Comparison of Matrix Pencil Extracted Features in Time Domain and in Frequency Domain for Radar Target Classification

Mahmoud Khodjet-Kesba,Christophe Pasquier,Claire Faure,Khalil El Khamlichi Drissi,Sukhan Lee,Kamal Kerroum

doi:10.1155/2014/930581

Abstract

Feature extraction is a challenging problem in radar target identification. In this paper, we propose a new approach of feature extraction by using Matrix Pencil Method in Frequency Domain (MPMFD). The proposed method takes into account not only the magnitude of the signal, but also its phase, so that all the physical characteristics of the target will be considered. With this method, the separation between the early time and the late time is not necessary. The proposed method is compared to Matrix Pencil Method in Time Domain (MPMTD). The methods are applied on UWB backscattered signal from three canonical targets (thin wire, sphere, and cylinder). MPMFD is applied on a complex field (real and imaginary parts of the signal). To the best of our knowledge, this comparison and the reconstruction of the complex electromagnetic field by MPMFD have not been done before. We show the effect of the two extraction methods on the accuracy of three different classifiers: Naïve bayes (NB), K-Nearest Neighbor (K-NN), and Support Vector Machine (SVM). The results show that the accuracy of classification is better when using extracted features by MPMFD with SVM.

Highlights

In the last fifteen years, the interest in ultra wideband systems has grown rapidly
We propose a new approach of feature extraction by using Matrix Pencil Method in Frequency Domain (MPMFD)
We show the effect of the two extraction methods on the accuracy of three different classifiers: Naıve bayes (NB), K-Nearest Neighbor (K-NN), and Support Vector Machine (SVM)

Summary

Introduction

In the last fifteen years, the interest in ultra wideband systems has grown rapidly. One of several applications of the UWB is automatic target classification in intelligent vehicles. The UWB technique has the advantage to be used for localization, target identification, and communication between vehicles. The scope of this paper focuses on using UWB radar for automatic target classification. UWB radar uses very short duration pulses resulting in occupying a very wide band in frequency domain. This technique is defined by the Federal Communication Commission (FCC) as it possesses at least one of the following characteristics [1]:

Objectives

Methods

Results

Conclusion