ElectroScience Lab

ULTRA WIDE BAND SPREAD SPECTRUM RADAR

Jodhpur Feb. 28-29, 2008

Bangalore Mar. 3-4, 2008

Eric K. WaltonThe Ohio State University, ElectroScience Lab.

Columbus, OH

walton.1@osu.edu

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BASIC CONCEPT

BASIC NOISE RADAR CONCEPT

NOISE RADAR

X

L.P.F.

SLOW A/D

NOISE GEN.

delay time

UWB antennas

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DIGITAL NOISE RADAR

pseudo- noise #1

lowpassfilter

output

antennas

pseudo-noise #2

clock

delay

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PREVIOUS STUDIES(dual FIFO system)

Teoman Ustun MS Thesis, Design and development of stepped frequency Continuous wave and fifo noise radar sensors For tracking moving ground vehicles OSU EE Dept, 2001.

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DIFFERENT TYPES OF RADAR WAVEFORMS

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SUPPRESSION OF INTERFERENCE/JAMMING

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BUILDING PENETRATION UWB NOISE RADAR

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TRANSMIT

RECEIVE

SIDE VIEW

TRANSMIT

RECEIVE

RECEIVE

RANGEBINS

DUALBISTATICRANGE

BINS

TOP VIEW

Conceptual Scenario for Dual Bistatic Building Penetration Radar

BUILDING PENETRATION UWB NOISE RADAR

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Walton - Wall Penetration Example

• SEQUENCE OF IMAGES SHOWING THE TRACKING OF A HUMAN AS HE WALKS FROM UPPER RIGHT TO LOWER LEFT. • THE HUMAN IS INSIDE A CONCRETE BLOCK BUILDING.• THE RADAR WAS APPROXIMATELY 50 FEET AWAY ON THE OUTSIDE.

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Walton - Wall Penetration Example

NOISERADAR

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TARGET SPECIFIC DIGITAL NOISE RADAR

Computer& digital I/O

64K x 9 FIFOCypress

CY7C4282(100 MHz)

100 MHzD/A

100 MHzD/A

3.4 GHzLO

DATA LOAD (TX & RX)

TX

RX

100 MHz TRANSMIT

WAVEFORM

100 MHZRECEIVE

WAVEFORM

MODULATED RF

RECEIVED RF

LOWPASS

FILTERAUDIO BAND

ANALOG DATATO COMPUTER

Burr BrownDAC900

ANTENNAS3.4 GHz +/- 50 MHz

CLOCK100 MHZ

BPFilt.

BPFilt.

64K x 9 FIFOCypress

CY7C4282(100 MHz)

Target Specific Noise RadarTarget Specific Noise Radar

RIGHT

LEFTSW

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UWB Noise Radar Example

Human Walking Toward the Radar Carrying C-Reflector

3.4 GHz

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PATENT

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RECENT STUDIES

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DOPPLER FROM NOISE

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SIGNAL TO NOISE CALCULATIONS

Here is the model:Let us assume RCS of object: -40 DBSM (1 sq. cm.)Power transmitted: 0.25 wattCenter Frequency: 10 GHzAntenna Power Gain: 5 wrt isotropic: (~7 dBi) Radar Range Equation :

34

22

)4(

LR

GPP t

r

Where Pr is the received reflected power and L is a set of loss factors lumped together (we use 0.5 here).

Eq. 1

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SIGNAL TO NOISE CALCULATIONS

Next, we have signal power received due to thermal noise power at the receiver.

Eq. 2where:k is Boltsman’s constant 1.38*10^-23,T= ambient temperature in deg. Kelvin (taken as 290 deg.)B = bandwidth in Hertz. (We use 300 MHz as the front end frequency bandwidth).This allows us to compute the pre-processing S/N ratio as Pr/Pn.

Eq. 3.

kTBPn

n

rprocpre P

P

N

S

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SIGNAL TO NOISE CALCULATIONS

Then the signal processing power gain is based on the final audio filter BW.

So:

Eq. 4bandwidth) (audio

bandwidth) (RF// . procprefinal NSNS

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SIGNAL TO NOISE CALCULATIONS

We wrote a MATLAB program to evaluate this equation. An example result is shown below for a specific set of conditions:>> nradarG (dB) = 6.9897 Ant. GainPt = 0.25 Power trans.R (m) = 30 Range in metersRCS - DBSM = -40 Target RCS (DBSM)Pr = 6.999e-016 Pow. Rec. (watts)Pno = 1.2006e-012 Noise Pow. Rec. (watts)SoNraw = 0.00058296 S/N power ratio - rawGsp = 60000 Signal processing gainSoNfin = 34.9777 Final signal to noise power ratioPrdbm = -121.5496 Rec. Power (dBm)Pnodbm = -89.206 Rec. N. Power (dBm)SoNfindb = 15.4379 S/N – post processing - dBIf we model it so that we get the post-processing S/N as a function of range, we get figure 1.

