- The BP algorithm is firstly used to accurately focus InSAR image pairs, then the subapertures (also called sublooks in this paper) for MSQ differential interferometry is evenly split in the azimuth wavenumber domain. In contrast to the process of the subaperture differential interferometric phase integration in , the proposed BP-MSQ algorithm estimates polynomial parameters of RME by using the subaperture differential phase, while it analyzes the representation of RME in the azimuth time domain. In this manner, both high- and low-frequency error components of RME can be obtained precisely.
- The second contribution of this work is that accurate analytic expressions of RME in BP InSAR image pairs from stripmap and spotlight SAR modes are derived separately. In addition, the characteristics of subaperture differential interferometry phase diagrams with linear and high-order types RME are analyzed, which makes the RME estimation more flexible and adjustable to multiple imaging modes.
- In the framework of the improved BP-MSQ algorithm, linear RME estimation flowcharts for stripmap SAR and spotlight SAR are given differently. Meanwhile, a piecewise RME model is developed for the refined high-order RME compensation under spotlight mode. Avoiding the differential phase integration in RME estimation, the developed BP-MSQ outperforms the original MSQ in the case of strong noises.
2. Airborne InSAR Focusing with Backprojection Imaging
3. RME Estimation Principle with the Polynomial Fitting MSQ
3.1. RME Estimation Principle with the BP-MSQ Algorithm
3.2. Investigation of RME Fitting Scheme in Stripmap and Spotlight SAR Modes
- Assume InSAR works in spotlight mode and RME has a linear form, we have
- Assume InSAR works in spotlight mode and RME has a high-order polynomial form, we have
- Assume InSAR works in stripmap mode and RME has a linear form, we have
- Assume InSAR works in stripmap mode and RME has a high-order polynomial form, we have
3.3. Detailed Algorithm Procedure
- Step (1)
- BP imaging using track information. Firstly, the track information can be extracted from IMU/GNSS. Then, the corresponding single-look complex image of each antenna can be obtained by BP algorithm from the echo data of the master antenna and the slave antenna.
- Step (2)
- Subapertures segmenting in azimuth Doppler domain. The Doppler spectrum of the single-look complex image of the master antenna and the slave antenna is uniformly divided into M frequency bands, and then multi-look images of the two antennas, i.e., a plurality of subaperture images are obtained.
- Step (3)
- Subaperture images differential interferometry. Firstly, the image of the subaperture with the same radar sight looking angle of the master antenna and the slave antenna is multiplied to obtain a subaperture interferogram. Then, the adjacent subaperture interferograms are multiplied by conjugate to obtain a subaperture differential interferogram.
- Step (4)
- RME estimation. The RME differential phase can be extracted from the subaperture differential interferogram, and then the corresponding strategy is adopted according to the SAR working mode and the RME type to estimate the value of the RME in the time domain over the entire imaging time.
- Step (5)
- BP imaging with RME compensation. BP algorithm was used to refocus the image and compensate RME at the same time to obtain the interferogram corrected by RME.
4.1. Linear RME Simulation Experiment with Stripmap SAR
4.2. Simulation with High-Order RME
4.3. Actual InSAR System Data Processing
Conflicts of Interest
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|Pulse Repetition Frequency||PRF/(Hz)||2000|
|Pulse Repetition Frequency||PRF/(Hz)||5000|
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