ELEVATION PROFILE ESTIMATION FOR SINGLE PASS BI-STATIC SAR TOMOGRAPHY USING COMPRESSED SENSING

Single-pass bistatic Synthetic Aperture Radar (SAR) Tomography (TomoSAR), in the case of a space-borne transmitter and a ground-based multi-channel receiver, can be used as an alternative to regular TomoSAR methods, which require multiple acquisitions (multi-pass) to derive elevation estimates from an observed scene. Generally, such systems utilize spectral-based reconstruction methods, which necessitate a large number of receiving elements or a limited number of elements arranged in a specific configuration to achieve the necessary resolution. In this study, we propose a novel approach for estimating the elevation profile using a reduced number of channels without a specific array configuration. We treat it as an underdetermined problem that can be solved using Compressed Sensing (CS) algorithms. The performance of the proposed approach is compared against the spectral-based approach using Monte Carlo simulations and demonstrated on real data measurements.