1. Sensing and Communications Using Ultrawideband Random Noise Waveforms Professor Ram M. Narayanan Department of Electrical Engineering The Pennsylvania State University University Park, PA 16802, USA Tel: (814) 863-2602 Email: ram@ee.psu.edu 2005 AFOSR Program Review for Sensing, Imaging and Object Recognition, Raleigh, NC, May 26, 2005 2005 AFOSR Program Review for Sensing, Imaging and Object Recognition, Raleigh, NC, May 26, 2005

2. May 26, 20052005 AFOSR S&S Program Review2 Outline Introduction Why use noise waveforms Noise waveform modeling Heterodyne correlation approach Polarimetric radar applications Radar imaging applications Covert communications applications MIMO network concept Conclusions

3. May 26, 20052005 AFOSR S&S Program Review3 Introduction Military operations require low probability of intercept (LPI), low probability of exploitation (LPE), low probability of detection (LPD), and anti-jam characteristics Traditional radar and communications systems use conventional deterministic waveforms Deterministic waveforms (such as impulse/short- pulse and linear/stepped frequency modulated) do not possess above desirable features

4. May 26, 20052005 AFOSR S&S Program Review4 Why use noise waveforms? Noise waveforms are inexpensive to generate both in analog and digital formats Noise waveforms have featureless LPI/LPD characteristics and are therefore covert Noise waveforms are inherently anti-jam and interference resistant Noise sources are easily obtained using current microwave and RF circuit technology Noise waveform spectral characteristics can be adaptively shaped to suit the dynamic environment Noise waveforms are spectrally very efficient and can share spectral bands without mutual interference Noise waveforms exhibit excellent waveform diversity characteristics

5. May 26, 20052005 AFOSR S&S Program Review5 Waveform comparison

6. May 26, 20052005 AFOSR S&S Program Review6 Simple noise radar architecture using homodyne correlator

7. May 26, 20052005 AFOSR S&S Program Review7 Phase coherence injection Homodyne correlation noise radar downconverts directly to DC and hence loses important phase information of returned signal There is a way to inject phase coherence in noise radar using time-delayed and frequency- offset transmit replica Heterodyne correlation noise radar downconverts to offset frequency and preserves phase information of returned signal

8. May 26, 20052005 AFOSR S&S Program Review8 Noise waveform - stochastic model Thermal noise is stochastic and can therefore only be described by its statistics Noise signal x(t) can described as follows:  PDF p x (X) ► Zero-mean Gaussian  Autocorrelation R xx (τ) ►Impulse at τ = 0  PSD S xx (f) ►White, assumed uniform and bandlimited Above representation does not permit time-frequency equivalence for tracing the signal through the system

9. May 26, 20052005 AFOSR S&S Program Review9 Noise waveform – time-frequency model where a(t) is Rayleigh distributed amplitude that describes amplitude fluctuations δω(t) is uniformly distributed frequency that describes frequency fluctuations [ - Δ ω ≤ δω ≤ +Δ ω] average power = ½ ‹ a 2 (t) › /R 0, assuming a(t) and δω(t) are uncorrelated center frequency = ω 0 /2π = f 0 bandwidth = 2 Δ ω/2π = B

10. May 26, 20052005 AFOSR S&S Program Review10 Bandwidth descriptors Narrowband ► B/f 0 ≤ 10% Ultrawideband (UWB) ► B/f 0 ≥ 25% Although time-frequency representation is inherently narrowband, we extend it to the UWB case owing to its simplicity and ease of signal analysis

11. May 26, 20052005 AFOSR S&S Program Review11 Alternate time-frequency representation where where s I (t) and s Q (t) are zero-mean Gaussian processes and f 0 is the center frequency This can be recast as Rayleigh distributed Uniformly distributed

12. May 26, 20052005 AFOSR S&S Program Review12 Homodyne correlation noise radar Noise Source Power Divider Time Delay Output Mixer Antenna

13. May 26, 20052005 AFOSR S&S Program Review13 Heterodyne correlator noise radar Noise Source Power Divider Time Delay Output Mixer Antenna LSB Upconverter Offset Frequency Source

