A Data Fusion Algorithm for Large Heterogeneous Sensor Networks

  • Authors:

  • Hong Lin;John Rushing;Sara Graves;Evans Criswell

  • Affiliations:

  • University of Alabama in Huntsville, Huntsville, Alabama;University of Alabama in Huntsville, Huntsville, Alabama;University of Alabama in Huntsville, Huntsville, Alabama;University of Alabama in Huntsville, Huntsville, Alabama

  • Venue:
  • WASA '07 Proceedings of the International Conference on Wireless Algorithms,Systems and Applications
  • Year:
  • 2007

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Abstract

A distributed search based data fusion algorithm is presented for target detections in large heterogeneous sensor networks. A score function is introduced as the objection function during the optimal search. The network state is determined when the score is the highest. A close to optimal solution can be obtained before the arrival of the next sensor data thus enabling real time target tracking. The algorithm is evaluated with a series of real-time simulations on networks of variable sensor compositions with a commodity Linux cluster.