自主光学导航非线性滤波算法研究
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摘要
新世纪以来,以大、小天体探测为代表的深空探测新热点逐渐兴起,深空探测技术研究与计划实施迎来新的高潮。深空探测任务的远距离导致较大的通讯延迟,靠地面测控站与深空探测器进行远程通讯,已经不能满足深空探测的任务要求。自主导航技术必将取而代之,成为二十一世纪深空探测领域的关键技术之一。
本学位论文结合“十五”863计划项目——“深空探测器自主导航技术”,分析了深空探测自主光学导航的背景及国内外发展现状,研究了一系列非线性滤波算法在自主光学导航技术中的应用。论文的主要内容包括:
首先,在综合分析大量有价值的参考文献的基础上,介绍了自主光学导航系统的研究意义、背景、国内外的发展现状;结合深空探测以及自主光学导航的任务流程,对光学导航原理进行简要分析;针对深空探测不同的任务阶段,介绍了相应的轨道动力学模型,并给出了各自的导航方案;对深空探测的观测模型建立过程进行了必要的说明,为下一步自主光学导航非线性滤波算法研究打下良好的基础。
其次,针对深空探测任务实时性要求较高,数据运算量大,而星载计算机运算能力有限的问题,在黄道坐标系中引入柱面坐标系,将TSS-EKF算法应用到自主光学导航中,减少了状态量和观测量的耦合关系,避免了繁杂的矩阵运算,提高了状态估计的实时性。同时,改进了接近段轨道动力学模型,在一定程度上提高了模型精度;结合接近段轨道动力学模型,将一种改进的UD-EKF算法在光学导航中加以应用,并与传统的EKF滤波进行了比较,仿真结果优势明显。
最后,针对单一系统使用多种传感器这一特定问题进行研究,将信息融合滤波引入到自主光学导航系统中。为了减少运算负担、避免高维运算和大的空间存储,用UD分解优化信息融合滤波,提高了收敛速度。同时,引入状态方程的一阶泰勒展开式,分析了滤波周期对状态方程可观性的影响。通过仿真,验证了优化算法的有效性。
In the new century, hot topics in deep space exploration are rising,which are represented by exploration missions of big and small celestial bodies. The new high tide of technology research and plan execution for deep space exploration have arrived.The communication delay induced by the large distance of deep space exploration is a long time.The communication of spacecraft and telemeter and command station on the ground can not satisfy with the need of deep space mission now.So deep space exploration autonomous navigation technology will replace it and will become a regarded key technology in the deep exploration fields.
With the supports of Tenth Five-Year 863 Program (Autonomous Navigation Technology of Deep Spacecraft), this dissertation analyses the background and domestic and foreign situation of deep space exploration optical autonomous navigation. And the dissertation also studies the nonlinear filtering algorithms application in autonomous optical navigation technology.The main contents of this dissertation are as follows:
First, based on the analysis of massive correlative valuable reference, this dissertation introduces the significance、background and domestic and foreign situation.Combined with the task flow of deep space and autonomous optical navigation, this dissertation briefly analyses the principle of optical navigation.To the different stage of deep space exploration, it introduces the relative orbit dynamics equations. And different autonomous optical navigation methods are proposed too.At the same time, observation equations of deep space exploration are introduced.So the well-grounded base is established for the next research work of autonomous optical navigation nonlinear filtering algorithm.
Second, real-time performance is considered to be a main factor in deep space exploration fields. But large amount of data are more complex and time-consuming. At the same time, on-board computer’s data processing is limited. To deal with these problems, cylindrical coordinate system is used in heliocentric ecliptic coordinate system in this dissertation. And TSS-EKF algorithm is applied in optical autonomous navigation too. They reduce the coupling between the state variables and the observation variables. Complex matrix operations are avoided too. And state estimation velocity is improved in the end. At the same time, the paper improves the approach stage relative dynamic model. Accuracy of dynamic model is improved to a certain degree. Combined with the approach stage dynamic model, UD-EKF algorithm is applied to autonomous navigation system. It is compared to EKF algorithm in this dissertation. And simulation results are far better than before.
Finally, a particular problem is studied in the paper. That is many kinds of sensors used in the same system. The multisensor information fusion algorithm is introduced in optical autonomous navigation. To reduce the computational burden and to avoid the high-dimension computation and the large memory, the algorithm is improved by UD decomposition in this dissertation. So the convergence rate is improved. And besides, in order to analyze the impact of filter cycle on the observability of state equation, state equation’s first order Taylor expansion is introduced in this dissertation. Feasibility was proved by the computer simulation.
