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Welcome To Our Presentation
Presented By:
S. M. M. Hossain MahmudStudent ID:090924ECE DisciplineKhulna UniversityKhulna-9208.
A. K. M. Tohidur RahmanStudent ID:090918ECE DisciplineKhulna UniversityKhulna-9208.
Tapan Kumar BiswasStudent ID:090933ECE DisciplineKhulna UniversityKhulna-9208.
Electronics and Communication Engineering Discipline Khulna University Khulna-9208.
10/31/2013 2
Supervised By:Shakila NazninLecturerECE DisciplineKhulna UniversityKhulna-9208.
External Member:Md. Abdul AlimAssistant Professor ECE Discipline Khulna University Khulna-9208.
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Thesis Title
Analysis of Target Detection Performance and Reduction of Interrupting Signals at the Receiver of Coherent MIMO Radar Using Space Time Adaptive
Processing
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Outline
Introduction
MIMO Radar
Types of MIMO Radar
Detection performance Analysis of Coherent MIMO Radar
Space Time Adaptive Processing (STAP)
STAP Architecture
STAP Mechanism
Reduction of interrupting signals
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Introduction
Radar: Radio detection and Ranging.
It radiates energy into space and detect echoes reflected from target.
What is Radar?
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Radar Function
Detection
Determining the received signal is an echo return from target.
Directly related to SNR at the receiver end.
Parameter estimation
Range
Velocity
Angle
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What is MIMO Radar?
MIMO Radar
A radar system that employs multiple transmit waveforms and has the
ability to simultaneously process signals received at multiple antennas.
Every antenna element transmits different waveforms.
Matched filtering used at receiver for waveforms diversity.
Antenna elements of MIMO radar can be co-located or distributed.
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Target
Rx
Tx
MIMO Radar System
Fig. 1: MIMO Radar system
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Types of MIMO Radar
Statistical MIMO Radar:
Has often widely spaced apertures.
The target response for each transmitter-receiver pair is statistically
independent.
Its applicable to different look angles or different frequencies.
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Coherent MIMO radar
Closely spaced apertures
Operating on the same frequency
Same target response to all transmitter-receiver pairs
Target localization by coherent MIMO radar offers high resolution
Types of MIMO Radar
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Why MIMO Radar?
Reduce coherent energy on target
Supports multiple sensors
Offers localization with high accuracy.
Handling of multiple targets
Improved Doppler processing through diversity of look angles
Mitigation of the problem of low radial velocities
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-20 -15 -10 -5 0 5 10 15 20 250
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1probability of detection for coherent MIMO radar
SNR(dB)
prob
abili
ty o
f de
tect
ion
Coherent MIMO,M=1, N=5
Coherent MIMO,M=5, N=5Coherent MIMO,M=9, N=5
Fig. 2: Probability of Detection Plotted vs SNR for Coherent MIMO Radar for variable M.
Probability of Detection for Variable M
The equation for is
Depends on Number of receiving
antennas SNR
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-20 -15 -10 -5 0 5 10 15 200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1probability of detection for coherent MIMO radar
SNR(dB)
pro
babili
ty o
f dete
ction
Coherent MIMO,M=5, N=1
Coherent MIMO,M=5, N=5Coherent MIMO,M=5, N=9
Coherent MIMO,M=5, N=13
The equation for is
Fig. 3: Probability of Detection Plotted vs SNR for Coherent MIMO Radar for variable N
Probability of Detection for Variable N
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-20 -15 -10 -5 0 5 10 15 200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1probability of detection for coherent MIMO radar with STC waveforms
SNR(dB)
prob
abili
ty o
f de
tect
ion
STC-MIMO,M=1, N=5
STC-MIMO,M=4, N=5STC-MIMO,M=9, N=5
Probability of Detection with STC for Variable M
The equation for is
Fig. 4: Probability of Detection Plotted vs SNR for STC Coherent MIMO Radar for variable M
Depends on Numbers of transmitting
pulses Numbers of receiving antenna SNR
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-20 -15 -10 -5 0 5 10 15 200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1probability of detection for coherent MIMO radar with STC waveforms
SNR(dB)
pro
babili
ty o
f dete
ction
STC-MIMO,M=5, N=1
STC-MIMO,M=5, N=5STC-MIMO,M=5, N=9
STC-MIMO,M=5, N=13
The equation for
Fig. 5: Probability of Detection Plotted vs SNR for STC Coherent MIMO Radar for variable N
Probability of Detection with STC for Variable N
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Comparison of probability of detection between with and without STC
Fig. 6: Comparison between Probability of Detection Plotted vs SNR for with and without STC
-20 -15 -10 -5 0 5 10 15 200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1Comparison of probability detection
SNR(dB)
pro
bability o
f dete
ction
STC-MIMO,M=5, N=5
MIMO,M=5, N=5
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A. K. M. Tohidur Rahman
090918
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Space Time Adaptive Processing(STAP)
Space Time Adaptive Processing
Refers to the ability to simultaneously process spatial sensor and temporal input data
Offers clutter and jamming cancellation to detect moving targets.
