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USING WAVELET ENTROPY TO DISTINGUISH BETWEEN HUMANS AND DOGS DETECTED BY UWB RADAR
Author(s) -
Yan Wang,
Xiao Yu,
Yang Zhang,
Hao Lv,
Teng Jiao,
G. Lu,
Wen Zhe Li,
Zhao Li,
Xijing Jing,
Jianqi Wang
Publication year - 2013
Publication title -
electromagnetic waves
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 89
eISSN - 1559-8985
pISSN - 1070-4698
DOI - 10.2528/pier13032508
Subject(s) - radar , entropy (arrow of time) , wavelet , ultra wideband , computer science , artificial intelligence , computer vision , pattern recognition (psychology) , physics , telecommunications , quantum mechanics
When using ultra-wide band (UWB) radar to detect targets in various conditions, identifying whether the target buried under building debris or in bad visibility conditions is a human or an animal is crucial. This paper presents the application of the wavelet entropy (WE) method to distinguish between humans and animal targets through brick wall and in free space at a certain distance. In the study, WE, WE change, and WE of the related range points were estimated for the echo signals from flve humans and flve dogs. Our flndings indicate that the entropy or degree of disorder in the energy distribution of the human target was much lower than that of the dog, and the waveform of the human's entropy was smoother than that of the dog. In addition, the body micro motions of humans are much more ordered than those of dogs. WE can be employed as a quantitative measure for recognizing invisible targets and may be a useful tool in the UWB radar's practical applications.

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