A Simple Method to Stop an Adaptive Process for the Multistage Wiener Filter

The multistage Wiener filter (MWF) outperforms the full rank Wiener filter in low sample support environments. However, the MWF adaptive process should be stopped at an optimum stage to get the best performance. There are two methods to stop the MWF adaptive process. One method is to calculate until the final full-stage, and the second method is to terminate at r-stage less than full-stage. The computational load is smaller in the latter method, however, a performance degradation is caused by an additional or subtractive stage calculation. Therefore, it is very important for the r-stage calculation to stop an adaptive process at the optimum stage. In this paper, we propose a simple method based on a cross-correlation coefficient to stop the MWF adaptive process. Because its coefficient is calculated by the MWF forward recursion, the optimum stage is determined automatically and additional calculations are avoided. The performance was evaluated by simulation examples, demonstrating the superiority of the proposed method. key words: reduced rank, multistage Wiener filter, optimum stage, stopping criterion