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Indoor human detection based on micro-Doppler features in the presence of interference from moving clutter sources by Jinlei Hou; Gao Chen; Qingfeng Zhou; Chanzi Liu; Xiangling Zuo; Yajuan Tang; Chi-Tsun Cheng is a Engineering article available to read on EtoBox.
What is Indoor human detection based on micro-Doppler features in the presence of interference from moving clutter sources about?
In this paper, to address the problem of detecting the presence of human in indoor environments in the presence of moving clutter sources, an indoor human detection method that utilizes random forest to process micro-Doppler signatures and a single pair of TX/RX unit is proposed. In contrast to most of the existing methods that use both distance information and micro-Doppler information assuming no interference from moving clutter sources (window curtains, blinds, table fans, etc.), our proposed method relies only on micro-Doppler information for human detection in indoor environments with curtain and fan interferences. Based on our time–frequency analyses on the measured radar data, seven features, i.e., the mean and standard deviation of the doppler centroid, the mean and standard deviation of the span of envelopes, the silhouette size, the positive peak values, and the peak spread, are extracted from spectrograms. These features are fed into a random forest classifier for categorizing the state of a room into one of the five scenarios considered in this work, namely (1) a person entering the room, (2) a person leaving the room, (3) interference from curtain/blind, (4) interferen
Who reads Indoor human detection based on micro-Doppler features in the presence of interference from moving clutter sources?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Jinlei Hou; Gao Chen; Qingfeng Zhou; Chanzi Liu; Xiangling Zuo; Yajuan Tang; Chi-Tsun Cheng
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Engineering (Physical Sciences)