Its basically an adaptive filter, which can filter over the spatial and temporal (or time) domain.
The goal of STAP:
It takes a hypothesis that there is a target at a given location and velocity
Its create a filter that has high gain for that specific location and velocity, and while applying proportional attenuation for all signals.
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2-D Interfering (clutter, jammer) signal locations are not precisely defined
Required rejection (side lobe level) is not achievable with conventional
filtering in presence of system errors
Beam broadening that results from uniformly lowering side lobes with
heavy tapers is not needed
Improved minimum detectable velocity and angle coverage close to
jamming
Why Space-Time-Adaptive-Processing?
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Adaptive Array Processing
Fig. 7: A linear adaptive array
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} N antennas
} M pulses
} NM weights (degrees of
freedom)
Z
T TT T TT T TT
w11 w1M wN1 wNM
STAP output = WY
STAP weightmatrix
Signal Outputw = R–1S R = covariance matrix
S = steering vector
Optimum weights
...
Space-Time Adaptive Processing
Fig. 8: Optimize Space-Time Adaptive Processing
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Dimensionality can be very large: NM can be 102 to >104
Covariance matrix unknown a priori and must be estimated from the radar
data
Large search space of interest
Space-Time Adaptive Processing (Contd…)
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Range gates
zz
z
Puls
es
T
T
T
Elements
T = pulse repetition intervalz = A/D sampling period
Radar data cube
Rangegate of interest
Estimate interferenceusing this data
(training region)
Range gatesz z z z
Fig. 9: Radar Data and Interference Estimation
Space-Time Adaptive Processing (Contd…)
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Space Time Steering matrix:
A Kronecker product (an operation on two matrices of arbitrary size resulting in a block matrix ) of temporal steering matrix and spatial steering matrix
Temporal steering matrix is the DFT of frequency resolution
Spatial steering matrix represents the extent of correlation between each active pixel to its neighboring
1 … N
TR
[ 1; ej2πω; ej2πω·2; …ej2πω·(N-1)]
Space-Time Adaptive Processing (Contd…)
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Covariance Matrix
It represents the degree of correlation across both antenna array inputs
and over the pulses comprising the CPI (coherent processing interval).
It creates an optimal filter and remove undesired signals. The undesired
signals include noise, clutter and jammers.
Basically, the covariance matrix will be used to compute the optimal
filter, it also contain the target data.
R=+
Space-Time Adaptive Processing (Contd…)
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N Blocks
M B
locks𝑹=𝐸 {𝒀 𝒀𝑯 }=[ 𝑄11 𝑄12 … 𝑄1 𝑀
𝑄21 𝑄22 . 𝑄2𝑀
⋯ … ⋱ ⋮𝑄𝑁 1 𝑄𝑁 2 … 𝑄𝑁𝑀
] An matrix . An block matrix with
block size
Space-Time Covariance Matrices for Noise
Space-Time Adaptive Processing (Contd…)
𝑅𝑛=𝜎2 𝑰𝑁=𝜎2[ 𝑰 𝑁 0 … 00 𝑰 𝑁 . 0⋮ . ⋱ ⋮0 0 … 𝑰𝑁
]
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Jammer signals in different pulses are independent.
Jammer signals in different pulses are independent.
Jammer signals in different matched filter outputs are independent.
Jammer signals in different matched filter outputs are independent.
