A Comparison of the ML-PDA and the ML-PMHT Algorithms
Abstract
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, MLPMHT slightly outperformed ML-PDA in terms of in-track percentage. However, in a scenario with closely-spaced targets, ML-PDA exhibited superior performance.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2011
- Accession Number
- ADA557844
Entities
People
- Peter Willett
- Steven Schoenecker
- Yaakov Bar-Shalom
Organizations
- University of Connecticut