A comparison of several different approaches for target tracking with clutter
Lucy Y. Pao, Richard M. Powers · 2004
Five different methods suitable for tracking single targets in clutter are compared: the nearest neighbor algorithm, the probabilistic multi-hypothesis tracking filter, the probabilistic data association filter, the mixture reduction algorithm, and the mean-field event-averaged maximum likelihood estimator. Across a range of clutter densities, comparison results were generated for a common, fixed set of Monte Carlo target, target measurement, and clutter measurement realizations. The relative performances, as measured by track lifetime, RMS tracking error, and computational complexity are compared.