Prediction of track purity and track accuracy in dense targetenvironments

摘要

This note is concerned with performance prediction of multiple-target tracking systems, particularly in data-rich, high-target-density environments. Two simple but useful expressions are described: (i) the exponential law for predicting average probability of correct data association, and (ii) the linear-times-exponential law for calculating the effective measurement error variances with possible data misassociation. Estimation of two key multiple-target tracking performance measures, i.e., track purity and track accuracy, are then derived using these two laws