Precision improvement methodology for INS/GPS after GPS outage using RB-UKF

ZHANG Bai-qiang; CHU Hai-rong; SUN Ting-ting; ZHANG Yue; JIA Hong-guang; GUO Li-hong

doi:10.3788/OPE.20162404.0835

您当前的位置：

首页 >

文章列表页 >

Precision improvement methodology for INS/GPS after GPS outage using RB-UKF

更新时间：2020-08-13

- Precision improvement methodology for INS/GPS after GPS outage using RB-UKF
- Optics and Precision Engineering Vol. 24, Issue 4, Pages: 835-843(2016)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院大学北京,中国,100049
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20162404.0835
  CLC： U666.1;V241.6
- Received：20 July 2015，
  
  Revised：27 August 2015，
  
  Published：25 April 2016
- 稿件说明：
移动端阅览
张百强, 储海荣, 孙婷婷等. 应用RB无迹卡尔曼滤波组合导航提高GPS重获信号后的导航精度[J]. 光学精密工程, 2016,24(4): 835-843

ZHANG Bai-qiang, CHU Hai-rong, SUN Ting-ting etc. Precision improvement methodology for INS/GPS after GPS outage using RB-UKF[J]. Editorial Office of Optics and Precision Engineering, 2016,24(4): 835-843
张百强, 储海荣, 孙婷婷等. 应用RB无迹卡尔曼滤波组合导航提高GPS重获信号后的导航精度[J]. 光学精密工程, 2016,24(4): 835-843 DOI： 10.3788/OPE.20162404.0835.

ZHANG Bai-qiang, CHU Hai-rong, SUN Ting-ting etc. Precision improvement methodology for INS/GPS after GPS outage using RB-UKF[J]. Editorial Office of Optics and Precision Engineering, 2016,24(4): 835-843 DOI： 10.3788/OPE.20162404.0835.

摘要

针对微机电-船舶惯性导航/全球定位(MEMS-SINS/GPS)组合导航系统在GPS信号中断时造成的强非线性误差及重获信号后精度变差的问题

设计了基于Rao-Blackwellised无迹卡尔曼滤波(RB-UKF)的组合导航算法。首先

基于捷联平台欧拉失准角定义了姿态误差

建立了捷联惯导系统的非线性误差传播方程。然后

针对组合导航的状态方程为非线性而量测方程呈线性的特点

设计了RB-UKF算法

在保证精度的同时降低了计算量。最后

设计了滤波算法总体结构

分别给出了GPS信号正常时和中断时组合导航滤波计算的流程。将提出的算法用于跑车实验

结果表明:在GPS失锁20 s和40 s再重获信号之后

使用RB-UKF算法的组合导航系统位置精度分别优于6 m和7.5 m

比扩展卡尔曼滤波(EKF)算法精度提高了1.5倍以上

误差收敛速度提高了1.88~16.5倍

计算量比UKF量测更新的计算量减小了41.7%。实验显示该方法显著提升了组合导航系统GPS信号中断再恢复后的滤波精度

且易于工程实现。

Abstract

A improved Rao-Blackwellised Unscented Kalman Filter(RB-UKF)algorithm fused by MEMS-SINS/GPS(Micro-Electrical-Mechanical System/Ship's Inertial Navigation/Global Positioning System) was established when the system has become strongly nonlinear after GPS outage. Firstly

the attitude misalignment was described based on the Euler platform error angle and the nonlinear error model for the SINS was set up. Then

as the state model was nonlinear while the observation model was linear

the RB-UKF algorithm was designed to ensure the accuracy of the UKF and to reduce its amount of computation. Finally

the algorithm structure was designed and its computing procedures when the GPS was in normal or in the period of outage were given. The algorithm was used in an in-car-experiment

and the results indicate that the SINS and GPS are fused by using the method proposed in this paper

the position error is less than 6 m or 7.5 m after 20 s and 40 s GPS outage respectively

which is 1.5 times better than that of Expand Kalman Filter(EKF) algorithm. Moreover

the error convergence time by RB-UKF is 1.88 to 16.5 times faster than that of the EKF

and the amount of computation of measurement update by RB-UKF algorithm is 41.7% smaller than that of the UKF. It concludes that the proposed method can effectively reduce the navigation errors after GPS outages for MEMS-SINS/GPS systems and has advantages in project implementation.

关键词

Keywords

references

YUKSEL Y, EL-SHEIMY N. Error modeling and characterization of environmental effects for low cost inertial MEMS units[C]. 2010 IEEE/ION Position Location and Navigation Symposium (PLANS), Indian Wells, 2010:598-612.

GROVES P D. Principles of GNSS, Inertial and Multisensor Integrated NavigationSystems[M]:Artech House, INC., 2008.

