Improved neural network information fusion in integrated navigation system

Lu Ding*, Lin Cai, Jia Bin Chen, Chun Lei Song

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

In order to overcome the limitation of single sensor in vehicle integrated navigation system, cascade fusion architecture is proposed to enhance the reliability of location information. Our research is focus on the algorithm in decision-making level of the fusion architecture, which is used to fuse the information from Global Positioning System (GPS), Kalman filter and Map Matching (MM) to get the precise location. The proposed algorithm in this paper utilizes Particle Swarm Optimizer (PSO) to substitute the traditional Back-Propagation (BP) algorithm in training parameters of neural net. It has more generalization capability. Besides that, it converges stably and is resistant to local optima compared with traditional BP. Test result shows that the proposed algorithm can improve location accuracy by making full use of all sensors' information, and it is robust and effective.

源语言英语
主期刊名Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007
2049-2053
页数5
DOI
出版状态已出版 - 2007
活动2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007 - Harbin, 中国
期限: 5 8月 20078 8月 2007

出版系列

姓名Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007

会议

会议2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007
国家/地区中国
Harbin
时期5/08/078/08/07

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