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...
Main Authors: | , , , , , |
---|---|
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 |
id |
doaj-cb7c83766b30486c84f292a252e4dcb6 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT baiqiangzhang errorpredictionforsinsgpsaftergpsoutagebasedonhybridkfukf AT hairongchu errorpredictionforsinsgpsaftergpsoutagebasedonhybridkfukf AT tingtingsun errorpredictionforsinsgpsaftergpsoutagebasedonhybridkfukf AT hongguangjia errorpredictionforsinsgpsaftergpsoutagebasedonhybridkfukf AT lihongguo errorpredictionforsinsgpsaftergpsoutagebasedonhybridkfukf AT yuezhang errorpredictionforsinsgpsaftergpsoutagebasedonhybridkfukf |
_version_ |
1725557568011501568 |