原始数据压缩对星载SAR/GMTI系统测速影响研究

行坤; 邓云凯; 祁海明

doi:10.3724/SP.J.1146.2009.00868

原始数据压缩对星载SAR/GMTI系统测速影响研究

doi: 10.3724/SP.J.1146.2009.00868

计量
- 文章访问数: 3856
- HTML全文浏览量: 106
- PDF下载量: 682
- 被引次数: 0
出版历程
- 收稿日期: 2009-06-12
- 修回日期: 2009-11-24
- 刊出日期: 2010-06-19

Study of Effect of Raw Data Compression on Space-borne SAR/GMTI Velocity Measurement

摘要

摘要: 星载SAR原始数据压缩是目前解决星载SAR实时获取的海量数据与星上有限数传带宽的有效手段。压缩比越大，数据率越低，但较大的量化误差将影响SAR-GMTI的测速精度；压缩比越低，数据压缩对测速精度影响越小，但数据率越高。因此，数据压缩比的选择需要在数据率与测速精度之间取得折中。该文建立了星载SAR/GMTI系统回波信号仿真模型，仿真了星载SAR-GMTI原始数据，针对相位中心偏置天线(DPCA)与沿迹干涉(ATI) 两种有重要工程应用潜力的方法，详细分析了分块自适应量化 (BAQ) 算法对测速精度的影响。该文的研究结果将为星载SAR/GMTI系统的压缩比选择提供重要的理论依据。
- 合成孔径雷达; 原始数据; 压缩; 地面动目标显示; 速度测量
Abstract: At present, the effective way to resolve the contradiction between huge space-borne SAR raw data rate and limited on-board data-transmission bandwidth is space-borne SAR raw data compression. The higher compression ratio is, the lower data rate will be, but larger quantization error will affect the velocity measurement accuracy of SAR-GMTI. The lower compression ratio is, the less effect of data compression on velocity measurement accuracy is, but the higher data rate will be. Therefore, the choice of data compression ratio needs achieve a compromise between data rate and velocity measurement accuracy. This paper establishes the echo simulation model of space-borne SAR/GMTI system and simulates the raw data of space-borne SAR-GMTI. For Displaced Phase Center Antenna (DPCA) and Along-Track Interferometry (ATI) methods which have significant application potentialities in practice, this paper analyzes the effect of Block Adaptive Quantization (BAQ) algorithm on velocity measurement accuracy in detail. The results of this paper provides important theory basis for the choice of compression ratio of the space-borne SAR/GMTI system.

HTML全文

参考文献(1)

Raney R K. Synthetic aperture imaging radar and moving targets[J].IEEE Transactions on Aerospace and Electronic Systems.1971, 7(3):499-505[2]Stockburger E F and Held D N. Interferometric moving ground target imaging. Proceedings of the IEEE International Radar Conference, Alexandria, New York, May 1995: 438-443.[3]杨垒, 王彤, 邢孟道, 保铮. 机载多通道SAR-GMTI的杂波抑制方法[J].电子与信息学报.2008, 30(12):2831-2834浏览Yang Lei, Wang Tong, Xing Meng-dao, and Bao Zheng. The clutter suppression method of airborne multi-channel SAR-GMTI system. Journal of Electronics and Information Technology, 2008, 30(12): 2831-2834.[4]Chiu S and Livingstone C, et al.. RADARSAT-2 moving object detection experiment(MODEX). Proceedings of the International Geoscience and Remote Sensing Symposium, Boston, Massachusetts, July 2008: 13-16.[5]Suchandt S and Runge H, et al.. First results of ground moving target analysis in TerraSAR-X data. Proceedings of EUSAR 2008, Friedrichshafen, Germany, June 2008: 55-58.[6]Livingstone C E, Sikaneta I, Gierull C H, and Chiu S, et al.. An airborne Synthetic Aperture Radar (SAR) experiment to support RADARSAT-2 Ground Moving Target Indication (GMTI). Canadian Journal of Remote Sensing, 2002, 28(6): 794-813.[7]Barbarossa S and Farina A. Space-time-frequency processing of synthetic aperture radar signals[J].IEEE Transactions on Aerospace and Electronic Systems.1994, 30(2):341-358[8]Kwok R and Johnson W T K. Block adaptive quantization of Magellan SAR data[J].IEEE Transactions on Geoscience and Remote Sensing.1989, 27(4):375-383[9]关振红, 朱岱寅等. 归一化自适应预测矢量量化算法压缩SAR原始数据[J].电子与信息学报.2006, 28(3):507-511浏览Guan Zhen-hong and Zhu Dai-yin, et al.. Compression of SAR raw data with normalized adaptive predictive vector quantization. Journal of Electronics and Information Technology, 2006, 28(3): 507-511.[10]祁海明, 禹卫东. 基于二维查找表结构的SAR原始数据自适应频域压缩算法[J].电子与信息学报.2009, 31(3):592-595浏览Qi Hai-ming and Yu Wei-dong. Adaptive frequency domain algorithm for SAR raw data compression based on two dimensions look-up table. Journal of Electronics and Information Technology, 2009, 31(3): 592-595.[11]Mcleod I and Cumming I. ENVISAT ASAR data reduction: Impact on SAR interferometry[J].IEEE Transactions on Geoscience and Remote Sensing.1998, 36(2):589-602[12]祁海明, 禹卫东. 针对饱和度全集上SAR原始数据自适应抗饱和BAQ压缩算法. 自然科学进展, 2009, 19(2): 227-234.[13]Qi Hai-ming and Yu Wei-dong. Anti-saturation block adaptive quantization algorithm for SAR raw data compression over the whole set of saturation degrees[J].Progress in Natural Science.2009, 19(8):1003-1009[14]祁海明, 禹卫东. 基于实测数据的原始数据压缩对InSAR系统测高影响研究[J].电子与信息学报.2008, 30(11):2693-2697浏览Qi Hai-ming and Yu Wei-dong. Study of effect of raw data compression on space-borne InSAR interferometry based on real data. Journal of Electronics and Information Technology, 2008, 30(11): 2693-2697.[15]祁海明, 禹卫东, 田旭文等. 星载SAR原始数据BAQ压缩算法性能评估[J]. 现代雷达, 2007, 29(11): 17-21.Qi Hai-ming, Yu Wei-dong, and Tian Xu-wen, et al.. Evaluation of BAQ algorithm for spaceborne SAR raw data compression. Modern Radar, 2007, 29(11): 17-21.[16]Schaefer C and Wagner A. Analysis of potential GMTI performance of TanDEM-X. Proceedings of EUSAR 2008, Friedrichshafen, Germany, June 2008: 115-118.[17]袁孝康. 星载合成孔径雷达导论. 北京: 国防工业出版社, 2003, 第2, 5章.[18]魏钟铨. 合成孔径雷达卫星. 北京: 科学出版社, 2001, 第7章.

施引文献

资源附件(0)

访问统计