Simultaneous localization, calibration, and tracking in an ad hoc sensor network

  • Authors:

  • Christopher Taylor;Ali Rahimi;Jonathan Bachrach;Howard Shrobe;Anthony Grue

  • Affiliations:

  • Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA

  • Venue:
  • Proceedings of the 5th international conference on Information processing in sensor networks
  • Year:
  • 2006

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Abstract

We introduce Simultaneous Localization and Tracking, called SLAT, the problem of tracking a target in a sensor network while simultaneously localizing and calibrating the nodes of the network. Our proposed solution, LaSLAT, is a Bayesian filter that provides on-line probabilistic estimates of sensor locations and target tracks. It does not require globally accessible beacon signals or accurate ranging between the nodes. Real hardware experiments are presented for 2D and 3D, indoor and outdoor, and ultrasound and audible ranging-hardware-based deployments. Results demonstrate rapid convergence and high positioning accuracy.