基于序列图像的航天器自主导航降维滤波方法

doi:10.7527/S1000-6893.2020.24971

电子电气工程与控制

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

基于序列图像的航天器自主导航降维滤波方法

孙博文^1,2, 王大轶², 王炯琦¹, 周海银¹, 葛东明², 董天舒²

1. 国防科技大学文理学院, 长沙 410073;
2. 中国空间技术研究院北京空间飞行器总体设计部, 北京 100094

收稿日期:2020-11-14 修回日期:2020-12-06 发布日期:2020-12-28
通讯作者: 王大轶 E-mail:dayiwang@163.com
基金资助:
国家杰出青年科学基金（61525301）；国家自然科学基金联合基金（U20B2055）；国家自然科学基金（61773021，61903366，61903386）；湖南省自然科学基金（2020 JJ4280）

Filter method for dimension reduction in spacecraft autonomous navigation based on sequence image

SUN Bowen^1,2, WANG Dayi², WANG Jiongqi¹, ZHOU Haiyin¹, GE Dongming², DONG Tianshu²

1. College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China;
2. Institute of Spacecraft System Engineering, China's Academy of Space Technology, Beijing 100094, China

Received:2020-11-14 Revised:2020-12-06 Published:2020-12-28
Supported by:
National Science Fund for Distinguished Young Scholars (61525301); National Natural Science Foundation of China (U20B2055); National Natural Science Foundation of China (61773021, 61903366, 61903386); National Natural Science Foundation of Hunan Province, China (2020 JJ4280)

摘要/Abstract

摘要： 非合作目标的运动感知与状态估计，是太空领域技术发展的重要组成部分。非合作目标相对状态的精确估计是相对导航的难点问题。传统的非合作目标扩展卡尔曼滤波算法需要结合非合作目标的质心位置，增加了状态变量的维数，提高了系统不确定性，从而会影响状态扩展卡尔曼滤波的收敛速度。提出了一种基于序列图像的非合作目标相对导航方法，该方法在不对质心进行估计的情况下首先对非合作目标姿态进行估计，在完成非合作目标姿态估计后再对其质心进行估计。本文推导了光学相机测量值与目标真实姿态的关系，构建了基于序列图像的测量模型，分别建立了不含有非合作目标质心位置的状态方程和基于非合作目标位置、速度矢量的状态方程，设计了适用于非合作目标状态估计的扩展卡尔曼滤波算法。仿真实验表明该方法可在10 Hz采样频率下经过50次采样（即5 s）内快速收敛，从而有利于空间飞行器的在轨服务与维护。

关键词: 非合作目标, 序列图像, 相对导航, 滤波算法, 收敛速度

Abstract: Motion measurement and state estimation of the non-cooperative target play an important role in the development of space technology. Estimation of the relative state of the non-cooperative target is a difficult problem. In the traditional extended Kalman filter algorithm, it is needed to estimate the centroid position of the non-cooperative target, which increases the dimension of state variables and uncertainty of the system, and thus affects the convergence speed of extended Kalman filtering. In this paper, a relative navigation method for non-cooperative target based on the sequence image is proposed. The attitude estimation of non-cooperative target can be realized without estimation of the centroid position, then the centroid position can be estimated based on the attitude estimated before. The relationship between the measured value and the true attitude of the non-cooperative target is derived. The sequence-image based measurement model is constructed. The state formula without the centroid position of the non-cooperative target and the state formula based on the position and velocity of non-cooperative target are established. An extended Kalman filter algorithm for state estimation of the non-cooperative target is developed. It is shown that the proposed method can converge rapidly within 50 samples times (i.e., 5 seconds) at a sampling frequency of 10HZ in the simulation, and is thus beneficial to the on-orbit service and maintenance of space vehicles.

Key words: non-cooperative target, sequence image, relative navigation, filter algorithm, convergence speed

中图分类号:

V249.3

孙博文, 王大轶, 王炯琦, 周海银, 葛东明, 董天舒. 基于序列图像的航天器自主导航降维滤波方法[J]. 航空学报, 2021, 42(4): 524971-524971.

SUN Bowen, WANG Dayi, WANG Jiongqi, ZHOU Haiyin, GE Dongming, DONG Tianshu. Filter method for dimension reduction in spacecraft autonomous navigation based on sequence image[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(4): 524971-524971.

