Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKF

The performance of MEMS-SINS/GPS integrated system degrades evidently during GPS outage due to the poor error characteristics of low-cost IMU sensors. The normal EKF is unable to estimate SINS error accurately after GPS outage owing to the large nonlinear error caused by MEMS-IMU. Aiming to solve th...

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Main Authors: Baiqiang Zhang, Hairong Chu, Tingting Sun, Hongguang Jia, Lihong Guo, Yue Zhang
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/239426
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spelling doaj-cb7c83766b30486c84f292a252e4dcb62020-11-24T23:25:26ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/239426239426Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKFBaiqiang Zhang0Hairong Chu1Tingting Sun2Hongguang Jia3Lihong Guo4Yue Zhang5Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, ChinaThe performance of MEMS-SINS/GPS integrated system degrades evidently during GPS outage due to the poor error characteristics of low-cost IMU sensors. The normal EKF is unable to estimate SINS error accurately after GPS outage owing to the large nonlinear error caused by MEMS-IMU. Aiming to solve this problem, a hybrid KF-UKF algorithm for real-time SINS/GPS integration is presented in this paper. The linear and nonlinear SINS error models are discussed, respectively. When GPS works well, we fuse SINS and GPS with KF with linear SINS error model using normal EKF. In the case of GPS outage, we implement Unscented Transform to predict SINS error covariance with nonlinear SINS error model until GPS signal recovers. In the simulation test that we designed, an evident accuracy improvement in attitude and velocity could be noticed compared to the normal EKF method after the GPS signal recovered.http://dx.doi.org/10.1155/2015/239426
collection DOAJ
language English
format Article
sources DOAJ
author Baiqiang Zhang
Hairong Chu
Tingting Sun
Hongguang Jia
Lihong Guo
Yue Zhang
spellingShingle Baiqiang Zhang
Hairong Chu
Tingting Sun
Hongguang Jia
Lihong Guo
Yue Zhang
Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKF
Mathematical Problems in Engineering
author_facet Baiqiang Zhang
Hairong Chu
Tingting Sun
Hongguang Jia
Lihong Guo
Yue Zhang
author_sort Baiqiang Zhang
title Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKF
title_short Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKF
title_full Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKF
title_fullStr Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKF
title_full_unstemmed Error Prediction for SINS/GPS after GPS Outage Based on Hybrid KF-UKF
title_sort error prediction for sins/gps after gps outage based on hybrid kf-ukf
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description The performance of MEMS-SINS/GPS integrated system degrades evidently during GPS outage due to the poor error characteristics of low-cost IMU sensors. The normal EKF is unable to estimate SINS error accurately after GPS outage owing to the large nonlinear error caused by MEMS-IMU. Aiming to solve this problem, a hybrid KF-UKF algorithm for real-time SINS/GPS integration is presented in this paper. The linear and nonlinear SINS error models are discussed, respectively. When GPS works well, we fuse SINS and GPS with KF with linear SINS error model using normal EKF. In the case of GPS outage, we implement Unscented Transform to predict SINS error covariance with nonlinear SINS error model until GPS signal recovers. In the simulation test that we designed, an evident accuracy improvement in attitude and velocity could be noticed compared to the normal EKF method after the GPS signal recovered.
url http://dx.doi.org/10.1155/2015/239426
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