Multi-target multi-scan smoothing in clutter

Abstract

The multi-target multi-scan smoothing algorithm, which is an extended version of the smoothing integrated track splitting (sITS) algorithm, is presented in this study. The differences between the sITS and the proposed algorithms are that the (iterative) joint integrated track splitting (ITS) algorithm is applied and joint data association probabilities are used for the backward ITS update. A comparative assessment of the smoothing/non-smoothing and single-target/multi-target data association algorithm is carried out to verify the false track discrimination, trajectory estimation and track retention performances.