Sensing and Sensing and Communications Using Communications Using Ultrawideband Random Ultrawideband Random Noise Waveforms Noise Waveforms Professor Ram M. Narayanan Professor Ram M. Narayanan Department of Electrical Engineering Department of Electrical Engineering The Pennsylvania State University The Pennsylvania State University University Park, PA 16802, USA University Park, PA 16802, USA Tel: (814) 863-2602 Tel: (814) 863-2602 Email: [email protected]Email: [email protected]2005 AFOSR Program Review for Sensing, 2005 AFOSR Program Review for Sensing, Imaging and Object Recognition Imaging and Object Recognition , Raleigh, , Raleigh, NC, May 26, 2005 NC, May 26, 2005
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Sensing and Communications Sensing and Communications Using Ultrawideband Random Using Ultrawideband Random
Noise WaveformsNoise Waveforms
Professor Ram M. NarayananProfessor Ram M. NarayananDepartment of Electrical EngineeringDepartment of Electrical Engineering
The Pennsylvania State UniversityThe Pennsylvania State UniversityUniversity Park, PA 16802, USAUniversity Park, PA 16802, USA
2005 AFOSR Program Review for Sensing, Imaging and 2005 AFOSR Program Review for Sensing, Imaging and Object RecognitionObject Recognition , Raleigh, NC, May 26, 2005, Raleigh, NC, May 26, 2005
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IntroductionIntroduction
• 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
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Why use noise waveforms?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
• Output of correlator is ALWAYSALWAYS 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 Γ2
• 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
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What can coherency give us?What can coherency give us?
• Polarimetry• Interferometry• Doppler estimation• SAR imaging• ISAR imaging• Monopulse tracking• Clutter rejectionALL USING INCOHERENT NOISE RADAR!!!
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Difficulty of stochastic representationDifficulty of stochastic representationGenerate 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
Γexp(-jΘ)S(ω)
Multiply above signals and perform low-pass filtering
Compute its Inverse Fourier Transform
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Images of two trihedral reflectors under foliage coverage, HH polarization
Trihedral-1Trihedral-2
Trihedral-1
Trihedral-2
Tree-1
Tree-4
Tree-2
Tree-3
Tree-1
Tree-2 Tree-3Tree-4
Target scenario FOPEN SAR image SVA enhanced image
FOPEN SAR imagingFOPEN SAR imaging
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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)
• 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
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Waterfilling examples in radarWaterfilling 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
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Adaptive beamformingAdaptive 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
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Adaptive beamforming Adaptive beamforming examples in noise radarexamples 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 N2
• Possible to achieve coherent beamforming if pseudorandom noise waveform is used at each node
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Radar tagsRadar 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
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Applications of radar tags in Applications of radar tags in noise radarnoise 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
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• 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
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Combat ID definedCombat 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”
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Combat ID approachesCombat 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)
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Noise radar RF tag solution to Noise radar RF tag solution to Combat IDCombat ID