基于奇异值分解的多通道带乘性噪声系统的最优滤波算法

提出 1种基于奇异值分解 (SVD)的多通道带乘性噪声系统的最优滤波方法。该方法基于多通道带乘性噪声系统的最优滤波理论1] ,利用奇异值分解作为工具 ,将原算法中的协方差矩阵P进行奇异值分解 ,可以在一定程度上避免在递推过程中 ,由于计算误差和舍入误差的积累而引起的协方差矩阵P失去对称性 ,因而导致算法失效的问题。在保证算法在线性最小方差意义下为最优的同时 ,具有很好的数值稳定性和鲁棒性。仿真中对改进后算法和原算法估计效果做了对比 ,仿真结果证明了本文方法的有效性。

A SVD-Based Optimal Filtering for Multi-Channel Systems with Multiplicative Noise

In this paper,an optimal filtering method based on the Singular Value Decomposition (SVD)technique for Multi-Channel Systems with Multiplicative Noise is proposed. This method is based on the theory of Optimal Filtering for Multi-Channel Systems with Multiplicative Noise, and uses SVD technique as a tool to decompose the covariance matrix P in the original method. The new method succeeds in avoiding the invalidation caused by errors during computation. It is optimal in the sense of linear minimum-variance and has excellent numerical stability. A typical numerical example is used to demonstrate the performance of the method.