Real-time tracking for sensor networks via sdp and gradient method

  • Authors:

  • Zizhuo Wang;Yichuan Ding

  • Affiliations:

  • Stanford University, Stanford, CA, USA;Stanford University, Stanford, CA, USA

  • Venue:
  • Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments
  • Year:
  • 2008

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Abstract

The sensor tracking problem is an important problem studied in many different fields. But many of those studies use analysis or machine learning method rather than optimization method. Recently, several approaches have been proposed to solve the static version of the tracking problem, the sensor network localization problem, via Semi-definite Programming(SDP). In this paper, we analyze a new real-time sensor tracking scheme by combining the SDP approach and the gradient method. We show that this approach provides fast and accurate tracking for network sensors. We also discuss the problem of extracting information from the moving sensors, which could be used to predict their movements.