Multiperson tracking with a network of ultrawideband radar sensors based on gaussian mixture PHD filters
Date
2015
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Abstract
In this paper, we investigate the use of Gaussian mixture probability hypothesis density filters for multiple person tracking using ultrawideband (UWB) radar sensors in an indoor environment. An experimental setup consisting of a network of UWB radar sensors and a computer is designed, and a new detection algorithm is proposed. The results of this experimental proof-of-concept study show that it is possible to accurately track multiple targets using a UWB radar sensor network in indoor environments based on the proposed approach. © 2014 IEEE.
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IEEE Sensors Journal
Publisher
Institute of Electrical and Electronics Engineers Inc.
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Keywords
Multiple person detection, PHD filter, Communication channels (information theory), Probability density function, Radar, Radar equipment, Sensor networks, Target tracking, Tracking radar, Ultra-wideband (UWB), Detection algorithm, Gaussian mixture phd, Gaussian mixture probability hypothesis density filters, Multi-person tracking, Person detection, PHD filters, Track multiple targets, Ultra wideband radars, Radar tracking
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Language
English