电子与控制

一种基于NGA-QPF的航天器姿态估计方法

  • 李海君 ,
  • 赵国荣 ,
  • 黄婧丽 ,
  • 周大旺
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  • 海军航空工程学院 控制工程系, 山东 烟台 264001
李海君男,博士研究生,工程师。主要研究方向:导航制导与控制。Tel:0535-6635636 E-mail:16529531@qq.com;赵国荣男,博士,教授,博士生导师。主要研究方向:导航制导与控制。 E-mail:GRZhao@163.com;黄婧丽女,博士研究生,助理工程师。主要研究方向:导航制导与控制。 E-mail:huangjingli_hy@163.com;周大旺男,博士研究生,助理工程师。主要研究方向:导航制导与控制。 E-mail:zhoudawang10@163.com

收稿日期: 2013-09-04

  修回日期: 2013-11-04

  网络出版日期: 2013-11-20

基金资助

部级项目

A Spacecraft Attitude Estimation Method Based on NGA-QPF

  • LI Haijun ,
  • ZHAO Guorong ,
  • HUANG Jingli ,
  • ZHOU Dawang
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  • Department of Control Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China

Received date: 2013-09-04

  Revised date: 2013-11-04

  Online published: 2013-11-20

Supported by

Ministry Level Project

摘要

针对航天器姿态确定中的非线性非高斯的滤波问题,提出一种基于遗传算法的粒子滤波的航天器姿态估计方法。该方法将姿态四元数作为采样粒子进行粒子滤波,并将小生境遗传算法(NGA)引入粒子滤波算法中,以改善粒子滤波的性能;用遗传算法单独进行陀螺偏差估计,以减少粒子滤波的状态维数。该姿态估计方法保持了四元数的归一化性质,通过引入小生境遗传算法解决了重采样阶段的粒子退化问题,并且由于单独估计陀螺偏差避免了粒子滤波状态的扩展。该方法能够在较少粒子的情况下实现高效率高精度的定姿,仿真结果说明了方法的有效性。

本文引用格式

李海君 , 赵国荣 , 黄婧丽 , 周大旺 . 一种基于NGA-QPF的航天器姿态估计方法[J]. 航空学报, 2014 , 35(6) : 1694 -1702 . DOI: 10.7527/S1000-6893.2013.0458

Abstract

A spacecraft attitude estimation method of particle filters based on the genetic algorithm is proposed to solve nonlinear non-Gaussian filtering problems in attitude determination. In this method, the attitude quaternion is used as sampling particles for the particle filter and the niche genetic algorithm (NGA) is introduced into the particle filter algorithm in order to improve its performance. At the same time, gyro bias is estimated by the genetic algorithm separately to reduce the state dimension of the particle filter. This method not only maintains the properties of the normalized quaternion but also solves the particle degradation problem in the resampling stage by introducing the NGA. And as gyro bias is estimated separately, the expansion of the state dimension is avoided. The method can achieve attitude determination with high efficiency and precision for the case of relatively few particles. Simulation results show the validity of the method.

参考文献

[1] Stoll E, Letschnik J, Walter U, et al. On-orbit servicing[J]. IEEE Robotics and Automation Magazine, 2009, 16(4): 29-33.
[2] Abdelrahman M, Park S Y. Sigma-point Kalman filtering for spacecraft attitude and rate estimation using magnetometer measurements[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(2): 1401-1415.
[3] Lefferts E J, Markley F L, Shuster M D. Kalman filtering for spacecraft attitude estimation[J]. Journal of Guidance, Control, and Dynamics, 1982, 5(5): 417-429.
[4] Crassidis J L, Markley F L. Unscented filtering for spacecraft attitude estimation[J]. Journal of Guidance, Control, and Dynamics, 2003, 26(4): 536-542.
[5] Wei X Q, Song S M. Improved cubature Kalman filter based attitude estimation avoiding singularity[J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(3): 610-619. (in Chinese) 魏喜庆, 宋申民. 基于改进容积卡尔曼滤波的奇异避免姿态估计[J]. 航空学报, 2013, 34(3): 610-619.
[6] Zhang J, Sun Z W. Satellite attitude determination based on particle filter[J]. Journal of Harbin Institute of Technology, 2012, 44(11): 31-35. (in Chinese) 张健, 孙兆伟. 粒子滤波在卫星姿态确定中的应用[J].哈尔滨工业大学学报, 2012, 44(11): 31-35.
[7] Bar-Itzhack I Y, Oshman Y. Attitude determination from vector observations: quaternion estimation[J]. IEEE Transactions on Aerospace and Electronic Systems, 1985, 21(1): 128-136.
[8] Psiaki M L. Attitude determination filtering via extended quaternion estimation[J]. Journal of Guidance, Control, and Dynamics, 2000, 23(2): 210-214.
[9] Kasdin N J. Satellite quaternion estimation from vector measurements with the two-step optimal estimator//AAS Guidance and Control Conference, 2002.
[10] Cheng J Z, Yuan J P, Fang Q. Attitude estimation algorithm based on Rodrigues parameter[J]. Acta Aeronautica et Astronautica Sinica, 2008, 29(4): 960-965. (in Chinese) 陈记争, 袁建平, 方群. 基于Rodrigues参数的姿态估计算法[J]. 航空学报, 2008, 29(4): 960-965.
[11] Higuchi T. Monte Carlo filter using the genetic algorithm operators[J]. Journal of Statistical Computation and Simulation, 1997, 50(1): 1-23.
[12] Park S, Hwang J, Rou K, et a1. A new particle filter inspired by biological evolution: genetic filter[J]. International Journal of Applied Science Engineering and Technology, 2007, 4(1): 459-463.
[13] Li C Y, Ji H B. A new particle filter with GA-MCMC resampling//Proceedings of International Conference on Wavelet Analysis and Pattern Recognition. Piscataway: IEEE, 2007: 146-150.
[14] Holland J H. Adaptation in natural and artificial systems[M]. Ann Arbor: University of Michigan Press, 1975: 27-30.
[15] Newman P M. On the structure and solution of the simultaneous localization and map building problem. New South Wales: University of Sydney, 1999.
[16] Feder H J S, Leonard J J, Smith C M. Adaptive mobile robot navigation and mapping[J]. International Journal of Robotics Research, 1999, 18(7): 650-668.
[17] Liu Y, Sun F C, Tao T, et al. A solution to active simultaneous localization and mapping problem based on optimal control//Proceeding of IEEE International Conference on Mechatronics and Automation, 2007: 314-319.
[18] Khatib O. Real time obstacle avoidance for manipulators and mobile robots[J]. International Journal of Robotics Research, 1986, 5(1): 90-99.
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