A IMPROVED TRACKING KALMAN FILTER USING MULTILAYER NEURAL NETWORK

Han Minghua; Yuan Naichang

Volume 20 Issue 6

Nov. 1998

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Article Navigation > Journal of Electronics & Information Technology > 1998 > 20(6): 739-744

Han Minghua, Yuan Naichang. A IMPROVED TRACKING KALMAN FILTER USING MULTILAYER NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1998, 20(6): 739-744.

Citation:

Han Minghua, Yuan Naichang. A IMPROVED TRACKING KALMAN FILTER USING MULTILAYER NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1998, 20(6): 739-744.

Han Minghua, Yuan Naichang. A IMPROVED TRACKING KALMAN FILTER USING MULTILAYER NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1998, 20(6): 739-744.

Citation:

Han Minghua, Yuan Naichang. A IMPROVED TRACKING KALMAN FILTER USING MULTILAYER NEURAL NETWORK[J]. Journal of Electronics & Information Technology, 1998, 20(6): 739-744.

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A IMPROVED TRACKING KALMAN FILTER USING MULTILAYER NEURAL NETWORK

Received Date: 1997-01-15
Rev Recd Date: 1998-02-23
Publish Date: 1998-11-19

Abstract

Abstract

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.

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References

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