1. ElectroScience Lab ULTRA WIDE BAND SPREAD SPECTRUM RADAR Jodhpur  Feb. 28-29, 2008 Bangalore  Mar. 3-4, 2008 Eric K. Walton The Ohio State University, ElectroScience Lab. Columbus, OH walton.1@osu.edu

2. ElectroScience Lab 2 BASIC CONCEPT BASIC NOISE RADAR CONCEPT

3. ElectroScience Lab 3 DIGITAL NOISE RADAR pseudo- noise #1 low pass filter output antennas pseudo-noise #2 clock delay

4. ElectroScience Lab 4 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.

5. ElectroScience Lab 5 DIFFERENT TYPES OF RADAR WAVEFORMS

6. ElectroScience Lab 6 SUPPRESSION OF INTERFERENCE/JAMMING

7. ElectroScience Lab 7 BUILDING PENETRATION UWB NOISE RADAR

8. ElectroScience Lab 8 Conceptual Scenario for Dual Bistatic Building Penetration Radar BUILDING PENETRATION UWB NOISE RADAR

9. ElectroScience Lab 9 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.

10. ElectroScience Lab 10 Walton - Wall Penetration Example NOISE RADAR

11. ElectroScience Lab 11 TARGET SPECIFIC DIGITAL NOISE RADAR Computer & digital I/O 64K x 9 FIFO Cypress CY7C4282 (100 MHz) 100 MHz D/A 100 MHz D/A 3.4 GHz LO DATA LOAD (TX & RX) TX RX 100 MHz TRANSMIT WAVEFORM 100 MHZ RECEIVE WAVEFORM MODULATED RF RECEIVED RF LOW PASS FILTER AUDIO BAND ANALOG DATA TO COMPUTER Burr Brown DAC900 ANTENNAS 3.4 GHz +/- 50 MHz CLOCK 100 MHZ BP Filt. BP Filt. 64K x 9 FIFO Cypress CY7C4282 (100 MHz) Target Specific Noise Radar RIGHT LEFT SW

12. ElectroScience Lab 12 UWB Noise Radar Example Human Walking Toward the Radar Carrying C-Reflector 3.4 GHz

13. ElectroScience Lab 13 PATENT

14. ElectroScience Lab 14 RECENT STUDIES

15. ElectroScience Lab 15 DOPPLER FROM NOISE

16. ElectroScience Lab 16 SIGNAL TO NOISE CALCULATIONS Here is the model: Let us assume RCS of object:-40 DBSM (1 sq. cm.) Power transmitted: 0.25 watt Center Frequency: 10 GHz Antenna Power Gain: 5 wrt isotropic: (~7 dBi) Radar Range Equation : Where Pr is the received reflected power and L is a set of loss factors lumped together (we use 0.5 here). Eq. 1

17. ElectroScience Lab 17 SIGNAL TO NOISE CALCULATIONS Next, we have signal power received due to thermal noise power at the receiver. Eq. 2 where: 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.

18. ElectroScience Lab 18 SIGNAL TO NOISE CALCULATIONS Then the signal processing power gain is based on the final audio filter BW. So: Eq. 4

19. ElectroScience Lab 19 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: >> nradar G (dB) = 6.9897 Ant. Gain Pt = 0.25 Power trans. R (m) = 30Range in meters RCS - DBSM = -40Target RCS (DBSM) Pr = 6.999e-016 Pow. Rec. (watts) Pno = 1.2006e-012Noise Pow. Rec. (watts) SoNraw = 0.00058296 S/N power ratio - raw Gsp = 60000Signal processing gain SoNfin = 34.9777Final signal to noise power ratio Prdbm = -121.5496 Rec. Power (dBm) Pnodbm = -89.206 Rec. N. Power (dBm) SoNfindb = 15.4379S/N – post processing - dB If we model it so that we get the post-processing S/N as a function of range, we get figure 1.

20. ElectroScience Lab 20 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.

21. ElectroScience Lab 21 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.

22. ElectroScience Lab 22 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.

23. ElectroScience Lab 23 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.

24. ElectroScience Lab 24 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

25. ElectroScience Lab 25 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

26. ElectroScience Lab 26 TIME DOMAIN SIGNATURES

27. ElectroScience Lab 27 Mathematical Description of the Noise Radar A noise signal can be written as (finite freq. band). The delayed signal is:

28. ElectroScience Lab 28 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)

29. ElectroScience Lab 29 The received signal is: 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 This is the signal part of the S/N value. Mathematical Description of the Noise Radar

30. ElectroScience Lab 30 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.Lightning 2.Man-made unintentional signals 3.Jammers 3.External narrow band signal sources 1.Radio transmitters 2.Computer equipment

31. ElectroScience Lab 31 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: Leaving out a number of steps, we eventually show that the output signal to noise ratio in the absence of environmental noise is: This is the best that we can hope for. Mathematical Description of the Noise Radar

32. ElectroScience Lab 32  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:

33. ElectroScience Lab 33 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: N s A 2 ). 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.)

34. ElectroScience Lab 34 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.)

35. ElectroScience Lab 35 QUESTIONS? / DISCUSSION?