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Research on adaptive Kalman filter algorithm based on fuzzy neural network

机译:基于模糊神经网络的自适应卡尔曼滤波算法研究

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When the plant of an integrated SINS/GPS navigation system dynamics or noise processes are not exactly known, or the noise processes are not zero mean white noise, divergence problems will occur. In this paper, a based on intelligent information fusion technology -fuzzy neural network adaptive system is used to adjust the exponential weighting of a weighted Kalman filtering and prevent it from divergence. The simulation results show that in the case of gradually increasing noise statistics, the fuzzy neural network adaptive algorithm is robust and has high accuracy.
机译:当综合SINS / GPS导航系统动力学或噪声过程的工厂并不恰恰知道,或者噪声过程不是零的平均白噪声,将发生发散问题。本文基于智能信息融合技术 - 可用于调整加权卡尔曼滤波的指数加权并防止其发散。仿真结果表明,在逐渐增加噪声统计的情况下,模糊神经网络自适应算法具有稳健性并且具有高精度。

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