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为了解决标准Kalman滤波法不能很好处理大坝变形观测粗差与状态方程异常的问题,提出了采用基于M估计的抗差Kalman滤波算法,在最小二乘准则的基础上,通过调整观测值对状态估计的比例权重,可得到模型参数的稳健估计,给出了其滤波准则及递推公式,并根据预测残差调节增益矩阵的大小,尽可能地削弱监测噪声和动态噪声里粗差的影响,让系统处于比较稳定的状态。实例应用结果表明,该算法不仅可提高滤波精度,且能很好地控制观测异常和动态扰动异常对监测的影响。
In order to solve the problem that the standard Kalman filter method can not handle well the dam deformation observation and the equation of state anomaly, a robust Kalman filter algorithm based on M estimation is proposed. Based on the least square criterion, The robust estimation of the model parameters is obtained, the filtering criterion and recursion formula are given, and the influence of the error in the monitoring noise and dynamic noise is reduced as much as possible according to the size of the gain matrix. , Let the system in a more stable state. The practical application shows that this algorithm can not only improve the filtering accuracy, but also control the influence of abnormal observation and dynamic disturbance on monitoring.