A real-time device-free localization system using correlated RSS measurements

Zhiyong Yang,Xuemei Guo,Guoli Wang,Kaide Huang

doi:10.1186/1687-1499-2013-186

Abstract

Abstract Device-free localization (DFL) with wireless sensor networks (WSN) is an emerging technology for target localization, which has received much attention in the area of Internet of Things. Received signal strength (RSS) measurements are the key to realize DFL and mainly affects the localization performance. Most existing approaches need to measure the RSS of all the wireless links in WSN, which take much time on measurement process and localization algorithm due to the large amounts of RSS data, thus they are inefficient, especially in the case of target tracking. In this paper, by making full use of the consecutiveness of motion, we present an efficient measurement strategy based on a small set of correlated wireless links. Furthermore, a lightweight compressed maximum matching select (CMMS) algorithm is proposed to localize target, which only needs a small-scale matrix-vector product operating for one estimation. The proposed approach can significantly reduce the number of RSS measurements and improve the real-time capability of the DFL system. Experimental results demonstrate the superior performance of the proposed method in the context of target localization and tracking.

Highlights

Internet of Things (IoT) concerns about the seamless interaction of objects, sensors, and computing devices [1]
5.1 Physical description of experiment A wireless network containing 20 nodes was deployed in a laboratory
6 Conclusion In this article, we designed and implemented a real-time Devicefree localization (DFL) system, which is based on efficient measurement strategy and lightweight reconstruction algorithm

Summary

Introduction

Internet of Things (IoT) concerns about the seamless interaction of objects, sensors, and computing devices [1]. Zhang et al [10,11,12,13] presented a dynamic model to describe the relation between the RSS variance and the target location, utilized geometric method and the dynamic cluster-based probabilistic cover algorithm to solve the DFL problem. They proposed a real-time DFL system [14]. It runs fast and is suitable for real-time system

System model

Efficient measurement strategy and CMMS algorithm

1: Initialization

L1 trajectory

Conclusion