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Study of Effect of Raw Data Compression on Azimuth Multi-channel SAR System
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摘要: 方位向多通道是实现星载SAR高分辨率宽测绘带成像的重要技术手段，随着分辨率和幅宽的提升，SAR系统的回波数据量也会急剧增加。然而星上存储空间和数传带宽有限，通常采用数据压缩技术降低回波的数据量。为研究数据压缩对方位向多通道SAR系统的影响，该文建立了多通道数据压缩的信号模型，推导并分析了数据压缩对多通道信噪比尺度因子和量化噪声的影响，最后通过仿真和实测数据验证了该文提出的模型与分析结果的正确性，并讨论了数据压缩对多通道虚假目标强度比的影响。该文的研究结果可为多通道SAR系统的原始数据压缩方式选择提供依据。Abstract: An effective way to achieve High Resolution and Wide Swath (HRWS) imaging capability is the multi-channel technique in azimuth. Improved resolution and swath can dramatically increase the volume of echo data in the SAR system. However, the onboard data storage and data-transmission bandwidth are limited, so data compression technique is typically used to reduce the volume of echo data. To study the effect of raw data compression on the azimuth multi-channel SAR system, in this paper, we establish a multi-channel SAR signal model based on data compression. We then derive and analyze the effects of data compression on the Signal-to-Noise Ratio (SNR) scaling factor of the multi-channel SAR system and quantization noise. Finally, we verify the validity of the proposed model and analysis results using simulation and real data and discuss the effect of data compression on the Peek-to-Ghost Ratio (PGR). The results of this paper provide an important theoretical basis for the choice of compression method in the multi-channel SAR system.
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图 5 加入不同热噪声的信噪比尺度因子随量化比特数的变化曲线
Figure 5. SNR scaling factor of adding different thermal noise over quantization bits
图 6 不同非均匀因子的数据域量化信噪比随量化比特数的变化曲线
Figure 6. Signal to quantization noise ratio of different non-uniform factors over quantization bits in data domain
图 7 不同非均匀因子的虚假目标强度比随量化比特数的变化曲线
Figure 7. Peek-to-ghost-ratio of different non-uniform factors over quantization bits
图 10 数据域量化信噪比随量化比特数的变化曲线
Figure 10. The signal to Quantization Noise Ratio over quantization bits in data domain
图 11 数据域平均相位误差随量化比特数的变化曲线
Figure 11. Mean phase error over quantization bits in data domain
图 12 图像域量化信噪比随量化比特数的变化曲线
Figure 12. Signal to quantization noise ratio over quantization bits in image domain
图 13 图像域平均相位误差随量化比特数的变化曲线
Figure 13. Mean phase error over quantization bits in image domain
表 1 多通道SAR系统的主要仿真参数
Table 1. Main simulation parameters of multi-channel SAR system
参数 数值 载频(GHz) 9.65 非均匀因子 0～0.7 速度(m/s) 7609.4 接收天线长度(Rx) (m) 4.78 子孔径数 2 发射天线长度(Tx) (m) 2.39 
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表 2 多通道SAR系统的主要系统参数
Table 2. Main parameters of multi-channel SAR system
参数 数值 载频(GHz) 5.4 PRF(Hz) 1800 速度(m/s) 137.7 接收天线长度(Rx) (m) 0.624 子孔径数 4 发射天线长度(Tx) (m) 0.156
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[1] Cumming I G and Wong F H. Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation[M]. Norwood, MA: Artech House, 2005. [2] 邓云凯, 赵凤军, 王宇. 星载SAR技术的发展趋势及应用浅析[J]. 雷达学报, 2012, 1(1): 1–10Deng Yun-kai, Zhao Feng-jun, and Wang Yu. Brief analysis on the development and application of spaceborne SAR[J]. Journal of Radars, 2012, 1(1): 1–10 [3] Currie A and Brown M A. Wide-swath SAR[J]. IEE Proceedings F-Radar and Signal Processing, 1992, 139(2): 122–135. DOI: 10.1049/ip-f-2.1992.0016 [4] Currie A. Wide-swath SAR imaging with multiple azimuth beams[C]. Proceedings of IEE Colloquium on Synthetic Aperture Radar, London, UK, 1989: 3/1–3/4. [5] Currie A and Hall C D. A synthetic aperture radar technique for the simultaneous provision of high-resolution wide-swath coverage[C]. Proceedings 1990 Military Microwaves Conference, 1990: 539–544. [6] Gebert N, Krieger G, and Moreira A. Digital beamforming on receive: Techniques and optimization strategies for high-resolution wide-swath SAR imaging[J]. