sensing and communications using ultrawideband random noise waveforms professor ram m. narayanan...
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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
Tel: (814) 863-2602Tel: (814) 863-2602Email: [email protected]: [email protected]
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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 22
OutlineOutline
• Introduction• Why use noise waveforms• Noise waveform modeling• Heterodyne correlation approach• Polarimetric radar applications• Radar imaging applications• Covert communications applications• MIMO network concept• Conclusions
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 33
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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 44
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
spectral bands without mutual interference• Noise waveforms exhibit excellent waveform diversity
characteristics
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 55
Waveform comparisonWaveform comparison
0 500 1000 1500-0.5
0
0.5
1Impulse waveform
Am
plitu
de
0 500 1000 1500-1
-0.5
0
0.5
1LFM waveform
Am
plitu
de
0 500 1000 1500
-2
0
2
Random noise waveform
Time
Am
plitu
de
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Simple noise radar architecture Simple noise radar architecture using homodyne correlatorusing homodyne correlator
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Phase coherence injection 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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 88
Noise waveform - stochastic modelNoise 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 px(X) ► Zero-mean Gaussian
Autocorrelation Rxx(τ) ►Impulse at τ = 0
PSD Sxx(f) ►White, assumed uniform and bandlimited
• Above representation does not permit time-frequency equivalence for tracing the signal through the system
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 99
Noise waveform – time-frequency Noise waveform – time-frequency modelmodel
})](cos{[)()( 0 tttatx
where• a(t) is Rayleigh distributed amplitude that describes
amplitude fluctuations• δω(t) is uniformly distributed frequency that describes
frequency fluctuations [-Δω ≤ δω ≤ +Δω]• average power = ½‹a2(t)›/R0, assuming a(t) and δω(t)
are uncorrelated• center frequency = ω0/2π = f0
• bandwidth = 2Δω/2π = B
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Bandwidth descriptorsBandwidth descriptors
•Narrowband ► B/f0 ≤ 10%
•Ultrawideband (UWB) ► B/f0 ≥ 25%
Although time-frequency representation is inherently narrowband, we extend it to the UWB case owing to its simplicity and ease of signal
analysis
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Alternate time-frequency Alternate time-frequency representationrepresentation
)2sin()()2cos()()( 00 tftstftsts QI
)](2cos[)()( 0 ttftats
)()()( 22 tststa QI
where
)(
)(tan)( 1
ts
tst
I
Q
where sI(t) and sQ(t) are zero-mean Gaussian processes and
f0 is the center frequency
This can be recast as
Rayleigh distributed
Uniformly distributed
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Homodyne correlation noise radarHomodyne correlation noise radar
Noise Source
PowerDivider
TimeDelay
Output
MixerAntenna
Antenna
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Heterodyne correlator noise radarHeterodyne correlator noise radar
NoiseSource
PowerDivider
TimeDelay
Output
Mixer
Antenna
Antenna
LSB Upconverter
OffsetFrequency
Source
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Heterodyne correlation noise radar Heterodyne correlation noise radar signal analysissignal 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, t0 and td are target and internal
delays, and ω′ is the offset frequency
}]cos{[)()( 0 ttatvt
)}](cos{[()()( 0 ddd ttttatv
}))](cos{[()()( 000 ttttatvr
)}](cos{[()()( 0 ddd ttttatv
]cos[)()( 2 avo
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Coherent reflectivity extractionCoherent reflectivity extraction
• 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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 1818
Dual-channel polarimetric noise Dual-channel polarimetric noise radar architectureradar architecture
OSC1PD1
OSC2PD2
DL1
DL2
MXR1
PD4
AMP1
PD6
MXR2
MXR3
ANT1
ANT2
FL1 FL2
Co-polarizedI/Q
Co-polarizedAmplitude
Cross-polarizedAmplitude
AMP3
PD3
AMP2
AMP4
AMP5
AMP6
AMP7
PD5
Cross-polarizedI/Q
IQD1
IQD2
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Time domain Frequency domain
Bandlimited noise waveformBandlimited noise waveform
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Measured point spread functions Measured point spread functions of Channel 1 and Channel 2of Channel 1 and Channel 2
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Approximate resolutionsApproximate resolutions
• Range resolution
where c is speed of light and B is the transmit bandwidth
• Doppler resolution
where Tint is the integration time
BcR 2
int
1Tfd
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B = 1 GHz
Tint = 50 (L), 10 (R) ms
Average ambiguity functionsAverage ambiguity functions
B = 100 MHz
Tint = 50 (L), 10 (R) ms
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 2323
Application examplesApplication examples
• Ground penetration imaging• Arc-SAR imaging• Polarimetric ISAR imaging• Foliage penetration (FOPEN) SAR imaging• Anti-jamming imaging performance
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 2424
Detection of multiple objects: Two metallic plates, 17.8 cm and 43.2 cm depth
Ground penetration imagingGround penetration imaging
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 2525
Detection of non-metallic object: Distilled water in 1 gallon plastic container, depth 7.6 cm
Ground penetration imagingGround penetration imaging
