Single-Group-Target Data Association and Track Maintenance

Abstract

As we know, the nearest-neighboring algorithm and probability association algorithm in Bayesian algorithm are very successful two data association algorithms. The nearest-neighboring method, as one of the comparatively effective data association methods, regards the statistically “nearest” observation data that fall inside association gates as the correlated observation data of the target under tracking. The probability data association algorithm is an all-neighboring method. It comprehensively considers all the measurements inside tracking gate, computes the equivalent measurement according to the probabilistic weighted coefficients of each measurement, and updates target state using equivalent measurement.