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Intelligent Automation, Inc.15400 Calhoun Drive, Suite 400
Rockville, MD 20855
Advances in Channel Modeling Tool Based on Bidirectional Analytic Ray Tracing and
Radiative Transfer (CBAR)Intelligent Automation Inc.
Rockville, MD. ITEA Workshop
Las VegasMay 14-16, 2019
This project is funded by the Test Resource Management Center (TRMC) Test and Evaluation/Science & Technology (T&E/S&T) Program through the U.S. Army Program Executive Office for Simulation, Training, and Instrumentation (PEO STRI) under Contract No. W900KK-11-C-0029. Distribution Statement A Distribution: Unlimited
Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Test Resource Management Center (TRMC) and Evaluation/Science & Technology (T&E/S&T) Program and/or the U.S. Army Program Executive Office for Simulation, Training, & Instrumentation (PEO STRI).Approval: AFFTC-PA-12461, 412 TW-PA-13524, 412TW-PA-19265
OverviewDetailed Description– Terrain Preparation– Antenna Pattern Generation– Route Generation– Channel Modeling– Communication Performance– User Interface– Channel Emulation
SummaryCurrent and Future Enhancements
Outline
3
OVERVIEW
Predict bit error rate of air to ground telemetry communications link by incorporating the impact of the following factors:– Terrain– Aircraft position orientation and velocity– Antenna pattern of aircraft and ground stations– Receiver characteristics– Modulation scheme
Objective
CBAR in a nutshell
Ray Tracing &Physical optics
Channel Modeling
Deterministic:
Statistical:
ModelValidation
PerformanceEvaluation
Database/library
CBAR Software
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Low cost approach to studying telemetry link performance for different locations of ground stations, routes, modulation schemes, center frequency and antenna configurations. Ability to portend trouble spots during an aircraft flight when the telemetry link may not be available.As a planning tool to test various suitable locations of ground stations for a given test article trajectory.
Benefits of CBAR
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DETAILED DESCRIPTION-I(Terrain, Antenna, Route)
Terrain PreparationAntenna pattern generationRoute GenerationChannel modelingCommunication performance User interface
Seven Elements of CBAR
Based on elevation data downloaded from USGS and other sources a terrain profile is created.
Element# 1: Terrain
Radiation pattern of ‘antenna on platform’ is critical for telemetry channel modelingMethod of Moments (MoM) is used to model the EM problem of ‘antenna on platform’Antenna and platform are modeled togetherThe power splits and relative phase-shifts between the two antennas, and cable losses are accountedMutual coupling between two antennas (top and bottom)– Found to be minimal in the case of C-12, i.e. ~78dB– primarily due to blockage of the fuselage
Element# 2: Antenna
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Convert antenna pattern into ray tubes3D antenna pattern is represented as triangular mesh on a unit sphere surface– each mesh represents a discretized beam– gain of each beam is simply calculated as the antenna gain of its
center direction
Incorporation of antenna pattern
12
Triangular Mesh Meshed Antenna Pattern
CBAR uses AGI’s route design library to generate routes based on waypoints, speed and altitude information.For flights changing altitude at a fixed rate of climb, IAI has created a Matlab code to find intermediary waypoint that can be used as input to CBAR.
Element# 3: Route
13
Waypoints:
Generated route:
A highly efficient 3D ray-tracing algorithm– Bidirectional ray tracing launches rays from both transmitter and
receiver and path is found when two rays meet.– It employs computational geometry to accurately trace polygon
ray tubes and calculate shadowing and reflection.A set of physics-based EM scattering models– It also incorporates a range of EM scattering models such as
Physical Optics (PO), Physical Theory of Diffraction (PTD)– Multithreading is used to parallelize the scattering computation
across multiple CPU cores.
Element# 4: Channel Modeling
14
Channel Modeling, cont.
15
The channel modeling engineuses bi-directional analytic ray-tracing to estimate time-varying channel impulseresponse for the aircraft toground link.The channel modeling enginetakes into account terraincharacteristics and theantenna patterns of groundstation and aircraft.The time-varying frequencyresponse is computed bytracking the Doppler shiftsassociated with each ray tubethat is launched from theaircraft.
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50
2
4
6x 10
-5
time /us
ampl
itude
RT2Theoretical
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-4
-2
0
2
time /us
phas
e
Bidirectional– Conventional RT shoots rays from Tx; only trace paths of
multiple reflections + one last hop of scattering– BART shoots rays from Tx and Rx; trace all paths of multiple
reflections + one hop of scattering + multiple reflections
Bidirectional Analytic Ray Tracing (BART)
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GO GO
PO
Tx Rx
Tx' Rx'
dx
Analytic– Describes 3D ray tubes as
polygonal cylinders (or cones) and precisely determines shadowing using geometric calculations of polygons
– Problem becomes scalable; independent of wavelength
– Analytic scattering model of polygon surface
– Breaks the wavelength-dependence of algorithm complexity
BART (cont…)
17
Father Ray
Facet
Illumination Area
Passed Region
Child Ray
Blocked Region
The channel modeling engine uses physical theory of diffraction to capture the effects of diffraction.Even when a line of sight link is unavailable due to obstruction from buildings, it is possible to receive signal behind the building due to edge diffraction.
