Application of Improved BP Neural Network in Information Fusion Kalman Filter

被引：0
作者：
Yu-Hang Yang
Ying Shi
机构：
[1] Heilongjiang University,Electronic Engineering College
[2] Key Laboratory of Information Fusion Estimation and Detection,undefined
[3] Heilongjiang Province,undefined
来源：
Circuits, Systems, and Signal Processing | 2020年 / 39卷
关键词：
BP neural network; Particle swarm optimization; Kalman filter; Information fusion;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Based on improved back propagation (BP) neural network, information fusion state estimation problem for multi-sensor system is considered. Firstly, particle swarm optimization, search dynamic learning rate and additional momentum method are introduced to train the initial weights and thresholds of BP neural network. Then, the improved neural network is used to optimize the estimated value of Kalman filter. Finally, the sate estimators are fused by weighting matrices. A simulation example verifies the effectiveness of the proposed algorithm.
引用
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页码：4890 / 4902
页数：12
相关论文
共 47 条
[1]  
Chai L(2005)Neural-network-aided information fusion for integrated navigation application J. Northwest. Polytech. Univ. 23 45-48
[2]  
Yuan JP(2019)Hidden Markov model-based nonfragile state estimation of switched neural network with probabilistic quantized outputs IEEE Trans. Cybern. 16 715-719
[3]  
Fang Q(1995)Neural network-based information fusion and parallel adaptive tracking of maneuvering targets Acta Aeronaut. Astron. Sin. 70 350-357
[4]  
Huang LW(2016)Understanding the ensemble Kalman filter Am. Stat. 24 970-977
[5]  
Cheng J(2016)Cooperative fusion model based on Kalman-BP neural network for suspended sediment concentration measurement J. Basic Sci. Eng. 20 6494-6497
[6]  
Park JH(2008)Initial alignment method based on Kalman/UKF integrated training neural network J. Syst. Simul. 2 1-7
[7]  
Cao JD(2018)Application of federal Kalman filter with neural networks in the velocity and attitude matching of transfer alignment Complexity 40 1017-1023
[8]  
Qi WH(2004)Multi-sensor optimal information fusion Kalman filter Automatica 162 1399-1409
[9]  
Jing ZL(2016)A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique Appl. Energy 36 49-51
[10]  
Xu H(2011)An adaptive Kalman tracking filter with colored noises Fire Control Command Control 190 390-407
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