本学位论文结合“十五”863计划项目——“深空探测器自主导航技术”,分析了深空探测自主光学导航的背景及国内外发展现状,研究了一系列非线性滤波算法在自主光学导航技术中的应用。论文的主要内容包括:
首先,在综合分析大量有价值的参考文献的基础上,介绍了自主光学导航系统的研究意义、背景、国内外的发展现状;结合深空探测以及自主光学导航的任务流程,对光学导航原理进行简要分析;针对深空探测不同的任务阶段,介绍了相应的轨道动力学模型,并给出了各自的导航方案;对深空探测的观测模型建立过程进行了必要的说明,为下一步自主光学导航非线性滤波算法研究打下良好的基础。
其次,针对深空探测任务实时性要求较高,数据运算量大,而星载计算机运算能力有限的问题,在黄道坐标系中引入柱面坐标系,将TSS-EKF算法应用到自主光学导航中,减少了状态量和观测量的耦合关系,避免了繁杂的矩阵运算,提高了状态估计的实时性。同时,改进了接近段轨道动力学模型,在一定程度上提高了模型精度;结合接近段轨道动力学模型,将一种改进的UD-EKF算法在光学导航中加以应用,并与传统的EKF滤波进行了比较,仿真结果优势明显。
最后,针对单一系统使用多种传感器这一特定问题进行研究,将信息融合滤波引入到自主光学导航系统中。为了减少运算负担、避免高维运算和大的空间存储,用UD分解优化信息融合滤波,提高了收敛速度。同时,引入状态方程的一阶泰勒展开式,分析了滤波周期对状态方程可观性的影响。通过仿真,验证了优化算法的有效性。
In the new century, hot topics in deep space exploration are rising,which are represented by exploration missions of big and small celestial bodies. The new high tide of technology research and plan execution for deep space exploration have arrived.The communication delay induced by the large distance of deep space exploration is a long time.The communication of spacecraft and telemeter and command station on the ground can not satisfy with the need of deep space mission now.So deep space exploration autonomous navigation technology will replace it and will become a regarded key technology in the deep exploration fields.
With the supports of Tenth Five-Year 863 Program (Autonomous Navigation Technology of Deep Spacecraft), this dissertation analyses the background and domestic and foreign situation of deep space exploration optical autonomous navigation. And the dissertation also studies the nonlinear filtering algorithms application in autonomous optical navigation technology.The main contents of this dissertation are as follows:
First, based on the analysis of massive correlative valuable reference, this dissertation introduces the significance、background and domestic and foreign situation.Combined with the task flow of deep space and autonomous optical navigation, this dissertation briefly analyses the principle of optical navigation.To the different stage of deep space exploration, it introduces the relative orbit dynamics equations. And different autonomous optical navigation methods are proposed too.At the same time, observation equations of deep space exploration are introduced.So the well-grounded base is established for the next research work of autonomous optical navigation nonlinear filtering algorithm.
Second, real-time performance is considered to be a main factor in deep space exploration fields. But large amount of data are more complex and time-consuming. At the same time, on-board computer’s data processing is limited. To deal with these problems, cylindrical coordinate system is used in heliocentric ecliptic coordinate system in this dissertation. And TSS-EKF algorithm is applied in optical autonomous navigation too. They reduce the coupling between the state variables and the observation variables. Complex matrix operations are avoided too. And state estimation velocity is improved in the end. At the same time, the paper improves the approach stage relative dynamic model. Accuracy of dynamic model is improved to a certain degree. Combined with the approach stage dynamic model, UD-EKF algorithm is applied to autonomous navigation system. It is compared to EKF algorithm in this dissertation. And simulation results are far better than before.
Finally, a particular problem is studied in the paper. That is many kinds of sensors used in the same system. The multisensor information fusion algorithm is introduced in optical autonomous navigation. To reduce the computational burden and to avoid the high-dimension computation and the large memory, the algorithm is improved by UD decomposition in this dissertation. So the convergence rate is improved. And besides, in order to analyze the impact of filter cycle on the observability of state equation, state equation’s first order Taylor expansion is introduced in this dissertation. Feasibility was proved by the computer simulation.
