Novel hybrid of strong tracking Kalman filter and wavelet neural network for GPS/INS during GPS outages
Novel hybrid of strong tracking Kalman filter and wavelet neural network for GPS/INS during GPS outages
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DOI：
10.1016/j.measurement.2013.07.016
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发表时间：
2013-12-01
期刊：
影响因子：
5.6
通讯作者：
Chiu, Kuanlin
中科院分区：
文献类型：
--
作者：
Chen, Xiyuan;Shen, Chong;Chiu, Kuanlin
为了提高GPS中断时GPS/INS组合导航系统的定位精度，提出并测试了一种结合强跟踪卡尔曼滤波器（STKF）和小波神经网络（WNN）算法的INS误差补偿模型。 STKF用于估计INS误差，替代卡尔曼滤波器（KF），WNN用于在GPS正常工作时基于STKF建立高精度模型，并在GPS中断时预测INS误差。使用陆地车辆导航测试中收集的 GPS 和 INS 数据对所提出模型的性能进行了实验验证。对比结果表明，所提出的模型结合STKF/WNN算法可以在GPS中断期间有效地为独立INS提供高精度修正。 (C) 2013 Elsevier Ltd. 保留所有权利。
Aiming to improve positioning precision of the GPS/INS integrated navigation system during GPS outages, a novel model combined with strong tracking Kalman filter (STKF) and wavelet neural network (WNN) algorithms for INS errors compensation is proposed and tested. STKF is used to estimate INS errors as a replacement of Kalman filter (KF), and WNN is applied to establish a highly accurate model based on STKF when GPS works well and to predict INS errors during GPS outages. Performance of the proposed model has been experimentally verified using GPS and INS data collected in a land vehicle navigation test. The comparison results indicate that the proposed model combined with STKF/WNN algorithms can effectively provide high accurate corrections to the standalone INS during GPS outages. (C) 2013 Elsevier Ltd. All rights reserved.