Airborne Single-Pass Multi-Baseline InSAR Layover Separation Method Based on Multi-Look Compressive Sensing

Due to the small number of baselines (2–3), the traditional L1 norm compressive sensing method for layover solution in InSAR has poor separation ability and height estimation stability and a long operation time. This paper, based on the idea of multi-look, adopts a multi-look compressive sensing method and a multi-look compressive sensing method based on separable approximate sparse reconstruction. The layover separation method based on multi-look compressive sensing adopts the surrounding pixels around the current point as independent observations together with this point to increase the observation vector in compressive sensing, and uses the singular value decomposition method to obtain the noise value, which is used to improve the dimensions of measured data in compressive sensing, reduces the noise level, and improves the stability of noise estimation. Meanwhile, the results of the multi-look L1 norm solution method are closer to those of the L0 norm solution, and the sparse reconstruction ability of compressive sensing is improved. Thus, the separation ability of the scatterers in the layover areas and the stability of height estimation are stronger. In addition, the multi-look compressive sensing method based on separable approximate sparse reconstruction constructs differential operation and soft functions, transforms the L1–L2 norm optimization into an iterative soft threshold shrinkage processing mode, and improves the processing speed by means of the threshold iteration method, which can effectively reduce the operation time while maintaining the resolution ability of scatterers in layover areas and the height direction estimation accuracy and provides the possibility for large-scale data processing. These two methods are effectively verified by means of simulation and measured data. The simulation experiments of the two methods are based on the airborne MEMPHIS system with four antennas, and the height values of the layover scatterers solved by the two methods are more reliable, stable, and closer to the real value than those solved by the traditional compressive sensing method. The operation time of the separable approximate sparse reconstruction method is comparable to the processing time of the traditional compressive sensing method and nearly one-quarter that of the multi-look compressive sensing method. The real data experiments of the two methods are based on the airborne Millimeter-wave InSAR system with three antennas. The two methods both have certain height resolutions in the height direction estimation of layover areas and fine elevation continuity, while traditional compressive sensing method cannot satisfy the condition of sparsity and has poor scatterer separation and elevation continuity. Nevertheless, the multi-look compressive sensing method is a little more stable than the separable approximate sparse reconstruction method, and the operation time of the separable approximate sparse reconstruction method is comparable to the traditional compressive sensing method and nearly one-fifth that of the multi-look compressive sensing method.