Set Theory Correlation Free Algorithm for HRRR Target Tracking
Abstract
One challenge of simultaneous tracking and identification of targets is the fusion of continuous and discrete information. