Bistatic SAR imaging using Non-Linear Chirp Scaling

1
Bistatic SAR imaging using Non-Linear Chirp
Scaling

• By Y. L. Neo
• Supervisor Prof. Ian Cumming
• Industrial Collaborator Dr. Frank Wong

2
Agenda

• Bistatic SAR
• Bistatic Image Reconstruction Issues
• Existing Algorithms
• Non-Linear Chirp Scaling Algorithm
• Extension to NLCS
• Simulation Results
• Conclusions

3
Bistatic SAR

• In a Bistatic configuration, the Transmitter and
  Receiver are spatially separated and can move
  along different paths.
• Bistatic SAR is important as it provides many
  advantages
• Cost savings by sharing active components
• Improved observation geometries
• Passive surveillance and improved survivability

4
Current Research

• Several European radar research institutes - DLR,
  ONERA, QinetiQ and FGAN have embarked on bistatic
  airborne experiments. Majority of the experiments
  uses two existing monostatic sensors to
  synthesize bistatic images.
• Satellite missions are also proposed TanDEM X
  proposal for TerraSAR-X single pass
  interferometry for accurate DEM DTED-3.
  Interferometric Cartwheel. Excellent paper
  Multistatic SAR Satellite Formations Gerhard
  Krieger.
• Other research involves the use of Bistatic
  Parasitic SAR. Where a ground based receiver
  pairs up with a non-cooperative satellite
  transmitter.

5
Agenda

• Bistatic SAR
• Bistatic Image Reconstruction Issues
• Existing Algorithms
• Non-Linear Chirp Scaling Algorithm
• Extension to NLCS
• Simulation Results
• Conclusions

6
Image Reconstruction Issues

• Bistatic SAR data, unlike monostatic SAR data, is
  inherently azimuth-variant.
• Difficult to derive the spectrum of bistatic
  signal due to the double square roots term.
• Traditional monostatic SAR algorithms based on
  frequency domain methods are not able to focus
  bistatic SAR imagery, since targets having the
  same range of closest approach do not necessarily
  collapse into the same trajectory in the azimuth
  frequency domain.

7
Image Reconstruction Issues

• Bistatic SAR has many configurations
• parallel tracks,
• non-parallel tracks,
• stationary receiver etc.
• These different configurations make the
  derivation of the spectrum difficult
• Analytical solution is not available, however
  approximate solution exist Loffelds bistatic
  equation
• Restricted the scope of research to focusing
  parallel and slightly non-parallel cases

8
Imaging geometry of bistatic SAR
9
Agenda

• Bistatic SAR
• Bistatic Image Reconstruction Issues
• Existing Algorithms
• Non-Linear Chirp Scaling Algorithm
• Extension to NLCS
• Simulation Results
• Conclusions

10
Existing Algorithms

• Time Domain Correlation
• Back Projection Algorithm
• ?K Algorithm
• Loffelds Bistatic Equations
• RDA
• Roccas Smile

11
Agenda

• Bistatic SAR
• Bistatic Image Reconstruction Issues
• Existing Algorithms
• Non-Linear Chirp Scaling Algorithm
• Extension to NLCS
• Simulation Results
• Conclusions

12
Non-Linear Chirp Scaling

• Existing Non-Linear Chirp Scaling
• Based on paper by F. H. Wong, and T. S. Yeo, New
  Applications of Nonlinear Chirp Scaling in SAR
  Data Processing," in IEEE Trans. Geosci. Remote
  Sensing, May 2001.
• Assumes negligible QRCM (for SAR with short
  wavelength)
• shown to work on Monostatic case and the Bistatic
  case where receiver is stationary
• Limitations of this method is unknown
• May be extended to other geometries parallel
  tracks, non-parallel tracks

13
Advantages

• NLCS can be used to focused bistatic data by
  finding the perturbation function for each
  bistatic configuration
• NLCS requires no interpolation
• NLCS can be used in non-parallel cases
• The Linear RCMC step in NLCS eliminates most of
  the RCM and the range/azimuth phase coupling.
• Computational load is comparable to traditional
  monostatic algorithms.

14
Main Processing Steps of NLCS Algorithm
Range Compression
Linear RCMC
Baseband Signal
Non-Linear Chirp Scaling
Azimuth Compression
Focused Image
15
A
C

• The trajectories of three point targets in a
  squinted monostatic case is shown
• Point A and Point B has the same Closest range of
  approach and the same chirp rate.

B
Monostatic Case
Range time
Az time
16
Chirp Rate Equalization (monostatic)
17

• After LRCMC, trajectories at the same range gate
  do not have the same chirp rates, an equalizing
  step is necessary

• Chirp rates are equalized by phase multiply with
  a perturbation function hpert(?) along azimuth
  time .
• Monostatic Case
• Bistatic Case with Stationary Receiver

• Once the Azimuth Chirp Rate is equalized, the
  image can be focused by an azimuth matched filter.

18
Agenda

• Bistatic SAR
• Bistatic Image Reconstruction Issues
• Existing Algorithms
• Non-Linear Chirp Scaling Algorithm
• Extension to NLCS
• Simulation Results
• Conclusions

19
Research work done

• Added residual QRCMC
• Extended the processing to parallel tracks and
  non-parallel tracks
• Azimuth Frequency Matched filter
• Secondary Range Compression
• Current work
• Invariance Region Analysis
• Registration to ground plane

20

• We have added a QRCMC to improve the impulse
  response
• Residual QRCM Correction can be performed in the
  range Doppler domain after the Chirp Rate has
  been equalized

21
Residual QRCMC

• Uncorrected QRCM will lead to Broadening in Range
  and Azimuth
• The Cubic RCM is very small compared to Quadratic
  RCM , can be ignored in most cases

Without residual QRCMC
With residual QRCMC Resolution and PSLR Improves
22
Perturbation Function

• We have extended the NLCS algorithm to
  Non-Parallel Tracks with the Same Velocity
• Using the method similar to the monostatic case
  and correction of the phase term up to the cubic
  term, the perturbation function is found to be a
  cubic function of azimuth time and the
  coefficient is found to be

• Limited to short and medium wavelength system

23
Azimuth Frequency Matched Filter

• Initially used time domain matched filter
  correlation (inefficient)
• Frequency matched filter is derived using the
  reversion of power series

• Linear phase term has to be removed before
  applying the reversion of power series

24
Azimuth Matched Filter

• Freq matched filter can be obtained by doing a
  FT of the equalized Az signal

• A relation between azimuth time and azimuth
  frequency can be obtained by using the Principle
  of Stationary Phase

25
Azimuth Matched Filter

• The Frequency matched filter is the conjugate
  of FT signal

• Expansion up to third order phase is necessary
• - e.g. C band 55deg squint 2m resolution

26
Limitations

• Restriction on patch size, residual RCM
  difference lt 1 range resolution cell restrict
  the range extent
• The Non-linear chirp scaling uses some
  approximations leading to restriction in
  azimuth extent
• Range Doppler Coupling for large QRCM Secondary
  Range Compression is necessary
• Algorithm suitable for shorter wavelengths (S, C
  , X, K band ) and cases where QRCM is not too
  significant

27
Invariance Region Analysis
The range invariance region to keep range and
azimuth resolution degradation less than 10 for
a 10 km by 10km patch.

• Bistatic case, imaging at broadside with Tx
  slant range of 40km, lateral separation of 20km
  and a bistatic angle of 9 deg.

Wavelength (Frequency) Wavelength (Frequency) Wavelength (Frequency) Wavelength (Frequency)
Resolution 0.01m (30GHz) 0.03m (10GHz) 0.06m (5GHz) 0.2m (1.5GHz)
10 m Full size Full size Full size Full size
3 m Full size Full size Full size 4.0 km
1 m Full size 2.7km 1.3km 0.4km

• Bistatic case, Tx imaging at 30 deg squint, Tx
  slant range of 40km, lateral separation of 20km
  and squint of 30 deg.

Wavelength (Frequency) Wavelength (Frequency) Wavelength (Frequency) Wavelength (Frequency)
Resolution 0.01m (30GHz) 0.03m (10GHz) 0.06m (5GHz) 0.2m (1.5GHz)
10 m Full size Full size Full size Full size
3 m Full size Full size Full size 3.4 km
1 m Full size 4.5km 2.1km 0.6km
28
Secondary Range Compression

• Range Doppler Coupling occurs for large QRCM i.e.
  longer wavelength and higher resolution cases
• Secondary Range Compression must be performed
  before Quadratic Range Cell Migration for these
  cases
• Additional processing required will reduce the
  efficiency of the algorithm
• Still investigating this part. Preliminary
  results shows that quadratic range migration of 6
  range resolution cells does not produce
  significant range Doppler coupling

Diagram referenced from the BOOK Digital
Processing of Synthetic Aperture Radar Data
29
Illustration of SRC
30
Agenda

• Bistatic SAR
• Bistatic Image Reconstruction Issues
• Existing Algorithms
• Non-Linear Chirp Scaling Algorithm
• Extension to NLCS
• Simulation Results
• Conclusions

31
Non-parallel flight, dissimilar velocity
Transmitter squinted at 40 degrees and both
platforms moving in a non-parallel configuration
with lateral separation of 3km and with Vt
200m/s and Vr 220m/s1 parallel to Transmitter .
It is a C-band system with wavelength 0.06m,
3dB beamwidth 1.9degree, PRF 185Hz. Range
bandwidth of 75MHz and Azimuth bandwidth about
160Hz. The imaged area has 25 point targets
32
Before Registration to Ground Plane
33
After Registration to Ground Plane
34
Impulse response
35
Agenda

• Bistatic SAR
• Bistatic Image Reconstruction Issues
• Existing Algorithms
• Non-Linear Chirp Scaling Algorithm
• Extension to NLCS
• Simulation Results
• Conclusions

36
Conclusions

• Illustrated the use of NLCS to focus bistatic SAR
• Show the extensions to the NLCS to improve its
  processing capabilities
• Simulated a non-parallel track example and the
  results

37
Future work

• Invariance Region Analysis.
• Secondary Range Compression.
• Registration.
• Comparison with existing algorithms.
• How the existing algorithms relate to one
  another.

38
Questions?