GODHA S, CANNON M E. GPS/MEMS INS integrated system for navigation in urban areas[J]. GPS Solutions, 2007, 11(3):193-203.

ILYAS M, YANG Y, QIAN Q S, et al.. Low-cost IMU/odometer/GPS integrated navigation aided with two antennae heading measurement for land vehicle application[C]. 25th IEEE Chinese Control and Decision Conference (CCDC), Guiyang, 2013:4521-4526.

CHEN L Z, FANG J C. A Hybrid Prediction Method for Bridging GPS Outages in High-Precision POS Application[J]. IEEE Transactions on Instrumentation and Measurement, 2014, 6(63):1656-1665.

崔留争, 高思远, 贾宏光, 等. 神经网络辅助卡尔曼滤波在组合导航中的应用[J]. 光学精密工程, 2014, 22(5):1304-1311. CUI L ZH, GAO S Y, JIA H G, et al.. Application of neural aided Kalman filtering to SINS/GPS[J]. Opt. Precision Eng., 2014, 22(5):1304-1311. (in Chinese)

CHEN X, SHEN C, ZHANG W, et al.. Novel hybrid of strong tracking Kalman filter and wavelet neural network for GPS/INS during GPS outages[J]. Measurement, 2013, 46(10):3847-3854.

BHATT D, AGGARWAL P, DEVABHAKTUNI V, et al.. A novel hybrid fusion algorithm to bridge the period of GPS outages using low-cost INS[J]. Expert Systems with Applications, 2014, 41(5):2166-2173.

JIANG Z, LIU C, ZHANG G, et al.. GPS/INS Integrated Navigation Based on UKF and Simulated Annealing Optimized SVM[C]. 78th. IEEE Vehicular Technology Conference (VTC Fall), Las Vegas, 2013:1-5.

严恭敏, 严卫生, 徐德民. 基于欧拉平台误差角的SINS非线性误差模型研究[J]. 西北工业大学学报, 2009, 27(4):511-516. YAN G M, YAN W S, XU D M. A SINS nonlinear error model reflecting better characteristics of SINS errors[J]. Journal of Northwestern Polytechnical University, 2009, 27(4):511-516. (in Chinese)

贾瑞才. 重力/地磁辅助的欧拉角无迹卡尔曼滤波姿态估计[J]. 光学精密工程, 2014, 22(12):3280-3286. JIA R C. Attitude estimation base on gravity/magnetic assisted Euler angle UKF[J]. Opt. Precision Eng., 2014, 22(4):3280-3286. (in Chinese)

马鹏斌, 宝音贺西, 沐俊山. 利用火星卫星光学测量实现火星探测器自主导航[J]. 光学精密工程, 2014, 22(4):863-869. MA P B, BAO Y H X, MU J S. Autonomous navigation of Mars probe based on optical observation of Martian moon[J]. Opt. Precision Eng., 2014, 22(4):863-869. (in Chinese)

HAO Y, XIONG Z, SUN F, et al.. Comparison of unscented Kalmanfilters[C]. Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation(ICMA), Harbin, 2007:895-899.

秦永元, 张洪钺, 王叔华. 卡尔曼滤波与组合导航原理(第2版)[M]. 西安:西北工业大学出版社, 2012. QIN Y Y, ZHANG H Y, WANG SH H. Theory of Kalman filter and integrated navigation(2nd Edition)[M]. Xi'an:North-western Polytechnical University Press, 2012. (in Chinese)

张召友. 非线性Bayesian滤波及其在SINS/GPS紧耦合导航中的应用研究[D]. 哈尔滨:哈尔滨工程大学, 2013. ZHANG ZH Y. Research on nonlinear Bayesian filtering and itsapplication for SINS/GPS tightly couplednavigation[D]. Harbin:Harbin Engineering University, 2013. (in Chinese)

Views

664

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Polarized light/MIMU integrated navigation SHKF attitude solving algorithm for motion acceleration suppression

Adaptive visual inertial geomagnetic tightly coupled positioning system

Multi-machine cooperative passive localization based on MEMS/GNSS

Fuzzy IAE-UKF integrated navigation method introducing system uncertainty

Effect of PBSs on nonlinearity in a homodyne interferometer

Related Author

ZHANG Ran

LIU Chen

ZHOU Zijian

PEI Sen

JIN Rencheng

WAN Zhenhua

FU Peng

WANG Kunfeng

Related Institution

Key Laboratory for Micro/Nano Technology and System of Liaoning Province ofDalian University of Technology

Faculty of Mechanical Engineering， Guangxi University

School of Instrument Science and Optoelectronic Engineering， Beijing Information Science and Technology University

Department of Precision Instrument， Tsinghua University

Space Vehicle Survival Technology and Effectiveness Evaluation Laboratory

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