DISPLACED PHASE CENTER ANTENNA SAR IMAGING
BASED ON COMPRESSED SENSING
Yueguan Lin 1,2,3, Bingchen Zhang 1,2, Wen Hong 1,2 and Yirong Wu 1,2
1 National Key Laboratory of Science and Technology on Microwave Imaging, P. R. China
2 Institute of Electronics, Chinese Academy of Sciences (IECAS), Beijing, P. R. China
3 Graduate University of Chinese Academy of Sciences (GUCAS), Beijing, P. R. China
National Key Laboratory of
Microwave Imaging Technology
Institute of Electronics, Chinese
Academy of Sciences
• Outlines
• Introduction
• DPCA SAR imaging based on Compressed Sensing
• Ground-based DPCA SAR experiment
• Conclusion and discussion
• Acknowledgement
• Introduction
• High azimuth resolution and wide unambiguous swath coverage
are contradictive in SAR system design.
• DPCA SAR has the potential to achieve HRWS imaging. While
there is a rigid restriction posed on its selection of PRF: SAR
platform moves just one half of its total antenna length between
subsequent radar pulses .
• When this condition is not satisfied, there will be nonuniform
sampling in azimuth and rising azimuth ambiguities will appear
under traditional imaging algorithms based on matched filter
• Introduction
• Krieger proposed A Doppler spectrum reconstruction algorithm *.
• This method can recover the unambiguous signal and suppress
ambiguous energy.
• It is computation costly as inversions of matrix are involved and
the reconstruction of spectrum should be carried out for every
azimuth signal.
* Krieger, G., Gebert, N., and Moreira, A.: ‘Unambiguous SAR signal reconstruction from
nonuniform displaced phase center sampling’. IEEE Geoscience and Remote Sensing
Letters, 2004, 1(4): 260-264.
• DPCA SAR imaging based on Compressed Sensing
• Compressed Sensing
X is sparse representable if there exists a sparsity basis that provides a K
sparse representation of it.
Y = ΦX
When Φ satisfies Restricted Isometry Property. The number of
measurements needed to reconstruct the signal is not restrained by the Nyquist
sampling rate, but by the complexity of the signal. We only need M
measurements, where
(
)
M = O K log (N / K )
where N is the number of measurements needed by the Nyquist Theorem
• DPCA SAR imaging based on Compressed Sensing
According to systems the DPCA SAR model can be constructed precisely
y  Φx  n
where，
y is the observations
x is observed scene
Φ is observation matrix
n is observation noise.
Φ  k , l   Φ p  P  k P  1, l 
0
 hp (1)
 h ( P  1)
hp ( P )
 p


hp (Q  1)
Φ p   hp (Q)

0
0



0
0

0
hp (1)
hp (Q  P)
hp (Q)
0
0
0
0
hp (1)
hp ( P  1)
0
0 
0 



hp (1) 


hp (Q) 
• DPCA SAR imaging based on Compressed Sensing
• The backscattering field of target is usually contributed by a few
strong scattering centers, so CS is suitable in SAR imaging.
• As the observation is constructed precisely according to SAR
system parameters, the ambiguity causes by nonuniform
effective azimuth phase centers doesn’t exist.
• The observed scene can be reconstructed through solving an
optimization problem
min  x 1  ,
subject to
y  Φx
2

• Ground-based DPCA SAR experiment
Ground-based DPCA SAR system with one aperture transmitting
stepped frequency and three apertures receiving echoes.
System parameters
Parameters
Values
Carrier frequency
17 GHz
Based band width
1 GHz
Stepped frequencies
2.5 MHz
Span in azimuth
[-1, 1] m
Azimuth sampling interval
0.024 m
Length of subaperture
0.032 m
DPCA SAR system
4.5
4
• Ground-based DPCA SAR experiment
3.5
3
2.5
2
1.5
1
0.5
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
Azimuth effective phase centers (m)
Antennas
•
Azimuth effective phase centers.
Effective azimuth phase centers of this DPCA SAR system are nonuniformly
distributed.
• Ground-based DPCA SAR experiment
0
Magnitude (dB)
-10
-20
-30
-40
-50
-1
Observed trihedral corner reflector.
-0.5
0
Azimuth (m)
0.5
1
RD imaging without preprocessing
• Result using traditional Range-Doppler algorithm without preprocessing has
-17dB ambiguities.
0
0
-10
-10
Magnitude (dB)
Magnitude (dB)
• Ground-based DPCA SAR experiment
-20
-30
-40
-50
-1
-20
-30
-40
-0.5
0
Azimuth (m)
0.5
1
RD imaging with spectrum reconstruction
-50
-1
-0.5
0
Azimuth (m)
0.5
1
Proposed CS imaging
• Result using RD algorithm after spectrum reconstruction has -25dB
ambiguities; result using proposed imaging algorithm with ambiguities being
suppressed under -30dB.
• Conclusion and discussion
• DPCA SAR imaging algorithm based on CS can suppress the
ambiguities caused by nonuniform sampling in azimuth and
retrieve the target scene with high quality.
• The experimental results with ground-based DPCA SAR system
validate its advantage.
 We will evaluate this method’s performance with real space
borne and airborne raw data in next step.
 The effect of observation noise will be researched.
• Acknowledgement
• This work was supported by the State Key Development Program for Basic
Research of China (Grant No. 2010CB731905).
Thank you for your attention!
Email: linyueguan@gmail.com