Template free Micro Doppler Signature Classification for Wheeled and Tracked Vehicles
Author(s) -
Guanghu Jin,
Dong Zhen,
Yongsheng Zhang,
Feng He
Publication year - 2019
Publication title -
defence science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.198
H-Index - 32
eISSN - 0976-464X
pISSN - 0011-748X
DOI - 10.14429/dsj.69.12096
Subject(s) - doppler effect , signature (topology) , computer science , doppler radar , echo (communications protocol) , artificial intelligence , radar , computer vision , pattern recognition (psychology) , transformation (genetics) , hough transform , feature (linguistics) , feature extraction , mathematics , image (mathematics) , telecommunications , physics , computer network , biochemistry , geometry , chemistry , linguistics , philosophy , astronomy , gene
The micro-Doppler signature is a time-varying frequency modulation imparted on radar echo caused by target’s micro-motion. To save the trouble of constructing template in the target classification, this paper investigates the micro-Doppler signature of wheeled and tracked vehicles and proposes a template-free classification method. Firstly, the echo signature is established and the micro-Doppler difference of these two kinds of targets is analysed. Secondly, some new micro-Doppler features are defined according to their difference. The new defined features are micro-Doppler bandwidth, micro-Doppler expansion rate and micro-Doppler peak number. According to the characteristic of the micro-Doppler in the time-frequency domain, we proposed to realise the feature extraction by Hough transformation. Lastly, template-free subjection functions are proposed to define the relationship between the features and the vehicles. By fuzzy comprehensive evaluation, the final classification result is obtained by combining the subjection probabilities together. Experimental results based on the simulated data and measured data are presented, which prove that the algorithm has good performance.
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