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http://dx.doi.org/10.5762/KAIS.2017.18.5.99

Research on improvement of target tracking performance of LM-IPDAF through improvement of clutter density estimation method  

Yoo, In-Je (Defense Agency for Technology and Quality)
Park, Sung-Jae (Defense Agency for Technology and Quality)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.18, no.5, 2017 , pp. 99-110 More about this Journal
Abstract
Improving tracking performance by estimating the status of multiple targets using radar is important. In a clutter environment, a joint event occurs between the track and measurement in multiple target tracking using a tracking filter. As the number increases, the joint event increases exponentially. The problem to be considered when multiple target tracking filter design in such environments is that first, the tracking filter minimizes the rate of false track alarmsby eliminating the false track and quickly confirming the target track. The purpose is to increase the FTD performance. The second consideration is to improve the track maintenance performance by allocating each measurement to a track efficiently when an event occurs. Through two considerations, a single target tracking data association technique is extended to a multiple target tracking filter, and representative algorithms are JIPDAF and LM-IPDAF. In this study, a probabilistic evaluation of many hypotheses in the assignment of measurements was not performed, so that the computation amount does not increase nonlinearly according to the number of measurements and tracks, and the track existence probability based on the track density The LM-IPDAF algorithm was introduced. This paper also proposes a method to reduce the computational complexity by improving the clutter density estimation method for calculating the track existence probability of LM-IPDAF. The performance was verified by a comparison with the existing algorithm through simulation. As a result, it was possible to reduce the simulation processing time by approximately 20% while achieving equivalent performance on the position RMSE and Confirmed True Track.
Keywords
Clutter Density; Data Association; LM-IPDAF; Multi-Target Tracking; Tracking Algorithm;
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