Block diagonalBlock diagonal
Numbers of jammersNumber of powersJammer spatial steering vector
Space-Time Adaptive Processing (Contd…)
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Separable: N+L tapsNon separable: NL taps
Joint processDoppler frequencies and angles
Joint processDoppler frequencies and angles
Independent process Doppler frequencies and angles
Independent process Doppler frequencies and angles
Angle processing
Doppler processingSpace-time
processing
L: # of radar pulses
L
Space-Time Adaptive Processing (Contd…)
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S. M. M. Hossain Mahmud090924
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EstimateInterferenceEstimate
Interference
ApplySTAP
Weights
ApplySTAP
Weights
Pre
proc
esso
rP
repr
oces
sorData cube
ComputeSTAP
Weights
ComputeSteering Vectors
ComputeSteering Vectors
Det
ectio
nsReduced dimensionspace
Beam Angle &Target Doppler
Selection
Beam Angle &Target Doppler
Selection
W=
Fig. 10: Generic STAP Architecture
Space-Time Adaptive Processing (Contd…)
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• Preprocessing may involve beamforming and Doppler filtering• Rejection of some interference nonadaptively• Adapt on small number of preprocessor outputs
Space-Time Adaptive Processing (Contd…)
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x y
OutputInput
A matched filter Colored noise Joint space (array beamforming) and time (Doppler)
)(
Matched Filter
Space-Time Adaptive Processing (Contd…)
Z=WY
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PulseE
lem
ent
Doppler bin
Ele
men
tDopplerfiltering
Pulse
Bea
m
Doppler bin
Bea
m
Dopplerfiltering
Spatialfiltering
Spatialfiltering
Element-SpacePre-Doppler
Element-SpacePost-Doppler
Beam-SpacePre-Doppler
Beam-SpacePost-Doppler
STAP algorithms classified by domain in which adaptivity occurs There are performance differences between algorithms
Taxonomy of STAP Architectures
Space-Time Adaptive Processing (Contd…)
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AdaptiveBeamforming
clutterNulling
AdaptiveBeamforming
clutterNulling
Beamspace
STAP
jammerNulling
Beamspace
STAP
jammerNulling
clutterTrainingclutter
TrainingjammingTrainingjammingTraining
N ElementsM Pulses
B BeamsM Pulses
Step 1 Step 2Detection
andMetrics
Detectionand
Metrics
• Requires training data free of main lobe clutter for Step 1– Beyond the horizon range gates in low PRF– Doppler filter away from mainlobe clutter
• Beamspace pre- or post-Doppler STAP clutter nulling
Space-Time Adaptive Processing (Contd…)
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Besides providing adequate power aperture product, the radar system design
must incorporate:
- A mechanism to suppress clutter returns
- Jammer suppression capability
Collectively refers to clutter and jamming signals as interference
Detection performance depends on the signal-to-interference-plus-noise ratio
(SINR) and specified false alarm rate
SINR=SNR
Detection Phenomenon
Space-Time Adaptive Processing (Contd…)
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Two-dimensional filtering required to cancel interference
Target Jamming
GroundClutter
v
–1
0
1
sin (Azimuth)
0
Doppler(H
z)0
10203040
SNR
(dB
)
Space-Time Adaptive Processing (Contd…)
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The total received signal contains returns from the target, clutter and jammer combined.
The signal is a data cube with three dimensions (range bins x number of elements x number of pulses).
Space-Time Adaptive Processing (Contd…)
Parameters assumed CNR: 30dB SNR: 10dB, JSR: 0dB
Space-time beampattern is the antenna gain as a function of angle of arrival and Doppler frequency.
04/17/202338
sine angle
norm
aliz
ed d
oppl
erTotal Return spectrum before STAP Detection of target, clutter, noise & jammer
-1 -0.5 0 0.5 1-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
42
44
46
48
50
52
54
56
58
60
Fig. 11: Total return spectrum before STAP detection.
Total Return Spectrum at Receiver
Target
Clutter+Noise
Jammer
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-1-0.5
00.5
1
-1
-0.5
0
0.5
140
45
50
55
60
65
sine angle
Total Return spectrum before STAP Detection of target, clutter, noise & jammer
normalized doppler
Total Return Spectrum at Receiver (Contd…)
Fig. 12: 3-D plot of total return spectrum at the receiver end with target, clutter, noise and jammer.
