Micro-Doppler based target classification in ground surveillance radar systems

被引:21
|
作者
Amiri, Reza [1 ]
Shahzadi, Ali [2 ]
机构
[1] Islamic Azad Univ, Tech & Engn Fac, South Tehran Branch, Tehran, Iran
[2] Semnan Univ, Tech & Engn Fac, Semnan, Iran
关键词
Automatic Target Recognition (ATR); General Linear Chirplet Transform (GLCT); Moving Target Detector (MTD); Radar Target Classification; Short Time Fourier Transform (STFT); INSTANTANEOUS FREQUENCY ESTIMATION; RECOGNITION; MODEL;
D O I
10.1016/j.dsp.2020.102702
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we investigate effect of different Time-Frequency (TF) analysis of micro-Doppler signature for robust and efficient automatic target classification in next-generation radar systems. Indeed, we provide a novel mathematical baseband model for the non-stationary reflected signal of the targets and explore how Short Time Fourier Transform (STFT) and General Linear Chirplet Transform (GLCT) are useful in categorization of different ground moving targets, including walking person, animal, light vehicles and drone. To simulate the micro-Doppler signature, we will introduce a simple, but sufficiently realistic signal model. Simulation and results which are provided for various scenarios, illustrate the importance of appropriate TF representation in target classification. (C) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页数:9
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