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

Zizhuo Wang, Yichuan Ding

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

2 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationMobiCom'08 Co-Located Workshops - Proceedings of the 1st ACM International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments, MELT'08
Pages109-112
Number of pages4
DOIs
StatePublished - 2008
Event2008 International Conference on Mobile Computing and Networking, MobiCom'08 - 1st ACM International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments, MELT'08 - San Francisco, CA, United States
Duration: Sep 19 2008Sep 19 2008

Publication series

NameProceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM

Other

Other2008 International Conference on Mobile Computing and Networking, MobiCom'08 - 1st ACM International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments, MELT'08
Country/TerritoryUnited States
CitySan Francisco, CA
Period9/19/089/19/08

Keywords

  • Semidefinite programming
  • Sensor network localization
  • Tracking

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