A Fast Accurate Back-Projection Algorithm for Multi-receiver Synthetic Aperture Sonar in Heterogeneous Environment
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摘要: 针对多子阵合成孔径声呐精确后向投影成像算法效率低的问题, 提出了一种异构环境下的精确多子阵合成孔径声呐后向投影成像快速方法。在分析精确逐点后向投影成像算法原理的基础上, 将脉冲压缩和方位向聚焦过程改造为单指令多线程模式, 借助图形处理器(graphics processor unit, GPU)强大的多核计算能力加速成像过程。通过仿真和实测数据的成像实验验证了所提快速成像算法的正确性和高效性, 与串行成像算法相比, 其加速比分别高达326.3和333.6。对于大规模数据成像处理, 所提方法体现出优异的加速性能, 满足实时信号处理需求, 同时为后续开展运动补偿奠定了基础。Abstract:Objectives Synthetic aperture sonar (SAS) is one kind of high resolution underwater imaging sonar. Its principle is to use small array to simulate large aperture array by uniforming linear motion along the direction of flight track, and realize coherent processing of echo signal to obtain high resolution two-dimensional sonar image, which is independent of imaging distance and acoustic wavelength. The back projection algorithm is an accurate point-by-point imaging algorithm, which is characterized by accurate focusing ability, suitable for wide beam and large scene imaging, and easy to realize motion compensation, but it has the disadvantages of low computational efficiency. In recent years, with the development of computer technology, especially the appearance of graphics processor unit, it has powerful computing power and provides a new way to accelerate the back projection algorithm.Methods We propose a fast accurate back projection algorithm for multi-receiver SAS in heterogeneous environment. On the basis of analyzing the principle of accurate back-projection imaging algorithm, the pulse compression and time-consuming azimuth accumulation are transformed into a single instruction multi-threaded mode, and the imaging process is accelerated by the powerful multi-core computing ability of graphics processor unit.Results The validity and efficiency of the proposed fast imaging algorithm are verified by the imaging experiments performed on simulated and real SAS data. Compared with the serial imaging algorithm, its acceleration ratio is as high as 326.3 and 333.6. For large-scale data imaging processing, it shows excellent acceleration performance.Conclusions The proposed back projection imaging algorithm greatly improves the imaging efficiency and meets the needs of real-time SAS imaging, which lays the foundation for subsequent motion compensation.
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图 4 异构环境下的成像算法流程
Figure 4. Flowchart of Imaging Algorithm in Heterogeneous Environment
表 1 仿真系统参数
Table 1 System Parameter for Simulation
参数 数值 参数 数值 带宽/kHz 20 脉冲间隔/ms 200 载频/kHz 150 子阵长/m 0.04 脉宽/ms 20 子阵个数 25 声速/(m∙s－1) 1 500 速度/(m∙s－1) 2.5 
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表 2 仿真点目标成像性能比较
Table 2 Imaging Quality Comparison of Simulated Target
方法 距离向 方位向 IRW
/cmPSLR
/dBISLR
/dBIRW
/cmPSLR
/dBISLR
/dB串行 3.4 －13.7 －10.8 2.2 －13.0 －10.2 并行 3.4 －13.7 －10.8 2.2 －13.1 －10.2
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表 3 实验系统基本参数
Table 3 System Parameter of the Trial
参数 数值 参数 数值 带宽/kHz 20 脉冲间隔/ms 320 载频/kHz 150 子阵长/m 0.04 脉宽/ms 20 子阵个数 40 声速/(m∙s－1) 1446 速度/(m∙s－1) 2.5 采样率/kHz 40 采样距离/m 51 231
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表 4 不同成像方法效率比较
Table 4 Efficiency Comparison of the Different Imaging Algorithms
成像场景 成像方式 数据上传时间/ms 脉冲压缩时间/ms 方位叠加时间/ms 数据下载时间/ms 总成像时间/ms 加速比 小场景 串行 3 541 3 153 097 3 156 638 1 共享内存并行 298 148 049 148 347 21.3 异构并行 50 33 9 553 38 9 674 326.3 大场景 串行 10 025 10 555 120 10 565 145 1 共享内存并行 641 456 303 456 944 23.1 异构并行 151 90 31 311 116 31 668 333.6
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[1] Hayes M P, Gough P T. Synthetic Aperture Sonar: A Review of Current Status[J]. IEEE Journal of Oceanic Engineering, 2009, 34(3): 207-224 doi: 10.1109/JOE.2009.2020853
