Sequential Monte Carlo for simultaneous passive device-free tracking and sensor localization using received signal strength measurements

Xi Chen, Andrea Edelstein, Yunpeng Li, Mark Coates, Michael Rabbat, Aidong Men

Research output: Chapter in Book/Report/Conference proceedingConference contribution

87 Citations (Scopus)

Abstract

This paper presents and evaluates a method for simultaneously tracking a target while localizing the sensor nodes of a passive device-free tracking system. The system uses received signal strength (RSS) measurements taken on the links connecting many nodes in a wireless sensor network, with nodes deployed such that the links overlap across the region. A target moving through the region attenuates links intersecting or nearby its path. At the same time, RSS measurements provide information about the relative locations of sensor nodes. We utilize the Sequential Monte Carlo (particle filtering) framework for tracking, and we use an online EM algorithm to simultaneously estimate static parameters (including the sensor locations, as well as model parameters including noise variance and attenuation strength of the target). Simultaneous tracking, online calibration and parameter estimation enable rapid deployment of a RSS-based device free localization system, e.g., in emergency response scenarios. Simulation results and experiments with a wireless sensor network testbed illustrate that the proposed tracking method performs well in a variety of settings.

Original languageEnglish
Title of host publicationProceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11
Pages342-353
Number of pages12
ISBN (Electronic)978-1-4503-0512-9
Publication statusPublished - 27 May 2011
Event10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11 - Chicago, IL, USA United States
Duration: 12 Apr 201114 Apr 2011

Publication series

NameProceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11

Conference

Conference10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11
CountryUSA United States
CityChicago, IL
Period12/04/1114/04/11

Keywords

  • Device-Free
  • Node Localization
  • on-line EM
  • Particle Filter
  • RSS
  • Target Tracking

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

Cite this

Chen, X., Edelstein, A., Li, Y., Coates, M., Rabbat, M., & Men, A. (2011). Sequential Monte Carlo for simultaneous passive device-free tracking and sensor localization using received signal strength measurements. In Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11 (pp. 342-353). [5779050] (Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11). https://ieeexplore.ieee.org/document/5779050