Physical Theory of Diffraction
18
Test case includes two elevated point sources (isotropic antenna pattern) over a real terrain surface of 10km by 10km centered at (34.9369°, 118.0628°) (near Edwards AFB)Compared with UTD-based commercial software
Validation of Channel Modeling
19
0.6 0.65 0.7 0.75 0.8 0.85 0.90
2
4
6
8x 10
-7
time /us
CIR
RT2Wireless Insite
2 2.05 2.1 2.15 2.2 2.25 2.3 2.35 2.4-160
-150
-140
-130
-120
-110
freq /GHz
CIR
/dB
RT2Wireless Insite
RT2
UTD
RT2
UTD
Result Comparison
20
Captures more multi-paths
CPU time MemoryRT2 4min 189MBUTD 36min 968MB
Comparison
21
Ray paths in RT2 Ray paths in UTD
Computation Resources
Channel model is defined as a time-varying, wideband channel with Doppler spread.– 2D matrix format 𝐻𝐻(𝑓𝑓, 𝑡𝑡) with the first dimension defined as
frequency and the second dimension defined as time– at any time step 𝑡𝑡0, 𝐻𝐻(𝑓𝑓, 𝑡𝑡0) represents the channel response in
frequency domain at that particular time instanceDoppler-shift based extrapolation– given the instant velocity of the aircraft, the Doppler of each ray
path can be estimated by taking the projection of the velocity vector on the ray direction.
– for each path, we can predict its variations in vicinity time steps– the extrapolated channel can be calculated by incorporating a
Doppler phase term in each path
Channel Impulse Response
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Communication performance module incorporates the time-varying channel impulse response to predict bit error rate performance (BER).Supported modulation schemes are – SOQPSK-TG– PCM/FM– CPM– OFDM based on WiMax 802.16d, etc.
The user can select either Monte-Carlo based approach or look-up table.The Monte-Carlo based approach captures the effects of multipath and synchronization errors.Look-up table provides fast outputs based on received SNR.The communication performance module also generates multipath profile.
Element# 5: Communication Performance
23
The user interface allows user to (a) setup a scenario, (b) run the simulation, (c) visualize the results, and (d) reporting.
Element# 6: User Interface
24
One of requirements of CBAR is interfacing with a channel emulator such as Spirent S5500. The channel emulator takes fading file that can be replayed.In order to generate the fading file, we first prepare a text file that is compiled using a Spirent proprietary software to produce a fading file that can replayed.CBAR generates the text file for every mission. The fading text file contains the time-varying multipath response, with up to 24 multipath components.The time stamp within each file is 0.2 ms, and the total duration is 1 second, i.e., 5000 lines per file, or multiples thereof.
Element# 7: Channel Emulation
25
We generated a sample file with only two rays that are at delays of 50 ns and 100 ns. We generated data for a duration of 10 seconds.Real part of the first 500 samples of the first and second multipath components (at delay of 50 ns).
Channel Emulation Example
26
0 100 200 300 400 500-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Time steps, 0.2 ms
Sig
na
l am
plit
ud
e
0 100 200 300 400 500-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
The following screenshot is a typical output from a Spirent Emulator
Typical Spirent Output
27
CBAR is a sophisticated yet easy-to-use T&E tool that allows a user to study air-to-ground communications link accounting for several factors, including, terrain, aircraft antenna pattern, modulation scheme, etc.The software has been validated with some test flight data, but validation is a unending process.The capabilities of CBAR can be expanded further in many ways.CBAR may find use at other MRTFBs besides Edwards AFB.CBAR has several niche capabilities that allow it to compete on a commercial front after some modifications.
Summary
28
Since the delivery of CBAR, we added new features to the underlying software under a Navy SBIR effort (Contract No: N6833517C0641, POC: Frederick Werrell).
These features include the following:– Attenuation effects due to rain,– 3D spatial link availability calculations, and– Clutter due to propagation over ocean at different sea states.
New Features
29
As part of another ongoing Navy SBIR effort (Contract Number: N68335-18-C-0528, POC: Robert Rumbaugh), IAI will transform CBAR into a radar propagation modeling tool.
We will add effects such as sea clutter, ducting, and time-variations due to target and ocean movement.
We will automate and optimize the terrain processing for speeding up the computations.
Future Enhancements
30
IAI would like to thank the following people for their technical, contractual and managerial support during this project:– Tom Young– Mark Radke– Kip Temple– Mark Santiago– Liz Walden– Thomas O’Brien– Peter Weed– Michael Thomasson– Michael Rice– Erik Perrins– Scott Kujiraoka– Marnita Harris– Glenda Torres– Dean Reiser
Acknowledgements
31