14. May 26, 20052005 AFOSR S&S Program Review14 Heterodyne correlation noise radar signal analysis Transmit waveform ► Received waveform ► Time-delayed transmit replica ► Time-delayed and frequency-offset transmit replica ► Low-pass filtered correlator output when both delays match (zero otherwise) ► where Γ and Θ are magnitude and phase of target reflectivity, t 0 and t d are target and internal delays, and ω ′ is the offset frequency

15. May 26, 20052005 AFOSR S&S Program Review15 Coherent reflectivity extraction ALWAYSOutput of correlator is ALWAYS at offset frequency!! UWB transmit waveform collapses to a single frequency! We can shrink detection bandwidth at correlator output to enhance SNR Power in correlator output is proportional to Γ 2 I/Q detector in receiver can measure Θ Doppler, if any, will modulate correlator output and can be extracted from the I/Q detector Offset frequency usually lies between 10-15% of center frequency of transmission

16. May 26, 20052005 AFOSR S&S Program Review16 What can coherency give us? Polarimetry Interferometry Doppler estimation SAR imaging ISAR imaging Monopulse tracking Clutter rejection ALL USING INCOHERENT NOISE RADAR!!!

17. May 26, 20052005 AFOSR S&S Program Review17 Difficulty of stochastic representation Generate random signal s(t) Calculate its Fourier Transform S(ω) Generate the offset- frequency Fourier Transform S(ω-ω′) Generate the reflected signal Fourier Transform Γ exp (-jΘ)S(ω) Multiply above signals and perform low-pass filtering Compute its Inverse Fourier Transform

18. May 26, 20052005 AFOSR S&S Program Review18 Dual-channel polarimetric noise radar architecture

19. May 26, 20052005 AFOSR S&S Program Review19 Time domain Frequency domain Bandlimited noise waveform

20. May 26, 20052005 AFOSR S&S Program Review20 Measured point spread functions of Channel 1 and Channel 2

21. May 26, 20052005 AFOSR S&S Program Review21 Approximate resolutions Range resolution where c is speed of light and B is the transmit bandwidth Doppler resolution where T int is the integration time

22. May 26, 20052005 AFOSR S&S Program Review22 B = 1 GHz T int = 50 (L), 10 (R) ms Average ambiguity functions B = 100 MHz T int = 50 (L), 10 (R) ms

23. May 26, 20052005 AFOSR S&S Program Review23 Application examples Ground penetration imaging Arc-SAR imaging Polarimetric ISAR imaging Foliage penetration (FOPEN) SAR imaging Anti-jamming imaging performance

24. May 26, 20052005 AFOSR S&S Program Review24 Detection of multiple objects: Two metallic plates, 17.8 cm and 43.2 cm depth Ground penetration imaging

25. May 26, 20052005 AFOSR S&S Program Review25 Detection of non-metallic object: Distilled water in 1 gallon plastic container, depth 7.6 cm Ground penetration imaging

26. May 26, 20052005 AFOSR S&S Program Review26 Detection of polarization-sensitive object: Metallic pipe, parallel to transmit polarization and parallel to scan direction Ground penetration imaging

27. May 26, 20052005 AFOSR S&S Program Review27 Ground penetrating imaging Detection of polarization-sensitive object: Metallic pipe, parallel to transmit polarization and perpendicular to scan direction

28. May 26, 20052005 AFOSR S&S Program Review28 Arc-SAR imaging SAR image of two corner reflectors using a 1-2 GHz random noise radar

29. May 26, 20052005 AFOSR S&S Program Review29 RGB color composite image of mock airplane (Red=HH, Green=HV/VH, Blue=VV) Geometry of mock airplane Polarimetric ISAR imaging

30. May 26, 20052005 AFOSR S&S Program Review30 Images of two trihedral reflectors under foliage coverage, HH polarization Trihedral-1 Trihedral-2 Trihedral-1 Trihedral-2 Tree-1 Tree-4 Tree-2 Tree-3 Tree-1 Tree-2Tree-3 Tree-4 Target scenario FOPEN SAR image SVA enhanced image FOPEN SAR imaging

