3

56:03.0

56:36.7

57:10.4

57:44.1

Decibels

TTS System Tracking Signal Strength Comparisons

Antenna A AGC

Antenna B AGC

‐100

0

100

200

300

400

27:36.2

28:21.6

29:07.0

29:52.4

30:37.8

31:23.2

32:08.6

32:54.0

33:39.4

34:24.8

35:10.2

35:55.7

36:41.1

37:26.5

38:11.9

38:57.3

39:42.7

40:28.1

Degrees

TTS Pointing Angles

actualAZ ‐ Ant. A

actualEL ‐ Ant. A

actualAZ ‐ Ant. B

actualEL ‐ Ant. B

44

6. Antenna A tracking errors and auto-track state, as shown in Figure 30.

Figure 30. Tracking status will provide data on how accurately the antenna pointed to the target. This plot will also show whether or not the antenna was able to

maintain auto-track.

7. Antenna B tracking errors and auto-track state

Same as #6 but for antenna B

8. Antenna A azimuth and elevation axis accelerations, as shown in Figure

31.

Figure 31. This plot will provide azimuth and elevation axis accelerations for antenna A

9. Antenna B azimuth and elevation axis accelerations

Same as #8 but for antenna B

‐2

‐1

0

1

2

348:11.1

48:46.8

49:22.5

49:58.2

50:33.9

51:09.6

51:45.3

52:21.0

52:56.8

53:32.5

54:08.2

54:43.9

55:19.6

55:55.3

56:31.0

57:06.7

57:42.4Volts (State)

TTS Antenna A: Tracking Status

autotrackErrorAzim

autotrackErrorElev

trackingState

‐40

‐20

0

20

40

46:21.0

46:45.8

47:10.6

47:35.4

48:00.2

48:25.0

48:49.8

49:14.6

49:39.4

50:04.2

50:29.0

50:53.9

51:18.7

51:43.5

52:08.3

52:33.1

52:57.9

53:22.7

53:47.5

54:12.3

54:37.1

55:01.9

Degrees / sec ^ 2

FTI‐01 FTI‐01 Side A

accelAxis1

accelAxis2

45

10. Antenna A roll axis acceleration, as shown in Figure 32.

Figure 32. TTS Antenna Roll Axis Accelerations will provide roll axis accelerations for antenna A

11. Antenna B roll axis acceleration

Same as #10 but for antenna B

12. Ship’s roll (can be taken from either antenna’s file), as shown in Figure

33.

Figure 33. TTS roll angles will provide insight as to the ocean’s conditions endured during the mission track by the antennas and

support personnel.

13. Interpretations and conclusions (text)

‐10

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0

5

1049:09.1

49:38.9

50:08.7

50:38.5

51:08.3

51:38.1

52:07.9

52:37.7

53:07.6

53:37.4

54:07.2

54:37.0

55:06.8

55:36.6

56:06.4

56:36.2

57:06.0

57:35.8

58:05.6

58:35.4

59:05.2

Degrees / sec ^ 2

TTS  Antenna A Roll Axis Acceleration

accelAxis3

‐10

‐5

0

5

10

49:09.1

49:36.3

50:03.5

50:30.7

50:57.9

51:25.1

51:52.3

52:19.5

52:46.7

53:14.0

53:41.2

54:08.4

54:35.6

55:02.8

55:30.0

55:57.2

56:24.4

56:51.6

57:18.8

57:46.0

58:13.2

58:40.4

59:07.6Degrees

TTS Roll Angles

Roll

46

The format described above, by which the data will be organized and presented,

may change and evolve over time, depending on future findings and/or if better methods

are discovered. With time, as TTS engineers and operators become more familiar with

the data plots, anomalies will become easier to spot providing clues to the true health of

the system. So long as the data is analyzed and interpreted on a continuous basis, the

potential will always exist to find patterns in the data that match up to certain part

failures.

47

V. CONCLUSION

A. HYPOTHESIS

The hypothesis outlined in this paper states that the great majority of tracking

system failures exhibit symptoms prior to a complete system breakdown. The ACU tab

file data presented here confirms that for the two scenarios described, indications in the

data of an oncoming failure were evident. Although two specific failure events do not

provide a sufficient sample size to characterize all telemetry trackers, the potential for

isolating problematic components by analyzing historical tab file data is very real.

Performing this type of analysis is nonintrusive and has no negative impacts. This can

only provide benefits and additional detail about the performance of the system.

By identifying potential issues in the early phases, symptoms can be isolated and

resolved before they become critical and/or catastrophic failures. By continually

analyzing the tab files for each antenna system, historical data trends can become more

easily identifiable by applying continuous process improvement techniques. Over time,

symptoms of potential failures can be more easily recognized, remediated in advance, and

overall system downtime will be reduced.

B. RECOMMENDATIONS

This paper described two particular cases in the history of the sea-based TTS

systems. This is hardly the sample size necessary to make conclusive matches between

data patterns and system failures. Nonetheless, the data presented here did prove that

symptoms of an underlying problem can make a presence in the tab files. If this type of

data analysis became a standard amongst test ranges utilizing tracking systems, much

more data would become available.

