Optimum signal processing for multichannel SAR: With application to high-resolution wide-swath imaging

A new method for processing multichannel synthetic aperture radar (SAR) data to achieve desirable image characteristics is presented. The method is optimal because it is derived by minimizing a mean-square-error cost function and generalizes current methods for high-resolution wide-swath SAR signal processing. The proposed method is easily implementable, can support a wide range in the pulse repetition frequency (PRF), including cases with highly nonuniform spatial sampling, and is robust against PRFs where current projection techniques fail, cases where the PRF is ideally suited to clutter suppression. Point spread functions for the proposed algorithms are presented, and the theory and simulations are further corroborated by results using multichannel SAR data measured by RADARSAT-2. We demonstrate that, if RADARSAT-2 were able to illuminate a 250-km swath (300 km ground range), then, conceptually, the new method would be able to process the highly nonuniformly sampled data to provide an extremely wide mode at approximately 5-m azimuth resolution

Space-based moving target positioning using radar with a switched aperture antenna

Ground moving target indication (GMTI) by space based radar can effectively only be performed with a multi- aperture/multi-channel system or a satellite cluster [1]. To keep weight, power consumption, data rate and costs low, the technique of switching subapertures from pulse to pulse has been proposed. While the detection performance using STAP (space-time adaptive processing) has been analysed in several publications, the estimation performance and the mechanisms leading to good or bad aperture switching strategies, have not yet been treated sufficiently. In fact, aperture partitions well suited for detection must not necessarily be good for estimation. This paper is thought as a contribution to fill the knowledge gaps concerning repositioning algorithms and performance analysis