Research Of Several Algorithms For SAR Raw Data Compression

Synthetic Aperture Radar (SAR) is a kind of all-weather and day-and-night remote sensing tools, through which high resolution image can be obtained. The amount of raw data of SAR is so large that it is difficult to downlink and to save. So the efficient algorithms for SAR raw data compression have become important tools in fulfilling the requirement of reducing data rate. In this article, Some SAR raw data compression algorithms have been studied by using true airborne SAR raw data.In the preface to this article, the base idea and the development of SAR raw data compression algorithms are introduced briefly.In chapter 2, the theories of data compression and quantization are introduced.In chapter 3, the statistical properties of raw data of the received electromagnetic waves are analyzed and computed, which show that the real and imaginary parts of SAR raw data have zero means, slow changing variance, and asymptotically Gaussian distribut. The high entropy of the real and imaginary parts of SAR raw data makes Lossless-Coding compression techniques unfit for SAR raw data.In chapter 4, some compression algorithms for SAR raw data compression, such as BAQ, UPQ, BAVQ and WT-subbandcade are analyzed and discussed. An improved Unrestricted Polar Quantizer (UPQ), which can enhance the performance of the quantizer is put forward.In chapter 5, all above algorithms are tested with the true raw data of an X-band SAR. The test results of different algorithms are compared in both data domain and image domain.In the end, conclusions and possible future work are explained.