Improving Track Initiation Performance by Track Validation Algorithms for Multi-Target Tracking in Heavy Clutter

Abstract

In this study, for multi-target tracking in an heavy clutter environment, line detection-based validation algorithms are proposed for improving track initiation performance by reducing false tracks. Track validation algorithm is applied to the results of the base track initiation algorithm periodically and deviation from line evaluated based on a defined measure. Then, by thresholding the deviation value, true and false tracks are discriminated, even for maneuvering targets. Thus, performance of both track initiation and tracker are improved by means of number of false tracks.