An Improved Segmented MTI Filter Based on a Clustering Algorithm

Abstract

A K-Means clustering algorithm modified MTI (Moving Target Indication) filter is proposed for refining signal processing of the array environment in response to the current demand for clutter suppression by array adaptive technology. The method first uses the clutter distribution type and distance as parameters of the K-Means clustering algorithm to divide the echo’s into different clutter distance segments. Then an adaptive MTI filter is used to filter each clutter distance segment separately. The identification was carried out using measured ground radar echo data. The results show that the k-means clustering algorithm has better clutter distance segmentation capability. Compared with the conventional two-pulse MTI filter, the improved segmented MTI filter of the k-means algorithm has better clutter suppression in complex clutter environments.