31. May 26, 20052005 AFOSR S&S Program Review31 Simulated ISAR images of a MIG-25 airplane: no jamming (top), LFM radar image with SJR = -10 dB (top right), and noise radar image with SJR = -10 dB (right) Anti-jamming imaging performance

32. May 26, 20052005 AFOSR S&S Program Review32 Covert communications conceptual architecture Noise Source Power Divider Modulator Message Signal LSB Mixer Channel 1 Channel 2 De- Modulator Mixer Output TransmitterReceiver Channel 1 is the “key”

33. May 26, 20052005 AFOSR S&S Program Review33 Diversity implementations Polarization diversity: Channels 1 and 2 transmitted over orthogonal polariztions Band stacking (Frequency diversity): Channels 1 and 2 are made to occupy contiguous spectral bands Delay diversity (Time diversity): Channel 2 delayed and transmitted after Channel 1

34. May 26, 20052005 AFOSR S&S Program Review34 Diversity implementation features

35. May 26, 20052005 AFOSR S&S Program Review35 Polarization diversity Transmit waveforms Noise source output ► NoiseHorizontally transmitted waveform ► ► Noise Modulator output ► LSB mixer output ► Vertically transmitted waveform ► Noise-like ► Noise-like where ω 0, ω c, ω m are the center frequency, modulator carrier frequency, and the modulating frequency respectively If, then H and V transmit signals occupy same frequency band!

36. May 26, 20052005 AFOSR S&S Program Review36 Polarization diversity Receive waveforms Horizontally received signal ► Vertically received signal ► Amplitude limited horizontally received signal ► Amplitude limited vertically received signal ► Mixer difference output ► Spectrum lies between 0 and 2 δω ► Spectrum lies between 0 and 2 δω Mixer sum output ► Spectrum is ALWAYS centered around ω c !!! ► Spectrum is ALWAYS centered around ω c !!!

37. May 26, 20052005 AFOSR S&S Program Review37 Noise like signal White Gaussian noise Frequency (Hz)Time (s) Noise and noise-like signal comparison

38. May 26, 20052005 AFOSR S&S Program Review38 Amplitude and polarization angle of transmitted signal

39. May 26, 20052005 AFOSR S&S Program Review39 Temporal variation of electric field vector of the propagating composite wave 1 2 3 4 5 6 Instantaneous polarization vector

40. May 26, 20052005 AFOSR S&S Program Review40 BER performance without coding

41. May 26, 20052005 AFOSR S&S Program Review41 BER performance with coding

42. May 26, 20052005 AFOSR S&S Program Review42 Phase Shift (delay) Attenuation Atmospheric Absorption RainVegetation Path Loss (distance) Four factors that may cause distortion: Transmitted Signal Received Signal Channel propagation issues

43. May 26, 20052005 AFOSR S&S Program Review43 Spectral efficiency issues Since independently generated noise waveforms are uncorrelated, they can share same spectral space Non-interference feature is useful in MIMO-type polarimetric applications to avoid cross- polarization contamination In MIMO-type radar networking applications, many more users can be added when using noise waveforms compared to conventional waveforms

44. May 26, 20052005 AFOSR S&S Program Review44 Noise waveform based networking scheme Ultrawideband (UWB) noise used for attaining spread spectrum characteristics UWB noise radar is used for high-resolution covert target detection, tracking, and imaging Fragmented slices within noise band can be used for network communications (node to node and node to base station) Camouflaged communications appears “noise like” to adversary

45. May 26, 20052005 AFOSR S&S Program Review45 Waterfilling waveform optimization Waterfilling optimization maximizes mutual information between input and output MIMO noise radar has many options available for optimization Waterfilling options in radar include polarization, operating frequency range, transmit bandwidth (resolution), spectral shaping

