摘要
针对目前星上遥感图像实时处理只能实现低级别算法的情况,提出了基于现场可编程门阵列(field-programmable gate array,FPGA)的P-H法星上相对姿态实时解算模型。该模型不仅避免了传统基于欧拉角的复杂三角函数计算与初值估算,还降低了迭代次数。试验选用FPGA(V7 xc7vx1140t)作为实时解算的硬件平台。在FPGA实现中,采用64位的浮点数据结构和串行/并行相结合策略;并采用LU(Lower-Upper)分解-分块算法实现矩阵求逆。试验结果表明,该模型的迭代次数比基于欧拉角的少了13次。该模型在FPGA和计算机的实现结果相差仅为5.0×10~(-14),加速度比为10。另外,该模型可广泛适用于实时性要求高的图像处理领域。
Aimed at the situation that the low-level algorithms were implemented in satellite real time processing system for remote sensing image, this paper proposes an FPGA(field programmable gate array)-based P-H method for satellite relative attitude on-board solution. The proposed algorithm not only avoids computations of trigonometric function and estimation of initial value, but also reduces the number of iterations when comparing with the Eulerian angle-based algorithm. The Xilinx FPGA(V7 xc7 vx1140 tflg1930-1) is selected as the hardware platform for the real-time processing. In FPGA implementation: ①We adopt a 64-bit floating point data structure and a strategy of combination of serial and parallel processing; ②a lower-upper(LU) decomposition-block algorithm is adopted for matrix inversion. The experimental results indicate that the number of iterations of the proposed algorithm is 13 less than the Eulerian angle-based algorithm. The difference of FPGA and PC implementation is about 5.0×10~(-14) and the speedup is about 10, which meets the requirements of precision and speed for on-board image real time processing. The proposed algorithm can be suitable for high real-time image processing field.
引文
[1] Zhou Guoqing, Baysal O, Kaye J. Concept Design of Future Intelligent Earth Observing Satellites[J]. International Journal of Remote Sensing, 2004, 25(14): 2 667-2 685
[2] Li Deren, Shen Xin. On Intelligent Earth Observation Systems[J]. Science of Surveying and Mapping, 2005, 30(4):9-11 (李德仁, 沈欣. 论智能化对地观测系统[J]. 测绘科学, 2005, 30(4):9-11)
[3] Zhang Bing. Intelligent Remote Sensing Satellite System[J]. Journal of Remote Sensing, 2011, 15(3):415-431 (张兵. 智能遥感卫星系统[J]. 遥感学报, 2011, 15(3): 415-431)
[4] Li Deren, Wang Mi, Shen Xin, et al. From Earth Observation Satellite to Earth Observation Brain[J]. Geomatics and Information Science of Wuhan University, 2017, 42(2):143-149 (李德仁, 王密, 沈欣, 等. 从对地观测卫星到对地观测脑[J]. 武汉大学学报·信息科学版, 2017, 42(2):143-149)
[5] Li Deren, Gong Jianya, Shao Zhenfeng. From Digi-tal Earth to Smart Earth[J]. Geomatics and Information Science of Wuhan University, 2010, 35(2):127-132 (李德仁, 龚健雅, 邵振峰. 从数字地球到智慧地球[J]. 武汉大学学报·信息科学版, 2010, 35(2):127-132)
[6] Du Liebo, Xiao Xuemin, Lu Qin, et al. An Implementation Scheme for JPEG2000 Satellite-Borne Remote Sensing Image Compression Based on FPGA + Multi-DSPs[J]. Journal of Test and Measurement Technology, 2008, 22(6):478-482 (杜列波, 肖学敏, 鲁琴, 等. 基于FPGA+多DSP的JPEG2000星载遥感图像压缩实现方案[J]. 测试技术学报, 2008, 22(6):478-482)
