Assessment of Image Quality of Waveform-Encoded Synthetic Aperture Radar Using Real Satellite Data

Abstract

Synthetic aperture radar (SAR) remote sensing is very attractive for the systematic observation of dynamic processes on the Earth’s surface since it allows high resolution imaging independently of weather conditions and sunlight illumination. Waveform-encoded SAR is a novel SAR concept based on pulse-to-pulse variation of the transmitted waveform that allows focusing the nadir echo and the range ambiguities and suppressing them through a multi-focus post-processing. However, the assessment of the ambiguity suppression performance for such a system is not trivial, as the processing involves a (non-linear) thresholding and blanking approach. This work proposes a novel methodology, which exploits real TerraSAR-X data to accurately simulate the effect of the range ambiguity on the useful signal and allows for a quantitative assessment of the image quality of a waveform-encoded SAR. The analysis considers different waveform variation schemes (e.g., up- and down-chirps, cyclicallyshifted chirps) and a contrast-minimization technique for threshold selection, whose performance is compared to the best achievable one (i.e., optimum threshold). The results of this work further highlight the potentialities of the waveform-encoded SAR concept and also allow accounting for its ambiguity suppression capability in the design of a SAR system.