ML-PDA and ML-PMHT: Comparing Multistatic Sonar Trackers for VLO Targets Using a New Multitarget Implementation
Abstract
The maximum-likelihood probabilistic data association (MLPDA) tracker and themaximum-likelihood probabilistic multihypothesis (MLPMHT) tracker are tested in their capacity as algorithms for very low observable (VLO) targets (meaning 6-dB postsignal processing or even less) and are then applied to five synthetic benchmark multistatic active sonar scenarios featuring multiple targets, multiple sources, and multiple receivers. Both methods end up performing well in situations where there is a single target or widely spaced targets. However, MLPMHT has an inherent advantage over MLPDA in that its likelihood ratio (LR) has a simple multitarget formulation, which allows it to be implemented as a true multitarget tracker. This formulation, presented here for the first time, gives MLPMHT superior performance for instances where multiple targets are closely spaced with similar motion dynamics.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 2014
- Accession Number
- AD1019675
Entities
People
- Peter Willett
- Steven Schoenecker
- Yaakov Bar-Shalom
Organizations
- University of Connecticut