Data association and fusion algorithms for13; tracking in presence of measurement loss

Naidu, VPS and Girija, G and Raol, JR (2005) Data association and fusion algorithms for13; tracking in presence of measurement loss. IE(I) journal-AS, 86. pp. 17-28.

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Abstract

Tracking in multi-sensor multi-amp;at@ (MSMT) scenario is a complex and difficult task due to the uncertainties in origin of observations. This requires appropriate gating and data association procedures to associate measurements with target. A PC MATlAB program, based on track-oriented approach, is evaluated which uses Nearest Neigbbour Kalman Filter (NNKF) and Probabilistic Data Association Filter (PDAF)for tracking multiple targets from data amp; multiple sensors. For track-to-track fusion state vector fusion philosophy is employed. The tracking performance in presence of simulated track/data loss and recovery as well as clutter is evaluated. During the data loss , the PDAF performed better than the the NKAF. In the presence of mild clutter and spare target scenarios, the NNKF and the PDAF give similar performance.

Item Type: Article
Uncontrolled Keywords: Fusion algorithm;Measurement loss;Uncertainty measurement;Track management
Subjects: MATHEMATICAL AND COMPUTER SCIENCES > Statistics and Probability
Depositing User: Users 90 not found.
Date Deposited: 19 Feb 2008
Last Modified: 17 Jun 2010 04:55
URI: http://nal-ir.nal.res.in/id/eprint/4608

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