A comparison of the ML-PDA and the ML-PMHT algorithms

The Maximum Likelihood Probabilistic Data Association (ML-PDA) tracker and the Maximum Likelihood Probabilistic Multi-Hypothesis (ML-PMHT) tracker were applied to five synthetic multistatic active sonar scenarios featuring multiple targets, multiple sources, and multiple receivers. For each of the scenarios, Monte Carlo testing was performed to quantify the performance differences between the two algorithms. Both trackers ended up performing well. For most scenarios, ML-PMHT slightly outperformed ML-PDA in terms of in-track percentage. However, in a scenario with closely-spaced targets, ML-PDA exhibited superior performance.