Parameter order selection of autoregressive model for classification of ground surveillance radar targets

Abstract

In this research the order selection of autoregressive model parameters for classification of signals from the ground surveillance radar audio-output is considered. For this purpose, a measure based on maximal separability between used radar classes (clutter, person walking, person running, group of persons walking, group of persons running, vehicle) is suggested. Determined order of the autoregressive model is compared to the information criterion proposed by Akaike for different used windows. After the feature reduction of used real radar Doppler echo signals, it is showed that the proposed measure determines as optimal significantly lower order with a higher separability between used classes of radar targets