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An Information Theory Approach to the Data Compression and Imaging System for Synthetic Aperture Radar (SAR)
作者姓名:Xiao Yongxin  Peng Hailiang and Chen Zongzhi
作者单位:Institute of Electronics,Chinese Academy of Sciences,Beijing 100080,P. R. China.
摘    要:AnInformationTheoryApproachtotheDataCompressionandImagingSystemforSyntheticApertureRadar(SAR)¥XiaoYongxin;PengHailiangandChen...


An Information Theory Approach to the Data Compression and Imaging System for Synthetic Aperture Radar (SAR)
Xiao Yongxin, Peng Hailiang and Chen Zongzhi.An Information Theory Approach to the Data Compression and Imaging System for Synthetic Aperture Radar (SAR)[J].Journal of Systems Engineering and Electronics,1995(1).
Authors:Xiao Yongxin  Peng Hailiang and Chen Zongzhi
Abstract:Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.
Keywords:Synthetic aperture radar (SAR)  information theory  data compression  radiometric resolution  probability density function (PDF)  multiple access channel  average mutual information
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