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New Data Association Technique for Target Tracking in Dense Clutter Environment Using Filtered Gate Structure

Author(s): El Said Mostafa Saad, El. Bardawiny, H. I. Ali, N. M. Shawky

Journal: Signal Processing : An International Journal
ISSN 1985-2339

Volume: 4;
Issue: 6;
Start page: 338;
Date: 2011;
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Keywords: Target Tracking | Data Association | Probabilistic Data Association Algorithm | Kalman Filter.

Improving data association process by increasing the probability of detectingvalid data points (measurements obtained from radar/sonar system) in thepresence of noise for target tracking are discussed in this paper. We develop anovel algorithm by filtering gate for target tracking in dense clutter environment.This algorithm is less sensitive to false alarm (clutter) in gate size thanconventional approaches as probabilistic data association filter (PDAF) whichhas data association algorithm that begin to fail due to the increase in the falsealarm rate or low probability of target detection. This new selection filtered gatemethod combines a conventional threshold based algorithm with geometricmetric measure based on one type of the filtering methods that depends on theidea of adaptive clutter suppression methods. An adaptive search based on thedistance threshold measure is then used to detect valid filtered data point fortarget tracking. Simulation results demonstrate the effectiveness and betterperformance when compared to conventional algorithm.
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