1. An Algorithm Based Wavelet Entropy for Shadowing Effect of Human Detection Using Ultra-Wideband Bio-Radar
- Author
-
Huijun Xue, Miao Liu, Yang Zhang, Fulai Liang, Fugui Qi, Fuming Chen, Hao Lv, and Jianqi Wang
- Subjects
Computer science ,0211 other engineering and technologies ,Ultra-wideband ,02 engineering and technology ,lcsh:Chemical technology ,Biochemistry ,Article ,Analytical Chemistry ,law.invention ,Radar engineering details ,law ,multiple target detection ,0202 electrical engineering, electronic engineering, information engineering ,Entropy (information theory) ,wavelet entropy ,lcsh:TP1-1185 ,Electrical and Electronic Engineering ,Radar ,Instrumentation ,021101 geological & geomatics engineering ,020206 networking & telecommunications ,Wavelet entropy ,ultra-wide band (UWB) ,Atomic and Molecular Physics, and Optics ,Continuous-wave radar ,Adaptive filter ,Bistatic radar ,Algorithm - Abstract
Ultra-wide band (UWB) radar for short-range human target detection is widely used to find and locate survivors in some rescue missions after a disaster. The results of the application of bistatic UWB radar for detecting multi-stationary human targets have shown that human targets close to the radar antennas are very often visible, while those farther from radar antennas are detected with less reliability. In this paper, on account of the significant difference of frequency content between the echo signal of the human target and that of noise in the shadowing region, an algorithm based on wavelet entropy is proposed to detect multiple targets. Our findings indicate that the entropy value of human targets was much lower than that of noise. Compared with the method of adaptive filtering and the energy spectrum, wavelet entropy can accurately detect the person farther from the radar antennas, and it can be employed as a useful tool in detecting multiple targets by bistatic UWB radar.
- Published
- 2017