Guangxue Wang

Fast Factorized Backprojection Algorithm for One-Stationary Bistatic Spotlight Circular SAR Image Formation

In this paper, a fast factorized backprojection (FFBP) algorithm is proposed for the one-stationary bistatic spotlight circular synthetic aperture radar (OS-BSCSAR) data processing. This method represents the subimages on polar grids in the slant-range plane instead of the ground plane, which can be accurately referenced to the tracks of both transmitter and receiver. It can not only accurately accommodate the complicated circular track including the motion error, scene topographic information, large spatial variances and significant range-azimuth coupling of the echo data, but also improve the imaging efficiency compared with the backprojection (BP) algorithm. First, OS-BSCSAR imaging geometry is provided, and then the bistatic BP algorithm for the OS-BSCSAR imaging is derived to provide a basis for the proposed FFBP algorithm. Second, based on the subaperture imaging model, the polar grids for calculating the subimages are defined, and the sampling requirements for the polar grids are derived from the viewpoint of the bandwidth, which can offer the near-optimum tradeoff between the imaging quality and the imaging efficiency. Finally, implementation and computational burden of the proposed FFBP algorithm is discussed, and then the speed-up factor of the proposed FFBP algorithm with respect to the bistatic BP algorithm is derived. Experiment results are given to prove the correctness of the theory analysis and validity of the proposed FFBP algorithm.

Phase Unwrapping for Large-Scale P-Band UWB SAR Interferometry

Phase unwrapping (PU) for large-scale images is a new challenging problem in reconstructing a digital elevation model from synthetic aperture radar interferometry (InSAR) data. In this letter, we proposed a region-partition-based PU method that could improve the efficiency and decrease the processing memory of the large-scale PU problem for P-band ultrawideband (UWB) InSAR. The interferometric phase is flattened by the reference phase, which is generated from the shift estimation in the registration step. We refer to the residual phase as the misregistration phase (MRP), which corresponds to the error of the shift estimation. The MRP is unambiguous in most of the area with high coherence because of the large fractional bandwidth; thus, the regions that assuredly have the unambiguous MRP are partitioned out from the MRP image and referred to as the high-quality area. Meanwhile, the remaining low-quality areas are separated by the high-quality areas and are considered irregular tiles. After unwrapping the tiles by a minimum discontinuity PU algorithm either in parallel or in series, the full-size unwrapped result is obtained. The test performed on real P-band UWB InSAR data confirms the effectiveness and efficiency of our method.

Relative radiometric normalization of SAR images based on bi-direction linear regression model

The Relative radiometric normalization (RRN) of multi-temporal synthetic aperture radar (SAR) images is very important for change detection. Many RRN techniques have been developed up to now. Among them, the No-Change set regression normalization algorithm (NC algorithm) is proved to have the best performance in optical image processing field. However, as our paper shows, the presence of speckle noise in SAR image will make the estimations of RRN parameters biased in NC algorithm. In order to deal with this problem, we propose a RRN method suitable for SAR images. In the approach, the biases of RRN parameters estimations are removed by a bi-direction linear regression model. And a recursive weighted least square method is included to improve robustness. The effectiveness of the proposed approach is confirmed with experimental results compared to NC algorithm.