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A unifying approach to track-to-track correlation for multisensor fusion for multiple targets

ASKIN DEMIRKOL1,* , ZAFER DEMIR2, EROL EMRE3

Affiliation

  1. Sakarya University, Faculty of Engineering, Department of Electrical and Electronics Engineering, Sakarya-Turkey
  2. Anadolu University, Vocational School of Porsuk, Eskisehir – T urkey
  3. Sakarya University, Department of Computer Engineering, Sakarya – Turkey

Abstract

In this paper, a global modeling approach was proposed for multi sensor fusion problems. Once the global model was investigated considering the data association and fusion, it is adapted to track to track correlation problem by a new approach. The key development of the approach is that a decentralized filtering algorithm is used for data fusion and state estimation problems in a multi-target tracking system. The use of a global mapping matrix for the track to track correlation is key element of our technique. Via the presented mathematical models, the sensor fusion and track to track correlation problems can be solved in a global way..

Keywords

Multi-sensor fusion, Decentralized Kalman filtering, Data association, Multi-target tracking, Track to track correlation.

Citation

ASKIN DEMIRKOL, ZAFER DEMIR, EROL EMRE, A unifying approach to track-to-track correlation for multisensor fusion for multiple targets, Optoelectronics and Advanced Materials - Rapid Communications, 9, 1-2, January-February 2015, pp.165-177 (2015).

Submitted at: Oct. 16, 2014

Accepted at: Jan. 21, 2015