Anderson-Darling test for ground radar environment sensing

Abstract

A clutter distribution identification method based on the AD (Anderson-Darling) goodness-of-fit test is proposed for the environmental perception and clutter distribution identification of ground radar positions, given the current demand for environment perception by position adaptive technology. The method determines which distribution the clutter obeys by comparing the critical value of the corresponding distribution with the AD statistic. The AD test method is improved by proposing a cell averaging method and a critical value unitisation method to address the problem that the AD parameters of the parameters in ground radar echo sample data fluctuate greatly, and the sample data are accepted by multiple distributions. The measured ground radar echo data was recorded and used for identification. The analysis results show that the improved AD test identification method has a better identification effect in the identification of ground radar’s position environment clutter distribution.

An Improved Segmented MTI Filter Based on a Clustering Algorithm

“…This topic hopes to use the K-Means clustering algorithm to divide the echo data into different clutter distance segments based on the existing ground radar position environment sensing [6], [7] and carry out targeted MTI filter design for each distance segment separately to achieve better clutter suppression effect.…”