[2] 刘经南, 阳凡林, 赵建虎. 浅析合成孔径声纳与干涉合成孔径声纳[J]. 海洋测绘, 2003, 23(2): 1-4 doi: 10.3969/j.issn.1671-3044.2003.02.001 Liu Jingnan, Yang Fanlin, Zhao Jianhu. Elementary Introduction to Synthetic Aperture Sonar and Interferometric Synthetic Aperture Sonar[J]. Hydrographic Surveying and Charting, 2003, 23(2): 1-4 doi: 10.3969/j.issn.1671-3044.2003.02.001
[3] Wang V T, Hayes M P. Synthetic Aperture Sonar Track Registration Using SIFT Image Correspondences[J]. IEEE Journal of Oceanic Engineering, 2017, 42(4): 901-913 doi: 10.1109/JOE.2016.2634078
[4] Myers V, Quidu I, Zerr B, et al. Synthetic Aperture Sonar Track Registration with Motion Compensation for Coherent Change Detection[J]. IEEE Journal of Oceanic Engineering, 2019, 45(3): 1045-1062
[5] Ødegård Ø, Hansen R E, Singh H, et al. Archaeological Use of Synthetic Aperture Sonar on Deepwater Wreck Sites in Skagerrak[J]. Journal of Archaeological Science, 2018, 89: 1-13 doi: 10.1016/j.jas.2017.10.005
[6] Ulander L M H, Hellsten H, Stenstrom G. SyntheticAperture Radar Processing Using Fast Factorized Back-Projection[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39 (3) : 760-776 doi: 10.1109/TAES.2003.1238734
[7] Yegulalp A F. Fast Back Projection Algorithm for Synthetic Aperture Radar[C]//IEEE Radar Conference, Waltham, MA, USA, 1999
[8] Wu H R, Tang J S, Zhong H P. Moderate Squint Imaging Algorithm for the Multiple-Hydrophone SAS with Receiving Hydrophone Dependence[J]. IET Radar, Sonar and Navigation, 2019, 13(1): 139-147 doi: 10.1049/iet-rsn.2018.5055
[9] Tian Z, Tang J S, Zhong H P, et al. Extended Range Doppler Algorithm for Multiple-Receiver Synthetic Aperture Sonar Based on Exact Analytical Two-Dimensional Spectrum[J]. IEEE Journal of Oceanic Engineering, 2016, 41(1): 164-174 doi: 10.1109/JOE.2015.2402053
[10] Zhang X B, Tang J S, Zhong H P. Multireceiver Correction for the Chirp Scaling Algorithm in Synthetic Aperture Sonar[J]. IEEE Journal of Oceanic Engineering, 2014, 39(3): 472-481 doi: 10.1109/JOE.2013.2251809
[11] 王金波, 唐劲松, 张森, 等. 一种宽带大斜视STOLT插值及距离变标补偿方法[J]. 电子与信息学报, 2018, 40(7): 1575-1582 https://www.cnki.com.cn/Article/CJFDTOTAL-DZYX201807008.htm Wang Jinbo, Tang Jinsong, Zhang Sen, et al. Range Scaling Compensation Method Based on STOLT Interpolation in Broadband Squint SAS Imaging[J]. Journal of Electronics and Information Technology, 2018, 40(7): 1575-1582 https://www.cnki.com.cn/Article/CJFDTOTAL-DZYX201807008.htm
[12] Li W J, Liao G S, Zhu S Q, et al. A Novel Helicopter-Borne RoSAR Imaging Algorithm Based on the Azimuth Chirp Z Transform[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 16(2): 226-230 doi: 10.1109/LGRS.2018.2871379
[13] Li B L, Liu W, Liu J Y, et al. Real-Time Implementation of Synthetic Aperture Sonar Imaging on High Performance Clusters[C]//The11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, London, UK, 2010
[14] 方留杨, 王密, 潘俊. CPU和GPU协同的多光谱影像快速波段配准方法[J]. 武汉大学学报·信息科学版, 2018, 43(7): 1000-1007 doi: 10.13203/j.whugis20160218 Fang Liuyang, Wang Mi, Pan Jun. CPU/GPU Cooperative Fast Band Registration Method for Multispectral Imagery[J]. Geomatics and Information Science of Wuhan University, 2018, 43 (7) : 1000-1007 doi: 10.13203/j.whugis20160218
[15] 王鸿琰, 关雪峰, 吴华意. 一种面向CPU/GPU异构环境的协同并行空间插值算法[J]. 武汉大学学报·信息科学版, 2017, 42(12): 1688-1695 doi: 10.13203/j.whugis20150361 Wang Hongyan, Guan Xuefeng, Wu Huayi. A Collaborative Parallel Spatial Interpolation Algorithmon Oriented Towards the Heterogeneous CPU/GPU System[J]. Geomatics and Information Science of Wuhan University, 2017, 42(12): 1688-1695 doi: 10.13203/j.whugis20150361
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