带未知时变噪声的非线性系统卡尔曼滤波器算法研究
A Kalman Filter Algorithm for Nonlinear System with Unknown Time-varying Noise
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摘要: 针对带有未知时变噪声的非线性系统的状态估计问题,详细研究了基于有限差分和未知时变噪声估计器的扩展Kalman滤波器算法。仿真结果发现,该算法具有滤波精度高,数值计算稳定等优点,但系统状态估计对初始误差较敏感。Abstract: A kind of noise statistics estimator based on finite difference Kalman filter algorithm, which has been presented for the nonlinear systems with unknown time varying noise, is considered in detail. Simulation results show that the algorithm has high precision and numerical stability, but the estimated states are sensitive to the initial error.