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星载ScanSAR成像研究

Study of Space-borne ScanSAR Image Processing

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【作者】 丁丁; 王贞松; 荆麟角; 徐永健; 谢列宾;

【Author】 DING Ding 1,WANG Zhen song 2,JING Lin jiao,XU Yong jian 1,XIE Lie bin 1 (1 Institute of Electronic,CAS;2 Institute of Computing Technology,CAS,Beijing 100080,China)

【机构】 中国科学院电子学研究所; 中国科学院计算技术研究所; 中国科学院电子学研究所 北京100080; 北京100080; 北京100080;

【摘要】 分析扫描模式合成孔径雷达不同于传统合成孔径雷达回波的时、频域特点。通过对不同成像方法及加拿大RadarSAT扫描模式雷达实际回波数据的理解 ,根据扫描模式雷达回波的特点 ,实现了全孔径RD算法 ,快速SPECAN算法和ChirpScaling算法几种适合于扫描模式雷达回波成像的算法 ,并在算法实现过程中结合实际数据讨论了抑制点目标回波旁瓣、实现快速距离走动校正、减弱Scalloping效应、抑制方位向重影、准确估计多普勒中心频率等问题 ,针对这些问题提出了一些新方法并通过模拟或实际数据成像进行了验证。

【Abstract】 This paper is about the processing of the burst mode Space borne ScanSAR data There are many algorithms developed for processing the strip mode space borne SAR data,for example;the RD algorithm,the Specan algorithm,the Chirp Scaling algorithm,the Ω k algorithm However,due to the bursting characteristics of the ScanSAR data and the operation mode of the ScanSAR,none of the above algorithms can be used directly in the processing of the Space borne ScanSAR data In this paper,the time domain and the frequency domain characteristics of the ScanSAR echo were analyzed Based on the understanding of RadarSAT ScanSAR data and the characteristics of the ScanSAR echo,the full swath RD algorithm,fast SPECAN algorithm and Chirp Scaling algorithm were developed The RD algorithm for whole scanned swath is an effective algorithm,the SPECAN algorithm can provide a high resolution image quickly and the chirp scaling algorithm has an excellent phase preserving ability In the real data processing,some methods like the side lobe control of point target echo,the fast range walk correction,the scalloping weakening,the range ambiguity control,the azimuth false target elimination and the Doppler centroid frequency estimation were discussed and verified

【关键词】 星载SAR; 扫描模式; 成像算法;
【Key words】 space borne SAR; ScanSAR; image processing algorithm;
【基金】 86 3 30 8 11 0 2 ( 1)项目资助
  • 【文献出处】 遥感学报 ,Journal of Remote Sensing , 编辑部邮箱 ,2002年04期
  • 【分类号】TN957.5
  • 【被引频次】16
  • 【下载频次】364
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