Performance Analysis of Block Adaptive Quantization in Synthetic Aperture Radar raw data compression by using practical SAR raw data and Representation of Adaptive Rate Selection

The Adaptive Block Quantization approach, or BAQ, is a common approach to compress synthetic aperture Radar raw data. Radar imaging systems, especially spaceborne SAR system, exploit large bandwidth and high sampling rate, resulting in a large bitstream to be handled. This leads to a major challenge due to the high volume of data obtained for each area being imaged, storing or sending raw data through a data link. Therefore, by using “raw data compression”, data link bandwidth and the needed memory capacity can be reduced effectively. In the course of developing the technical knowledge of spaceborne SAR systems in the country, the design and implementation of SAR raw data compression algorithms has been developed in the Institute of Mechanics. In order to evaluate and analyze the efficiency of these methods, the SAR raw data of a SAR system developed by the Institute of Mechanics were used. One of the most important issues discussed in this paper is the adaptive selection of the BAQ rate in the raw data compression as well as the effect of this bit rate selection on the quality of image which is formed by the compressed data. To compare the resulting images from different BAQ bit rates, the PSNR criterion and visual evaluations of the resulting images are used. The results of this comparison indicate the high performance of the proposed approach.