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SIGNAL TO NOISE CALCULATIONS

Post processing S/N for -40 DBSM object(based on parameters from previous slide)

Note that at +8 dB S/N, we can see this very small target out to 50 meters.

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CONCLUSIONS

Note that this is not the best that can be done:

The raw data can be further processed using FFT processing.

The final bandwidth then is the incremental bandwidth of the FFT. (sometimes called the bin bandwidth)

In other words we get the signal processing gain of the FFT where a signal can be extracted from the noise. There are examples in some of my data where the signal can not be seen in the raw data but can be seen in the spectral (Doppler) plots. If we process 128 point FFT, for example, we get another factor of 128 signal processing gain.

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NOISE RADAR -BACKGROUND

Publications:“Ultrawide-Band Noise Radar in the VHF/UHF Band,” (co-authors, I.P. Theron, S. Gunawan and L. Cai), IEEE Transactions Antennas Propagation, Volume 47 Number 6, pp. 1080-1084, Jun. 1999.

“Compact Range Radar Cross Section Measurements Using a Noise Radar,” (co-authors, I.P. Theron and S. Gunawan), IEEE Trans. Antennas Propagation, Vol. 46, No. 9, pp. 1285-1288, Sep. 1998.

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NOISE RADAR BACKGROUND

Papers:“Development and Applications of a 16 Channel UHF/L-Band Noise Radar,” (co-author, S. Gunawan), Twentieth Annual Meeting and Symposium of the Antenna Measurement Techniques Association, pp. 210-213, Montreal, Canada, Oct. 26-30, 1998.“Signatures of Surrogate Mines using Noise Radar,” (co-author, L. Cai), AeroSense PIERS Meeting, Orlando, Florida, Apr. 13-17, 1998.“Future concepts for Ground Penetrating Noise Radar,” (invited paper) PIERS Workshop on Advances in Radar Methods, Joint Research Centre of the European Commission (Space Applications Institute), Baveno, Italy, Jul. 20-22, 1998.“Noise Radar A-P Mine Detection and Identification,” Demining MURI review, Night Vision Laboratory, Delphi, Maryland, Aug. 10-13, 1998.“Comparative Analysis of UWB Underground Data Collected Using Step-Frequency, Short pulses and Noise,” (co-author, S. Gunawan), Ultra-Wideband, Short Pulse Electromagnets 3, Proceedings of the Third International Conference on Ultra-Wideband, Short Pulse Electromagnetics, May 27-31, 1996, Albuquerque, New Mexico. (refereed; digest released as book for, Jan. 1997) “Moving Vehicle Range Profiles Measured Using a Noise Radar, “ (co-authors, I.P. Theron, S. Gunawan and L. Cai), 1997 IEEE AP-S Symposium and URSI Meeting, Montreal, Canada, Jul. 13-18, 1997.“Use of Fixed Range Noise Radar for Moving Vehicle Identification,” ARL 1997 Sensors and Electron Devices Symposium, College Park, MD, Jan. 14-15, 1997.“UWB Noise Radar Using a Variable Delay Line,” (co-authors, I. Theron and S. Gunawan), Nineteenth Annual Meeting and Symposium of the Antenna Measurement Techniques Association, Boston, Massachusetts, Nov. 17-21, 1997.“Comparative Analysis of UWB Underground Data Collected using Step-Frequency, Short Pulse and Noise Waveforms,” (co-author, S. Gunawan), AMEREM ‘96 International Conference on “The World of Electromagnetics” Albuquerque, New Mexico, May 27-31, 1996.“ISAR Imaging Using UWB Noise Radar,” (co-authors, V. Fillimon and S. Gunawan), Antenna Measurement Techniques Association Symposium, Seattle, Washington, Sep. 30-Oct. 3, 1996.“Comparison of Impulse and Noise-Based UWB Ground Penetrating Radars,” (co-author, F. Paynter), URSI Radio Science Meeting (Joint with AP-S), Seattle, WA, Jun. 19-24, 1994. “High Resolution Imaging of Radar Targets using Narrow Band Data,” (co-author, A. Moghaddar), Joint URSI Meeting and International IEEE/AP-S Symposium, London, Ontario, Jul. 1991.“Use of Stepped Delay Line Noise Radar for ISAR Imaging in the OSU Compact RCS Measurement Range,” (co-authors S. Gunawan), Joint Tech. Report 732168-2 and 727723-12, The Ohio State University ElectroScience Laboratory, Sep. 1997.

