基于小波神经网络的卡尔曼滤波在GPS/DR系统中的应用
Application of the Kalman Filter Based on Wavelet Neural Network in GPS/DR Navigation System
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摘要: 针对GPS/DR定位过程中采用卡尔曼滤波时噪声的统计特性与实际不符,提出采用小波神经网络嵌入到卡尔曼滤波,来实现自适应调整噪声协方差矩阵.通过对基于小波神经网络的自适应卡尔曼滤波辅助的GPS/DR定位系统进行仿真,结果表明既能有效抑制发散,又能有效提高定位精度.Abstract: GPS /DR positioning using Kalman filter has a large margin of error after a period of time, even divergent. This paper uses wavelet neural network in the Kalman filter to adjust the noise covariance matrix. Simulation results of mobile robot GPS/DR positioning system show that the divergence can effectively suppress, and can effectively improve the positioning accuracy.
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