参考文献

[1] TAFAZOLI M. A study of on-orbit spacecraft failures[J]. Acta Astronautica, 2009, 64(2-3):195-205.
[2] FLORES-ABAD A, MA O, PHAM K, et al. A review of space robotics technologies for on-orbit servicing[J]. Progress in Aerospace Sciences, 2014, 68(8):1-26.
[3] AKIN D, SULLIVAN B. A survey of serviceable spacecraft failures[C]//AIAA Space Conference & Exposition.Reston:AIAA, 2001.
[4] LI W J, CHENG D Y, LIU X G, et al. On-orbit service (OOS) of spacecraft:A review of engineering developments[J]. Progress in Aerospace Sciences, 2019, 108:32-120.
[5] 周军, 白博, 于晓洲. 一种非合作目标相对位置和姿态确定方法[J]. 宇航学报, 2011, 32(3):516-521. ZHOU J, BAI B, YU X Z. A new method of relative position and attitude determination for non-cooperative target[J]. Journal of Astronautics, 2011, 32(3):516-521(in Chinese).
[6] SHAN M H, GUO J, GILL E. Review and comparison of active space debris capturing and removal methods[J]. Progress in Aerospace Sciences, 2016, 80:18-32.
[7] ZHOU B Z, CAI G P, LIU Y M, et al. Motion prediction of a non-cooperative space target[J]. Advances in Space Research, 2017, 61(1):207-222.
[8] AGHILI F. A prediction and motion-planning scheme for visually guided robotic capturing of free-floating tumbling objects with uncertain dynamics[J]. IEEE Transactions on Robotics, 2012, 28(3):634-649.
[9] TERUI F, KAMIMURA H, NISHIDA S I. Motion estimation to a failed satellite on orbit using stereo vision and 3D model matching[C]//2006 9th International Conference on Control, Automation, Robotics and Vision, Singapore, 2006:1-8.
[10] XU W F, LIANG B, LI C, et al. A modelling and simulation system of space robot for capturing non-cooperative target[J]. Mathematical Modelling of Systems, 2009, 15(4):371-393.
[11] 王大轶, 张磊, 朱卫红, 等. 基于双目光学图像信息的空间非合作目标自主相对导航方法[J]. 中国科学:物理学力学天文学, 2019, 49(2):024509. WANG D Y, ZHANG L, ZHU W H, et al. Autonomous relative navigation for noncooperative target using stereo vision measurements[J]. SCIENTIA SINICA Physica, Mechanica & Astronomica, 2019, 49(2):024509(in Chinese).
[12] KIM S G, CRASSIDIS J L, CHENG Y, et al. Kalman filtering for relative spacecraft attitude and position estimation[J]. Journal of Guidance Control & Dynamics, 2007, 30(1):133-143.
[13] 王大轶, 葛东明, 史纪鑫,等. 基于序列图像的非合作目标自主导航及验证[J]. 南京航空航天大学学报, 2018, 50(6):727-733. WANG D Y, GE D M, SHI J X, et al. Non-cooperative target autonomous navigation and verification based on sequence image[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2018, 50(6):727-733(in Chinese).
[14] ZHANG Y Z, HUANG P F, SONG K H, et al. An angles-only navigation and control scheme for non-cooperative rendezvous operations[J]. IEEE Transactions on Industrial Electronics, 2019,66(11):8618-8627.
[15] CHEN F, ZHOU Y, LI R H, et al. Relative position and pose measurement approach of specific operation site of space non-cooperative target[C]//MIPPR 2015:Pattern Recognition and Computer Vision, 2015.
[16] 王楷, 陈统, 徐世杰. 基于双视线测量的相对导航方法[J]. 航空学报, 2011, 32(6):1084-1091. WANG K, CHEN T, XU S J. A method of double line-of-sight measurement relative navigation[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(6):1084-1091(in Chinese).
[17] 徐培智, 徐贵力, 王彪,等. 基于立体视觉的非合作目标位姿测量[J]. 计算机与现代化, 2013(8):85-91. XU P Z, XU G L, WANG B, et al. Pose measurement of non-cooperative target based on stereo vision[J]. Computer and Modernization, 2013(8):85-91(in Chinese).
[18] SEGAL S, CARMI A, GURFIL P. Stereovision-based estimation of relative dynamics between noncooperative satellites:Theory and experiments[J]. IEEE Transactions on Control Systems Technology, 2014, 22(2):568-584.
[19] PENG J Q, XU W F, LIANG B, et al. Pose measurement and motion estimation of space non-cooperative targets based on laser radar and stereo-vision fusion[J]. IEEE Sensors Journal, 2018, 19(8):3008-3019.
[20] AGHIL F, PARSA K. Motion and parameter estimation of space objects using laser-vision data[J]. Journal of Guidance Control & Dynamics, 2009, 32(2):537-549.
[21] ZHANG L J, ZHANG S F, YANG H B, et al. Relative attitude and position estimation for a tumbling spacecraft[J]. Aerospace Science and Technology, 2015, 42:97-105.
[22] GE D M, WANG D Y, ZOU Y J, et al. Motion and inertial parameter estimation of non-cooperative target on orbit using stereo vision[J]. Advances in Space Research, 2020, 66(6):1475-1484.
[23] PESCE V, LAVAGNA M, BEVILACQUA R. Stereovision-based pose and inertia estimation of unknown and uncooperative space objects[J]. Advances in Space Research, 2017, 59(1):236-251.

