基于容积卡尔曼滤波的卫星导航定位解算方法

doi:10.7523/j.issn.2095-6134.2021.04.013

中国科学院大学学报 ›› 2021, Vol. 38 ›› Issue (4): 532-537.DOI: 10.7523/j.issn.2095-6134.2021.04.013

基于容积卡尔曼滤波的卫星导航定位解算方法

张杰, 李婧华, 胡超

中国科学院国家天文台, 北京 100101

收稿日期:2019-10-15 修回日期:2019-12-16 发布日期:2021-07-10
通讯作者: 张杰
基金资助:
国家重点研发计划项目（2016YFB0501903）资助

Solution method of satellite navigation positioning based on cubature Kalman filter

ZHANG Jie, LI Jinghua, HU Chao

National Astronomical Observatories of Chinese Academy of Sciences, Beijing 100101, China

Received:2019-10-15 Revised:2019-12-16 Published:2021-07-10

摘要/Abstract

摘要： 由于卫星导航定位方程组的非线性特性，传统的定位解算方法在解算之前需要对定位方程组进行线性化处理，会影响定位解算精度。容积卡尔曼滤波算法基于贝叶斯估计和容积变换，可以有效地提高非线性滤波估计的精度。将容积卡尔曼滤波算法应用于卫星导航定位解算，建立定位解算系统状态转移模型和测量模型，通过时间更新和测量更新两个环节递推估计接收机的三维位置坐标。利用IGS观测数据对基于容积卡尔曼滤波的定位解算方法进行验证，并与最小二乘法和扩展卡尔曼滤波算法进行对比，结果证明将容积卡尔曼滤波用于卫星导航定位解算可以获得更高的定位精度，并且具有较快的收敛速度。

关键词: 定位解算, 贝叶斯估计, 容积准则, 容积卡尔曼滤波, 最小二乘法, 扩展卡尔曼滤波

Abstract: Due to the nonlinear characteristics of satellite navigation positioning equations, the traditional positioning methods need to linearize the equations before solving, which would reduce the accuracy of positioning. Cubature Kalman filter (CKF) algorithm based on Bayesian estimation and cubature transformation could effectively improve the accuracy of nonlinear filtering estimation. In this paper, cubature Kalman filter algorithm is applied to satellite positioning solution. The transfer and measurement models of the positioning solution system are established. The three-dimensional position coordinates of the receiver are recursively solved by time update and measurement update. The positioning solution algorithm based on cubature Kalman filter is verified by IGS observation data tests, and compared with the least square method and extended Kalman filter algorithm. The results show that the application of CKF algorithm in satellite positioning is of higher precision and faster convergence speed.

Key words: positioning solution, Bayesian estimation, cubature rule, CKF, LSM, EKF

中图分类号:

TN965.8

张杰, 李婧华, 胡超. 基于容积卡尔曼滤波的卫星导航定位解算方法[J]. 中国科学院大学学报, 2021, 38(4): 532-537.

ZHANG Jie, LI Jinghua, HU Chao. Solution method of satellite navigation positioning based on cubature Kalman filter[J]. Journal of University of Chinese Academy of Sciences, 2021, 38(4): 532-537.

参考文献

[1] Kaplan E D, Hegarty C. Understanding GPS:principles and applications[M]. 2nd edition. Norwood:Artech House, 2006:322-332.
[2] 谢钢. GPS原理与接收机设计[M]. 北京:电子工业出版社, 2009:96-106.
[3] 秦永元, 张洪钺, 汪叔华. 卡尔曼滤波与组合导航原理[M]. 2版. 西安:西北工业大学出版社, 2012:1-3.
[4] Arasaratnam I, Haykin S. Cubature Kalman filters[J]. IEEE Transactions on Automatic Control, 2009, 54(6):1254-1269.
[5] 唐李军. Cubature卡尔曼滤波及其在导航中的应用研究[D]. 哈尔滨:哈尔滨工程大学, 2012.
[6] 杨峻巍. 水下航行器导航及数据融合技术研究[D]. 哈尔滨:哈尔滨工程大学, 2012.
[7] Havlicek M, Jan J, Brazdil M, et al. Nonlinear estimation of BOLD signal based on cubature particle filter[C]//The 20th Int EURASIP Conf on BIOSIGNAL 2010. Brno, 2010:328-332.
[8] Roy A, Mitra D. Multi-target trackers using cubature Kalman filter for Doppler radar tracking in clutter[J]. IET Signal Processing, 2016, 10(8):888-901.
[9] 葛磊. 容积卡尔曼滤波算法研究及其在导航中的应用[D]. 哈尔滨:哈尔滨工程大学, 2013.
[10] 王宏健, 李村, 么洪飞, 等. 基于高斯混合容积卡尔曼滤波的UUV自主导航定位算法[J]. 仪器仪表学报, 2015, 36(2):254-261.
[11] Pesonen H, Piché R. Cubature-based Kalman filters for positioning[C]//20107th Workshop on Positioning, Navigation and Communication (WPNC). Dresden, Germany:IEEE Press, 2010:45-49.
[12] Cui B B, Chen X Y, Tang X H. Improved cubature Kalman filter for GNSS/INS based on transformation of posterior sigma-points error[J]. IEEE Transactions on Signal Processing, 2017, 65(11):2975-2987.
[13] Ito K, Xiong K. Gaussian filters for nonlinear filtering problems[J]. IEEE Transactions on Automatic Control, 2000, 45(5):910-927.
[14] 陈杨毅. GPS与BD双模GNSS接收机定位解算技术研究[D]. 厦门:厦门大学, 2014.
[15] Gao C F, Wu F, Chen W R, et al. An improved weight stochastic model in GPS Precise Point Positioning[C]//International Conference on Proceedings Transportation, Mechanical, and Electrical Engineering(TMEE). 2011 Changchun, China:IEEE Press, 2011:629-632.
[16] 王慧, 王伟. 一种改进的卡尔曼滤波定位算法研究[J]. 船舶工程, 2006, 28(4):34-38.

基于容积卡尔曼滤波的卫星导航定位解算方法

Solution method of satellite navigation positioning based on cubature Kalman filter

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 4

编辑推荐

Metrics

本文评价

访问统计

联系我们

[1]	徐京萍;　张柏;　宋开山;　王宗明;　刘殿伟;　段洪涛. 用偏最小二乘法提取石头口门水库水色信息[J]. 中国科学院大学学报, 2007, 24(6): 814-849.
[2]	王源华. 非阿基米德局部域上的最小二乘法与最小距离和(英文)[J]. 中国科学院大学学报, 2004, 21(4): 447-450.
[3]	刘渭滨, 王书鸿, 黄楠, 顾鹏达. BEPCII LINAC束流轨道校正方法研究及程序设计[J]. 中国科学院大学学报, 2004, 21(3): 328-332.
[4]	叶五一, 缪柏其. 应用改进Hill估计计算在险价值[J]. 中国科学院大学学报, 2004, 21(3): 305-309.