引文
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[2] J. E. Riedel, S. Bhaskaran and S. P. Synnott et al. An Autonomous Optical Navigation and Control System for Interplanetary Exploration Missions. IAA Symposia and Scientific Meetings.1996.
[3] S.Mancuso. Vision Based GNC Systems for Planetary Exploration. ESAESTEC, Noord- wijk, The Netherlands. 2004, 1~10.
[4] Ferri, P. and Sorensen, E. Automated Mission Operations for Rosetta. Proceeding of the Fifth International Symposium on Space Mission Operations and Ground Data System. 1998.
[5] Barney Pell, Douglas E.Bernard, Steven A. Chien, Erann Gat, Nicola Muscettola, P. Pan- durang Nayak, Michael D.Wagner, and Brian C.Williams.An Autonomous Spacecraft Age- nt Prototype. Autonomous Robots. 1998, 5(1).
[6] Marc Sarrel. Cassini Science Operations and Planning Computer Design, Proceedings of SPIE, Denver, Colorado, USA. 1996, 222~223.
[7] S.C.LEE, A.G.SANTO. Reducing Mission Operations Costs through Spacecraft Autonomy. the Near Earth Asteroid Rendezvous (NEAR) Experience. Journal of Reducing Space Mission Cost. 1998, 1: 87~104,.
[8] A. B.索洛多夫.宇航技术工程手册.闵桂荣等.科学出版社, 1982, 282~290.
[9] Franzen M.A., Sears D.W.G.The HERA NEAR-EARTH ASTEROID SAMPLE RETURN MISSION: AN OVERVIEW. The Lunar and Planetary Science. 2003, 1032~1033.
[10] M. A. Chory, D. P. Hoffman and C. S. Major, et al. Autonomous Navigation—Where We Are in 1984. Proceedings of the AIAA Guidance and Navigation Symposium. 1984, 27~36
[11] W. L. James. Autonomous Navigation Systems Technology Assessment. Proceedings of the AIAA Guidance and Navigation Symposium. 1979, 1~12.
[12]潘科炎.航天器的自主导航技术.航天控制. 1994, 18~27.
[13]黄翔宇.探测器自主导航方法及在小天体探测中的应用研究.哈尔滨工业大学博士学位论文.
[14] S. Bhaskaran, D. Desai and P. J. Dumont et al. Orbit Determination Performance Evalua- tion of the Deep Space 1 Autonomous Navigation System. Proceedings of the AAS/AIAA Spaceflight Mechanics Meeting, Monterrey. 1998, 1295~1314.
[15]董云峰,章仁为.利用星敏感器的卫星自主导航.宇航学报. 1995, 16(4): 37~103.
[16]魏春玲,李勇,陈义庆.基于紫外敏感器的航天器自主导航.航天控制. 2004, 22(3): 35~39.
[17]韩潮,章仁为.利用雷达测高仪的卫星自主定轨.宇航学报. 1999, 20(3): 13~20.
[18]王淑一,杨旭等.近地卫星磁测自主导航算法研究.宇航学报. 2003, 24(6): 634~637.
[19]郭建新,解永春.基于姿态敏感器的地球同步轨道卫星自主导航研究.航天控制. 2003, 21(4): 1~6.
[20]黄翔宇,荆武兴.基于"日-地-月"信息的卫星自主导航技术研究.黑龙江.哈尔滨工业大学学报. 2002, 34(5): 643~646.
[21] T. Misu, T. Hashimto and K. Ninomiya. Optical Guidance for Autonomous Landing of Sp- acecraft. IEEE Transaction on Aerospace and Electronic Systems. 1999, 35(2): 459~473.
[22]袁健.深空探测器自主光学导航方案及非线性滤波算法研究.青岛.青岛科技大学硕士学位论文.
[23]邵巍.深空探测器自主光学导航研究.青岛科技大学硕士学位论文.
[24]刘宇飞.深空自主导航方法研究及在接近小天体中的应用.黑龙江.哈尔滨工业大学博士学位论文.
[25]邵巍.基于图像信息的小天体参数估计及探测器自主导航研究.黑龙江.哈尔滨工业大学博士学位论文.
[26] Veverka,J.,et al. The landing of the NEAR Shoemaker spacecraft on asteroid 433Eros, Nature. 2001, 1(413): 390~393.
[27]秦兴.基于“日-地-月”方位信息的卫星自主导航技术研究.黑龙江.哈尔滨工业大学硕士学位论文.
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