Iterative-SGLRT for Multiple-Scatterer Detection in SAR Tomography

This letter introduces a multiple-scatterer detection method in synthetic aperture radar tomography (TomoSAR), named iterative sequential generalized likelihood ratio test (iterative-SGLRT). In this technique, the number of scatterers is sequentially decided by the generalized likelihood ratio test (GLRT) pixel by pixel, after iteratively estimating the parameters. It is a good tradeoff of the aforeproposed methods of sup-GLRT and fast-sup-GLRT on accuracy and efficiency. Simulated comparisons showed that iterative-SGLRT outperformed fast-sup-GLRT on the performances of detection probability and accuracy without substantial computation time increase, and compared with sup-GLRT, its performance loss could be negligible with computational burden greatly reduced. In addition, both iterative-SGLRT and sup-GLRT have been applied to the TerraSAR-X data set over Shenzhen city. The 3-D reconstruction of the test site and the separation of the overlaid scatterers have been achieved. In addition, verification using light detection and radar (LiDAR) indicated a root-mean-square error (RMSE) of $ {0.1\rho _{s}}$ for both methods of the height estimated. Accordingly, iterative-SGLRT is very suitable for large urban area processing for its super-resolution, high efficiency, and robustness.