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于序列图像的航天器自主导航降维滤波方法

Filter method for dimension reduction in spacecraft autonomous navigation based on sequence image

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	殷泽阳, 邢友朋, 韩飞, 魏才盛, 廖宇新. 编队航天器协同绕飞非合作目标的全驱预设性能控制[J]. 航空学报, 2024, 45(1): 628904-628904.
[2]	郑伟, 王禹淞, 姜坤, 王奕迪. X射线脉冲星导航方法研究综述[J]. 航空学报, 2023, 44(3): 527451-527451.
[3]	徐升, 褚明, 蔺绍奇, 常睿, 孙汉旭. 非合作目标软捕获后的动力学参数无激励辨识[J]. 航空学报, 2023, 44(19): 228342-228342.
[4]	褚明, 蔺绍奇, 徐升, 常睿. 空间非合作目标全向柔顺对接关节设计与仿真[J]. 航空学报, 2023, 44(13): 428024-428024.
[5]	陈斌, 郗厚印, 张晓东, 罗敏, 郭治栋. 基于测地线距离的空间非合作目标点云配准[J]. 航空学报, 2023, 44(1): 326336-326336.
[6]	孙洪驰, 穆荣军, 龙腾, 李寿鹏, 崔乃刚. 临近空间飞行器北斗/INS高动态深组合导航方法[J]. 航空学报, 2022, 43(9): 325672-325672.
[7]	王梓, 孙晓亮, 李璋, 程子龙, 于起峰. 基于Transformer模型的卫星单目位姿估计方法[J]. 航空学报, 2022, 43(5): 325298-325298.
[8]	夏鹏程, 罗建军, 王明明, 谭龙玉. 空间双臂机器人抓捕非合作目标后的协调稳定控制[J]. 航空学报, 2022, 43(2): 325398-325398.
[9]	王大轶, 侯博文, 王炯琦, 葛东明, 李茂登, 徐超, 周海银. 航天器自主导航状态估计方法研究综述[J]. 航空学报, 2021, 42(4): 524310-524310.
[10]	王润, 郁丰, 周士兵, 刘方武. 基于3D Zernike矩的巡检器与空间站的相对导航算法[J]. 航空学报, 2021, 42(2): 324298-324298.
[11]	叶子鹏, 周庆瑞, 王辉. 日地L2点航天器编队的分布式自主相对导航[J]. 航空学报, 2021, 42(2): 324145-324145.
[12]	董凯凯, 罗建军, 马卫华, 高登巍, 谭龙玉. 非合作目标交会的双层MPC全局轨迹规划控制[J]. 航空学报, 2021, 42(11): 524903-524903.
[13]	牟金震, 刘宗明, 韩飞, 周彦, 李爽. 失效卫星远距离相对位姿估计与优化方法[J]. 航空学报, 2021, 42(11): 524959-524959.
[14]	韩飞, 刘付成, 王兆龙, 杜宣, 刘珊珊, 刘超镇. 空间多机器人协同的多视线仅测角相对导航[J]. 航空学报, 2021, 42(1): 524174-524174.
[15]	万文娅, 孙冲, 袁建平. 空间非合作目标多指包络抓捕路径设计[J]. 航空学报, 2020, 41(12): 324041-324041.