MODEL: moving object detection and localization in wireless networks based on small-scale fading

Authors:
Qingming Yao;Hui Gao;Bin Liu;Fei-Yue Wang
Affiliations:
Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
Proceedings of the 6th ACM conference on Embedded network sensor systems
Year:
2008

Citing 2
Cited 1

Wireless Communications: Principles and Practice

Wireless Communications: Principles and Practice
Challenges: device-free passive localization for wireless environments

Proceedings of the 13th annual ACM international conference on Mobile computing and networking

A ZigBee indoor security system based on small-scale fading

INSS'09 Proceedings of the 6th international conference on Networked sensing systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a new Moving Object Detection and Localization (MODEL) system, which is based on the smallscale fading of RF signal strength and independent from the salient characteristics of both the device and the sensor. We first validated the feasibility of applying small-scale fading effects to moving object detection and localization through experimental analysis. Then, we introduced MODEL: an embedded network system which adopts an easily-realized Rolling-Window algorithm. We applied the Region-Partition method to determine the position of the moving object, and concluded that the precision of the object position is dependant upon the density of participating nodes. MODEL is also scalable to other wireless network infrastructures and adaptable to various environments without the need for complex and time consuming training.