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(2): 564–592. DOI: 10.1109/TAES.2009.5089542 [7] Kim J H, Younis M, Prats-Iraola P, et al. First spaceborne demonstration of digital beamforming for azimuth ambiguity suppression[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(1): 579–590. DOI: 10.1109/TGRS.2012.2201947 [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. DOI: 10.1109/36.29557 [9] Max J. Quantizing for minimum distortion[J]. IRE Transactions on Information Theory, 1960, 6(1): 7–12. DOI: 10.1109/TIT.1960.1057548 [10] McLeod I H and Cumming I G. On-board encoding of the ENVISAT wave mode data[C]. Proceedings of IEEE International Geoscience and Remote Sensing Symposium, Firenze, Italy, 1995, 3: 1681–1683. [11] Martone M, Bräutigam B, and Krieger G. Quantization effects in TanDEM-X data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(2): 583–597. DOI: 10.1109/TGRS.2014.2325976 [12] Pavia P, Spera G, Venturini R, et al.. CSG satellite design and performance[C]. Proceedings of the 11th European Conference on Synthetic Aperture Radar, Hamburg, Germany, 2016: 1023–1026. [13] McLeod I H, Cumming I G, and Seymour M S. ENVISAT ASAR data reduction: Impact on SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(2): 589–602. DOI: 10.1109/36.662741 [14] Benz U, Strodl K, and Moreira A. A comparison of several algorithms for SAR raw data compression[J]. IEEE Transactions on Geoscience and Remote Sensing, 1995, 33(5): 1266–1276. DOI: 10.1109/36.469491 [15] 谭洪, 仇晓兰, 洪峻. 原始数据压缩对全极化SAR极化信息的影响[J]. 系统工程与电子技术, 2015, 37(9): 2029–2034 doi: 10.3969/j.issn.1001-506X.2015.09.12Tan Hong, Qiu Xiao-lan, and Hong Jun. Effect of raw data compression on polarimetric information of quad polarimetric SAR[J]. Systems Engineering and Electronics, 2015, 37(9): 2029–2034. DOI: 10.3969/j.issn.1001-506X.2015.09.12 [16] 行坤, 邓云凯, 祁海明. 原始数据压缩对星载SAR/GMTI系统测速影响研究[J]. 电子与信息学报, 2010, 32(6): 1321–1326Xing Kun, Deng Yun-kai, and Qi Hai-ming. Study of effect of raw data compression on space-borne SAR/GMTI velocity measurement[J]. Journal of Electronics&Information Technology, 2010, 32(6): 1321–1326 [17] Krieger G, Gebert N, and Moreira A. Unambiguous SAR signal reconstruction from nonuniform displaced phase center sampling[J]. IEEE Geoscience and Remote Sensing Letters, 2004, 1(4): 260–264. DOI: 10.1109/LGRS.2004.832700 [18] Jing Wei, Xing Meng-dao, Qiu Cheng-wei, et al. Unambiguous reconstruction and high-resolution imaging for multiple-channel SAR and airborne experiment results[J]. IEEE Geoscience and Remote Sensing Letters, 2009, 6(1): 102–106. DOI: 10.1109/LGRS.2008.2008825 [19] Lin Y P and Vaidyanathan P P. Periodically nonuniform sampling of bandpass signals[J]. IEEE Transactions on Circuits and Systems II:Analog and Digital Signal Processing, 1998, 45(3): 340–351. DOI: 10.1109/82.664240 [20] Jenq Y C. Perfect reconstruction of digital spectrum from nonuniformly sampled signals[J]. IEEE Transactions on Instrumentation and Measurement, 1997, 46(3): 649–652. DOI: 10.1109/19.585419 [21] 仇晓兰, 雷斌, 葛蕴萍, 等. SAR原始数据两种量化压缩方式的性能评估[J]. 电子与信息学报, 2010, 32(9): 2268–2272Qiu Xiao-lan, Lei Bin, Ge Yun-ping, et al. Performance evaluation of two compression methods for SAR raw data[J]. Journal of Electronics&Information Technology, 2010, 32(9): 2268–2272 [22] Algra T. Data compression for operational SAR missions using entropy-constrained block adaptive quantisation[C]. Proceedings of 2002 IEEE International Geoscience and Remote Sensing Symposium, Toronto, Canada, 2002, 2: 1135–1139. [23] 郜参观, 邓云凯, 冯锦, 等. 非均匀采样对偏置相位中心多波束SAR性能影响的分析[J]. 电子与信息学报, 2012, 34(6): 1305–1310Gao Can-guan, Deng Yun-kai, Feng Jin, et al. Analysis on the non-uniform sampling of displaced phase center multiple-beam SAR systems[J]. Journal of Electronics&Information Technology, 2012, 34(6): 1305–1310 [24] 李信, 祁海明, 华斌, 等. 星载SAR原始数据压缩引起的目标辐射误差机理研究[J]. 电子与信息学报, 2011, 33(8): 1845–1850Li Xin, Qi Hai-ming, Hua Bin, et al. Theoretical analysis on target radiometric error resulting from spaceborne SAR raw data compression[J]. Journal of Electronics&Information Technology, 2011, 33(8): 1845–1850 -
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