46. May 26, 20052005 AFOSR S&S Program Review46 Waterfilling examples in radar FOPEN applications: Higher signal losses through foliage for vertical polarization (due to vertically oriented trees) may imply the need for diverting larger fraction of transmit power to horizontal polarization Imaging applications: Higher bandwidth can be used to achieve better resolution from aspect locations where higher resolution is necessary to image finer identifying features of the target, while lower bandwidth (thus better spectrum usage) may be used from aspect locations where finer features may be concealed in the shadow region

47. May 26, 20052005 AFOSR S&S Program Review47 Adaptive beamforming Adaptive beamforming has been suggested for sensor networks Individual nodes respond to commands from base station and coordinate their transmissions to accomplish coherent beamforming MIMO radar can greatly benefit from this approach

48. May 26, 20052005 AFOSR S&S Program Review48 Adaptive beamforming examples in noise radar Noise radar nodes can receive “pings” from base station through the covert spectrally fragmented bands Standard approach would be an incoherent beamforming scheme since different noise waveforms are uncorrelated and phase synchronization is not possible Incoherent beamforming may only improve received power advantage by a factor of N instead of N 2 Possible to achieve coherent beamforming if pseudorandom noise waveform is used at each node

49. May 26, 20052005 AFOSR S&S Program Review49 Radar tags Radar tag is a wireless device that can embed information into radar data acquisition by receiving radar pulses, modifying and coding these, and retransmitting them back to the radar Backscatter modulation is primarily used in sensor networks to interrogate remote devices

50. May 26, 20052005 AFOSR S&S Program Review50 Applications of radar tags in noise radar Simultaneous “tagging” by each noise radar will not cross-pollinate other noise radars due to uncorrelated nature of the transmissions Radar tag can be designed with specific frequency dependence to be adaptive to environment conditions as viewed by each node Radar tags can also be used to covertly communicate information about target from one radar node to another

51. May 26, 20052005 AFOSR S&S Program Review51 Noise radar networking advantages UWB Noise Radar Technology –Noise-like transmissions for covert operations –Large signal bandwidth, hence excellent range resolution –LPI/LPD, anti-jam, and interference-resistant characteristics –Efficient use of the frequency spectrum –Low cost and compact Ad hoc Sensor Networks –Deployed inside or around scene of interest –Low-cost, low-power, untethered, multi-functional sensing devices –Data-processing and communication –Powerful protocol stack –Fault-tolerant and scalable –Application dependent

52. May 26, 20052005 AFOSR S&S Program Review52 Proposed netted MIMO noise radar system

53. May 26, 20052005 AFOSR S&S Program Review53 Possible field implementation

54. May 26, 20052005 AFOSR S&S Program Review54 Features of proposed system It has LPI/LPD characteristics for detection, tracking, and imaging It can be used for covert communications and signaling It is based on a self-organized network-centric architecture The network can be used for both high and low data rate applications Network possesses high spectral efficiency

55. May 26, 20052005 AFOSR S&S Program Review55 Combat Identification (Combat ID) About 3-5% fatalities in war are due to friendly forces mistakenly targeting military targets of friendly forces (called fratricide) Problem is exacerbated due to adverse environmental conditions (fog/rain), harsh ground clutter, multitude of benign-looking target types (cars, etc.), crowded EM spectrum, and need to remain covert/LPD/anti-jam Solution requires multiple disciplines, such as sensing, communications, networking, image processing, fuzzy logic, information management, and decision sciences Take Aways from the Combat Identification Systems Conference (CISC) held in Portsmouth, VA, May 23- 26, 2005

56. May 26, 20052005 AFOSR S&S Program Review56 Combat ID defined “The process of attaining an accurate characterization of detected objects in the joint battlespace to the extent that high confidence, timely application of tactical military options and weapons resources can occur”

57. May 26, 20052005 AFOSR S&S Program Review57 Combat ID approaches Thermal signatures RF tags on vehicle Dynamic optical tags (DOTs) using lasers Millimeter wave cooperative transponder Microwave long range RF tags Digital radio frequency tags (DRAFTs)

58. May 26, 20052005 AFOSR S&S Program Review58 Noise radar RF tag solution to Combat ID High spectral efficiency for dense usage Covert operation LPD capability Anti-jam capability Adaptable and diverse waveform features

59. Questions ? Thank You