Affine Projection Algorithm With Outlier Detection for Robust Filtering

In this paper, a new adaptive filtering algorithm called affine projection robust outlier detection algorithm (APRODA) that combines affine projection (AP) method and outlier detection is proposed. The convergence speed of traditional AP-type algorithms is easily affected by impulsive noise. APRODA enhances impulsive noise resistance by removing the outliers generated by impulsive noise. Also, a new step-size adjustment method is proposed. This method greatly reduces the computational complexity of the traditional step-size adjustment method by switching the step-size through the detection of steady state and mutation. Combined with APRODA, switched-APRODA is proposed. Several simulation experiments show that the proposed algorithms are significantly preferable to other AP-type algorithms in terms of convergence speed and tracking ability for system identification.