Performance assisted enhancement based on change point detection and Kalman filtering

Performance assisted enhancement based on change point detection and Kalman filtering

A performance assisted enhancement Kalman filtering algorithm （PAE-KF） for GPS/INS integration navigation in urban areas was presented in this work. The aim of this PAE-KF algorithm was to prevent ＂deep contamination＂ caused by error GPS data. This filtering algorithm effectively combined fault esti...

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Veröffentlicht in:Journal of Central South University 2013-12, Vol.20 (12), p.3528-3535
1. Verfasser: 任孝平 王健 薛志超 谷明琴
Format: Artikel
Sprache:eng
Schlagworte:
Engineering
GPS信号
GPS数据
Metallic Materials
卡尔曼滤波算法
基础
性能
故障估计
检测
非完整约束
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container_issue 12
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container_title Journal of Central South University
container_volume 20
creator 任孝平 王健 薛志超 谷明琴
description A performance assisted enhancement Kalman filtering algorithm （PAE-KF） for GPS/INS integration navigation in urban areas was presented in this work. The aim of this PAE-KF algorithm was to prevent ＂deep contamination＂ caused by error GPS data. This filtering algorithm effectively combined fault estimation of raw GPS data and nonholonomic constraint of vehicle. In fault estimation, a change point detection algorithm based on abrupt change model was proposed. Statistical tool was then used to infer the future bound of GPS data, which can detect faults in GPS raw data. If any kinds of faults were detected, dead reckoning mechanism begins to compute current position. Nonholonomic constraint condition of vehicle was used to estimate velocity of vehicle and change point detection was added into classic Kalman filtering structure. Experiment on vehicle shows that even when the GPS signals are unavailable for a period of time, this method can also output high accuracy data.
doi_str_mv 10.1007/s11771-013-1878-z
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subjects Engineering
GPS信号
GPS数据
Metallic Materials
卡尔曼滤波算法
基础
性能
故障估计
检测
非完整约束
title Performance assisted enhancement based on change point detection and Kalman filtering
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