Target Clutter+Noise
Jammer
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sine angle
norm
alized d
opple
rSTAP Detection of target & jammer; clutter removed
-1 -0.5 0 0.5 1-1
-0.8
-0.6
-0.4
-0.2
0
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1
-60
-50
-40
-30
-20
-10
0
Clutter Removed by STAP
Fig. 13: STAP detection; Removal of clutter and noise while target & jammer remains.
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-1-0.5
00.5
1
-1
-0.5
0
0.5
1-60
-50
-40
-30
-20
-10
0
sine angle
STAP Detection of target & jammer; clutter removed
normalized doppler
Fig. 14: 3-D plot of STAP detection; Removal of clutter and noise while target & jammer remains.
Clutter removed by STAP (Contd…)
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sine angle
norm
alized d
opple
rSTAP Detection of target; jammer & clutter removed
-1 -0.5 0 0.5 1-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
-60
-50
-40
-30
-20
-10
0
Jammer and clutter removed by STAP
Fig. 15: Output of STAP processor; Removal of jammer and clutter while only target remains.
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-1-0.5
00.5
1
-1
-0.5
0
0.5
1-60
-50
-40
-30
-20
-10
0
sine angle
SNR after STAP Detection of target, clutter, noise & jammer
normalized doppler
Fig.16: 3-D plot of output of STAP processor; Removal of jammer and clutter while only target remains.
Jammer and clutter remove by STAP (Contd…)
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References
1. M. Skolnik, “Introduction To Radar Systems”, 3rd ed. McGraw-Hill, 2001.2. ŞAFAK BİLGİ AKDEMİR, “AN OVERVIEW OF DETECTION IN MIMO RADAR”
published in SEPTEMBER 2010.3. J. Li and P. Stoica, “MIMO radar with colocated antennas,” IEEE Signal Processing Magaz.,
vol. 24, no. 5, pp. 106–114, Sept. 2007.4. Chaoran Du, “Performance Evaluation and Waveform Design for MIMO Radar”, The
University of Edinburgh, March 2010.5. Mark A. Richards, “Fundamentals of Radar Signal Processing”, Georgia Institute of Technology,
McGraw-Hill-2005.6. P. Tait, “Introduction to Radar Target Recognition”, Radar, Sonar and Navigation Series 18,
edited in 2009, The Institution of Engineering and Technology, London. 7. Z. C. Yang*, X. Li, and H. Q. Wang, “SPACE-TIME ADAPTIVE PROCESSING BASED ON
WEIGHTED REGULARIZED SPARSE RECOVERY”, Electronics Science and Engineering School, National University of Defense Technology, Changsha 410073, China.
8. Janice Onanian McMahon, “Space-Time Adaptive Processing on the Mesh Synchronous Processor”, THE LINCOLN LABORATORY JOURNAL, VOLUME 9, NUMBER 2, 1996.
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References9. J. R. Guerci, “Space-Time Adaptive Processing for Radar”, 2003 ARTECH HOUSE, INC.10. Dr. Marshall Greenspan, “MIMO Radar Signal Processing of Space Time Coded Waveforms”,
IEEE Signal Processing Society Baltimore Chapter MeetingMay 21, 2008. 11. Janice Onanian McMahon, “Space-Time Adaptive Processing on the Mesh Synchronous
Processor”, THE LINCOLN LABORATORY JOURNAL, VOLUME 9, NUMBER 2, 1996.12. Brian R. Hunt, Ronald L. Lipsman, Jonathan M. Rosenberg “A Guide to MATLAB for Beginners
and Experienced Users”, Second Edition, cambridge university press-2006.13. Mahafza, B. R., “Radar Signal Analysis and Signal Processing Using MATLAB”, Chapman and
Hall/CRC, Boca Raton, FL, 2008.14. Bassem R. Mahafza, Ph.D., Atef Z. Elsherbeni, “MATLAB Simulations for Radar Systems
Design”, 2004 by Chapman & Hall/CRC CRC Press LLC15. Bassem R. Mahafza, Ph.D., “Radar Systems Analysis and Design Using MATLAB”, 2008 by
Chapman & Hall/CRC.
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THANKS TO ALL