The comparison of the performances of global nearest neighbor and probability hypothesis density filter for varying clutter rates

Target tracking algorithms adopted in modern radars are designed such that they can track multi targets by considering target births and target deaths. These algorithms are derived by integrating the data association techniques into the single target filters. Recently, target tracking methods expoiting random finite sets have been emerged as an alternative to the data association techniques In this paper we aim to compare the performance both of the techniques in varying clutter rates with respect to OSPA distance metric that considers both the cardinality and the localization errors of the filters.