[7] Gong Jianya,Zhong Yanfei. Survey of Intelligent Optical Remote Sensing Image Processing[J].Journal of Remote Sensing, 2016, 20(5):733-747 (龚健雅, 钟燕飞. 光学遥感影像智能化处理研究进展[J]. 遥感学报, 2016, 20(5):733-747)
[8] Gao Lining,Long Teng. On-Board Spaceborne Real-Time Digital Signal Processing System[C]. Compu-ter Engineering and Applications, Nanjing, China, 2008(高立宁, 龙腾.基于FPGA的星上实时信息处理系统[C]. 全国信号处理与应用学术会议, 南京, 2008)
[9] You Zheng, Dai Mi. “Hangtian Tsinghua_1” Micro-Satellite and Its Image Processing[J]. Journal of Remote Sensing, 2001, 5(3):177-182 (尤政, 戴汩. “航天清华一号”微小卫星及其图像处理[J]. 遥感学报, 2001, 5(3):177-182)
[10] Williams J A, Dawood A S, Visser S J. FPGA-Based Cloud Detection for Real-Time Onboard Remote Sensing[C]. IEEE International Conference on Field-Programmable Technology, Hong Kong, China, 2002
[11] Gao Kun, Liu Yinghui, Ni Guoqiang, et al. Study on On-Board Real-Time Image Processing Technology of Optical Remote Sensing[J]. Spacecraft Recovery & Remote Sensing, 2008, 29(1):50-54 (高昆, 刘迎辉, 倪国强, 等. 光学遥感图像星上实时处理技术的研究[J]. 航天返回与遥感, 2008, 29(1): 50-54)
[12] Huang Jingjin, Zhou Guoqing. On-Board Detection and Matching of Feature Points[J]. Remote Sen-sing, 2017, 9:601
[13] Huang Jingjin, Zhou Guoqing, Zhang Dianjun, et al. An FPGA-Based Implementation of Corner Detection and Matching with Outlier Rejection[J]. International Journal of Remote Sensing, 2018, doi:10.1080101431161.2018.1500728
[14] Zhou Guoqing, Jiang Linjun, Huang Jingjin, et al. FPGA-Based On-Board Geometric Calibration for Linear CCD Array Sensors[J]. Sensors, 2018, 18(6):1 794
[15] Yan Li,Nie Qian, Zhao Zhan. Space Resection of Line Scanner CCD Image Based on the Description of Quaternions[J].Geomatics and Information Science of Wuhan University, 2010, 35(2):201-204 (闫利, 聂倩, 赵展. 利用四元数描述线阵CCD影像的空间后方交会[J]. 武汉大学学报·信息科学版, 2010, 35(2):201-204)
[16] Zhou Yongjun, Deng Caihua. A New Method for Relative Orientation with Hybrid Genetic Algorithm and Unit Quaternion[J]. Geomatics and Information Science of Wuhan University, 2011, 36(6):670-673 (周拥军, 邓才华. 利用HGA和单位四元数的相对定向解法[J]. 武汉大学学报·信息科学版, 2011, 36(6):670-673)
[17] Ben Jin, Tong Xiaochong, Lv Haiqing. Space Resection Based on the Pope-Hinsken Algorithm[J]. Journal of Geomatics Science and Technology, 2011, 28(1): 37-41 (贲进, 童晓冲, 闾海庆. 基于Pope-Hinsken算法的空间后方交会[J]. 测绘科学技术学报, 2011, 28(1):37-41)
[18] Jiang Gangwu, Jiang Ting, Wang Yong, et al. Space Resection Independent of Initial Value Based on Unit Quaternions[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(2):169-175 (江刚武, 姜挺, 王勇,等. 基于单位四元数的无初值依赖空间后方交会[J]. 测绘学报, 2007, 36(2):169-175)
[19] Wang Zhizhuo. Photogrammetry Principle[M]. Wuhan: Wuhan University Press, 2007(王之卓. 摄影测量原理[M]. 武汉:武汉大学出版社, 2007)
[20] Wu Guiming. Parallel Algorithms and Architectures for Matrix Computations on FPGA[D]. Changsha:National University of Defense Technology, 2011 (邬贵明. FPGA矩阵计算并行算法与结构[D].长沙:国防科学技术大学, 2011)