A Novel BPNN-Based Method to Overcome the GPS Outages for INS/GPS System

被引:43
|
作者
Wang, Guangcai [1 ,2 ]
Xu, Xiaosu [1 ,2 ]
Yao, Yiqing [1 ,2 ]
Tong, Jinwu [1 ,2 ]
机构
[1] Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China
[2] Southeast Univ, Key Lab Microinertial Instrument & Adv Nav Techno, Nanjing 210096, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
INS/GPS integrated system; BP neural network; global positioning system (GPS) outages; KALMAN FILTER; STRONG TRACKING; GPS/INS; HYBRID; INTEGRATION; NAVIGATION;
D O I
10.1109/ACCESS.2019.2922212
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to improve the performance of the global positioning system (GPS) and inertial navigation system (INS) integrated system during GPS outages, a novel fusion algorithm based on back propagation neural network (BPNN) is proposed. A new model is built which relates the INS velocity, inertial measurement unit (IMU) outputs and the duration of GPS outages to the GPS position increment. Performance of the proposed method has been experimentally evaluated in a land vehicle navigation test. The test results show: (1) the proposed model can efficiently predict the increment of position and compensate the INS errors accumulation during GPS outage; (2) the advantage of new model on positioning accuracy becomes more obvious when the GPS observations are unavailable for a long time; (3) utilizing the current and past 2-step information as the input of BPNN model can effectively balance the computation burden and accuracy.
引用
收藏
页码:82134 / 82143
页数:10
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