A IMPROVED TRACKING KALMAN FILTER USING MULTILAYER NEURAL NETWORK
多层神经网络在跟踪式卡尔曼滤波器中的应用

This paper presents a method to improve the estimation accuracy of a tracking Kalman filter (TKF)by using a multilayer neural network(MNN). The estimation accuracy of the TKF is degraded due to the uncertainties that cannot be expressed by the linear state-space model proposed in the literature. This fault is overcome due to the use of MNN. The results of the TKF can be modified by the treated MNN. Simulation results show that the estimation accuracy is much improved by using the MNN.