Strategy for SAR Imaging Quality Improvement With Low-Precision Sampled Data

It has been proven that the imaging quality of 1-bit quantized synthetic aperture radar (SAR) data can be improved by using an imaging scheme of a single-frequency threshold (SFT). In this article, such a quantization model is specialized to a fixed threshold application by setting the frequency of the threshold to zero. Using multiple fixed thresholds, the conventional quantization schemes are also assimilated into this model. In this way, the performance degradation caused by low-precision quantization is analyzed in terms of harmonics, and the SFT quantization (SFTQ) strategy is addressed to handle the issue of performance degradation. The proposed quantization scheme provides significant imaging quality improvements, especially when the quantization level is low, and its advantage in computational complexity is also analyzed. Simulations on different SAR scenes show that the SFTQ, compared with the conventional quantizers, is able to guarantee 97% information in the SAR imagery while consuming less than 1/6 hardware for pulse compression. Therefore, the proposed low-precision SFTQ is a promising approach to SAR system miniaturization.