观测时滞离散系统卡尔曼滤波算法

Kalman Filtering Algorithm for Observing Time-delay Discrete Systems

由于观测时滞系统的观测方程不符合卡尔曼滤波算法的实现形式,导致传统卡尔曼滤波算法无法直接应用于观测时滞离散系统。为此,在借鉴系统状态增广方法的基础上,设计了一种将观测方程转换为无时滞观测方程的方法。同时根据卡尔曼滤波算法原理,针对变换后的无时滞系统模型方程,给出观测时滞卡尔曼滤波算法的步骤,并将此方法应用到实际非线性观测光电跟踪系统中,进行算法的性能对比。仿真实验结果证明:将时滞观测方程转换为无时滞观测方程的方法是可行的,可大幅度提高算法精度。

The observation equation of the observing time-delay system doesn't conform to the realization form of Kalman filtering algorithm,this results in Kalman filtering algorithm's incapability of being directly applied to observing the traditional time-delay discrete system. Basing on the method of augmented state,the way to convert observation equation to an equation without time delay was proposed. According to the principle of Kalman filtering algorithm and aiming at the model equation of non-delay system transformed,the steps of observing time-delay Kalman filtering algorithm were presented and applied to the nonlinear observation of electro-optical tracking system. Comparing and simulating the algorithms' performance show that converting the time-delay observation equation to the one without time-delay is feasible and it can greatly improve the algorithm accuracy.