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Detection of polarization-sensitive object: Metallic pipe, parallel to transmit polarization and parallel to scan direction
Ground penetration imagingGround penetration imaging
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 2727
Ground penetrating imagingGround penetrating imagingDetection of polarization-sensitive object: Metallic pipe, parallel to transmit
polarization and perpendicular to scan direction
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 2828
Arc-SAR imagingArc-SAR imagingSAR image of two corner reflectors using a 1-2 GHz random noise radar
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 2929
RGB color composite image of mock airplane (Red=HH, Green=HV/VH, Blue=VV)
Geometry of mock airplane
Polarimetric ISAR imagingPolarimetric ISAR imaging
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 3030
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)
Anti-jamming imaging performanceAnti-jamming imaging performance
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 3232
Covert communications conceptual Covert communications conceptual architecturearchitecture
NoiseSource
PowerDivider
Modulator
MessageSignal
LSB Mixer
Channel 1
Channel 2
De-Modulator
MixerOutput
Transmitter ReceiverChannel 1 is the “key”
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 3333
Diversity implementationsDiversity 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
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Diversity implementation featuresDiversity implementation features
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Polarization diversityPolarization diversityTransmit waveformsTransmit waveforms
• Noise source output ►
• Horizontally transmitted waveform ► ► NoiseNoise
• Modulator output ►
• LSB mixer output ►
• Vertically transmitted waveform ►
► Noise-likeNoise-like
where ω0, ωc, ωm are the center frequency, modulator carrier frequency,
and the modulating frequency respectively
• If , then H and V transmit signals occupy same frequency band!
}]cos{[)()( 0 ttatvn
})cos{()(mod ttv mc
})cos{()()( 0 ttatv mcLSB
}]cos{[)()( 0 ttatvtH
})cos{()()( 0 ttatv mctV
02 c
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 3636
Polarization diversityPolarization diversityReceive waveformsReceive 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 2Spectrum lies between 0 and 2δωδω
• Mixer sum output ►
► Spectrum isSpectrum is ALWAYSALWAYS centered around centered around ωωcc !!! !!!
}]cos{[)()( 0 HHrH ttaAtv
}]cos{[)()( 0 VmcVrV ttaAtv
}]cos{[~
)(~0 HrH tAtv
}]cos{[~
)(~0 VmcVrV tAtv
}]22cos{[)( 0 HVmcdiff tBtv
}]cos{[)( HVmcsum tBtv
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 3737
Noise like signal
White Gaussian noise
Frequency (Hz)Time (s)
Noise and noise-like signal Noise and noise-like signal comparisoncomparison
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 3838
Amplitude and polarization angle of Amplitude and polarization angle of transmitted signaltransmitted signal
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 3939
Temporal variation of electric field vector of the propagating composite wave
1
2
3
4
5
6
Instantaneous polarization vectorInstantaneous polarization vector
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BER performance without codingBER performance without coding
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 4141
BER performance with codingBER performance with coding
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 4242
Phase Shift(delay)
Attenuation
AtmosphericAbsorption Rain Vegetation
Path Loss(distance)
Four factors that may cause distortion:
TransmittedSignal
Received Signal
Channel propagation issuesChannel propagation issues
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 4343
Spectral efficiency issuesSpectral 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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 4444
Noise waveform based Noise waveform based networking schemenetworking 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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 4545
Waterfilling waveform Waterfilling waveform optimizationoptimization
• 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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 4646
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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 4747
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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 4848
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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Noise radar networking advantagesNoise 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
AmplifierNoise Signal Generator
I/Q Correlation Receiver
Antennas
VVI Q
Variable Delay Line
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Proposed netted MIMO noise Proposed netted MIMO noise radar systemradar system
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 5353
Possible field implementationPossible field implementation
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Features of proposed systemFeatures 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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 5555
Combat Identification (Combat ID)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
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 5656
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)
May 26, 2005May 26, 2005 2005 AFOSR S&S Program Review2005 AFOSR S&S Program Review 5858
Noise radar RF tag solution to Noise radar RF tag solution to Combat IDCombat ID
• High spectral efficiency for dense usage
• Covert operation
• LPD capability
• Anti-jam capability
• Adaptable and diverse waveform features
Questions ?Questions ?
Thank YouThank You