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AVAILABLE AS AN OSU REPORT:

“Signal to Noise Ratio Calculations and Measurements for the OSU Noise Radar”

I. P. Theron, E. K. Walton, S. Gunawan and L. Cai

Technical Report 732168-1, The Ohio State Univ. ElectroScience Laboratory, Nov. 1996

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NOTE THAT THE SPECTRAL DISPERSION OF THE SPHERE MAKES THE ABSOLUTE VALUE OF THE PEAK LOWER EVEN WHILE THE TOTAL ENERGY REMAINS HIGH.

TIME DOMAIN SIGNATURES

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TIME DOMAIN SIGNATURES

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Mathematical Description of the Noise Radar

)2 to0( phase random is

:where

]cos[

n

nn

nn Ah A noise signal can be written as (finite freq. band).

The delayed signal is:

function transfer linedelay )()(~where

])(cos[

dnjd

nnd

n

dnncn

dn

d

eTT

tATh

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The received signal consists of environmental noise

and reflections from both the target of interest and clutter for an overall “target” transfer function of

Next there is the propagation factor (delay and attenuation)

enje

nne eAS )(

~

tnjt

nnt eTT )(

~

in vacuumlight of speed c

targetodistanct t

where

/1 and /2

where2

p

r

rTcr

eT

p

jt np

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The received signal is:

snjs

nns

enn

n

en

n

tn

snnpn

tn

sn

pr

eTT

tA

tTTATth

)(~

system ing transmitt theof influence theincludeswhich

]cos[

])(cos[)(

The output of the mixer (mixing the received signal and the delayed transmitted signal) and remembering that the low pass filter will retain only the difference frequencies, we have

n l

dll

endln

tl

en

n l

dl

tn

snlndlpn

dl

tn

sn

pm

ttTAA

ttTTTTAth

])(cos[2

1

])()(cos[

2

1)(

2

This is the signal part of the S/N value.

Mathematical Description of the Noise Radar

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So what is the “noise” part of the “signal – to - noise ratio”?

1. Output of low pass filter (without external noise)2. External wide band noise sources

1. Lightning2. Man-made unintentional signals3. Jammers

3. External narrow band signal sources1. Radio transmitters2. Computer equipment

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Noise from Low Pass Filter internal processes

Even in the absence of external noise, the LPF will contain DC and some low freq. noise as:

])(cos[

])(cos[)(

)0(0

0

knn

nknn

s

tk

tkAkH

ANH

Leaving out a number of steps, we eventually show that the output signal to noise ratio in the absence of environmental noise is:

bandwidth system theis and

frequency cutoff LPF theis :where

220

s

f

f

s

f

s

no

s

B

B

B

B

N

N

P

P

This is the best that we can hope for.

Mathematical Description of the Noise Radar

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EXTERNAL SOURCE OF WIDE BAND NOISE:

•Assume an external signal with a flat spectrum but that is incoherent with the transmitted radar signal•Power computed as before ( ) •For large BW(noise) the total noise power is thus:

•So the final S/N in this case is:

2AN s2

0 ANNP fsn

f

s

f

s

no

s

B

B

N

N

P

P0

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External source of narrow band signal:

Using similar logic, we can show that the average power at each frequency due to a narrow band source is based on the average power over the BW of the radar (IE: NsA2 ).

Thus we obtain the same total noise power as for the wide band external noise signal with a flat spectrum.

(We simply must compute the total external signal power in the BW of the radar.)

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The signal power must be averaged in the t-domain and the noise power must be computed relative to the signal peak (IE: Lets assume a threshold target detection algorithm).

If we plan on using a threshold level to determine the detection of a target, then we must consider the peak signal response to the peak noise response. (not the average noise power).

We can thus compute the peak response of a random noise with a known power based on a useful number of statistical (sigma) widths.

We usually find that the result yields a requirement of a factor of as much as 10 in the ratio of signal to noise to reliably “detect” a target.

Of course, this depends on the desired ratio of false alarms to missed detections. (As does nearly all radar target detection processes.)

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QUESTIONS? / DISCUSSION?