If multiple ranges began documenting critical failures and performing tab file

analysis on data leading up to that anomaly, much more insight would be gained as to the

relationship between the data patterns and the failures. The question now is, “How do we

get all these ranges to sign up for this?” It is the author’s intent to one day submit a paper

and present this topic at the International Telemetry Conference (ITC). This conference is

48

the perfect forum for disseminating these ideas effectively to ranges utilizing similar

systems. The TTS program at WSMR will begin to implement this type of analysis, as

described in Chapter IV, and discuss this idea with colleagues as opportunities permit.

C. FINAL THOUGHTS

Test ranges, such as White Sands Missile Range, typically employ multiple

telemetry tracking systems several times a week for testing various Department of

Defense (DoD) weapons programs. Very few, if any, perform ACU tab file analysis on a

continuous basis. In an effort to reduce system down-time, test ranges have the

opportunity to strive toward a maintenance strategy that encourages proactive measures

over reactive ones. It is a consensus that it is not cost efficient to wait for a system to fail

before addressing any concerns and tab file analysis is an excellent method for

identifying issues in the making. This paper has presented data analysis supporting the

fact that ACU tab file analysis can assist in detecting issues and critical failures much in

advance, providing supporting personnel with valuable time to do something about it. As

this type of analysis becomes standard operating procedure within the TTS program, the

expectation is that system performance will be better characterized as system downtime

becomes a less frequent event.

49

LIST OF REFERENCES

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Fact Sheet 13-MDA-7128: Ballistic missile defense testing. (2013). Missile Defense Agency. Retrieved March 20, 2013 from http://www.mda.mil/system/testing.html

Goswami, M., Sucharita, B., Arya, P. (2003). Performance evaluation of telemetry stations based on site selection. Defence Science Journal, 53, 233–238.

Hildreth, S. A. & Woolf, A. F. (2010, May 10). Ballistic missile defense and offensive arms reduction: A review of the historical record (Congressional Report No. R41251). Washington DC: Library of Congress Congressional Research Service. Retrieved from Federation of American Scientists website: http://www.fas.org/sgp/crs/nuke/R41251.pdf

Kaplan, L.M. (2008, August 15). Missile defense: The first sixty years (08-MDA-3756). Retrieved from Missile Defense Agency website: http://www.mda.mil/global/documents/pdf/first60.pdf

Lash, M. E. (2010, June). Applicability of DODAP to the conversion of a crane ship to host a ballistic missile defense test radar and telemetry system (Master’s thesis). Retrieved from http://edocs.nps.edu/npspubs/scholarly/theses/2010/Jun/10Jun_Lash.pdf

L-3 Communications Telemetry West (L-3). (n.d.). Telemetry tutorial. Retrieved from L-3 website: http://www.tw.l-3com.com/tutorial/telemetry_tutorial.pdf

Mahafza, B. R. (2000). Radar systems analysis and design using matlab. Boca Raton: Chapman & Hall/CRC.

Missile Defense Agency (MDA). (2003, October). Transportable telemetry system specification. Las Cruces, NM: EMI Technologies

Missile Defense Agency (MDA). (2013, March 12). The ballistic missile defense system (BMDS). Retrieved from MDA website: http://www.mda.mil/system/system.html

National Missile Defense Act of 1999, 10 U.S.C. § 2 (1999).

Pusey, H.C., & Howard, P. L. (2008, May). An historical view of mechanical failure prevention technology. Sound and Vibration. Retrieved from http://www.SandV.com

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Range Commanders Council (RCC). (2008, March). Telemetry (TM) systems radio frequency (RF) handbook (Document 120–08). White Sands Missile Range, NM: RCC Secretariat.

Smith, M. (2008, September). Basics of oil analysis (Form 4015.1). Retrieved from Analysts, Inc. website: http://analystsinc.com/documents/BasicsOA.pdf

Testing: Building Confidence. (2009). Missile Defense Agency. Retrieved March 24, 2013, from http://www.scribd.com/doc/16757438/2009-Missile-Defense-Agency-Programs-

Thielmann, G. (2009, July/August). The national missile defense act of 1999. Arms Control Association. Retrieved from http://www.armscontrol.org/act/2009_07–08/lookingback

Transportable Telemery System-1 Team. (June, 2010). Data log files retrieved from the antenna control units for the BVT-01 mission event. White Sands Missile Range [producer].

Transportable Telemery System-1 Team. (October, 2010). Data log files retrieved from

the antenna control units for the SBSS mission event. White Sands Missile Range [producer].

Transportable Telemery System-1 Team. (December, 2010). Data log files retrieved

from the antenna control units for the FTG-06A mission event. White Sands Missile Range [producer].

Transportable Telemery System-2 Team. (November, 2011). Data log files retrieved

from the antenna control units for the AHW-01 mission event. White Sands Missile Range [producer].

Transportable Telemery System-2 Team. (October, 2012). Data log files retrieved from

the antenna control units for the FTI-01 mission event. White Sands Missile Range [producer].

ViaSat Inc. (2005, December). 7.3-meter L/S-band telemetry autotracking antenna. Operation and Maintenance Manual. Manual Part Number 1043579 Rev. 001.

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INITIAL DISTRIBUTION LIST

1. Defense Technical Information Center Ft. Belvoir, Virginia 2. Dudley Knox Library Naval Postgraduate School Monterey, California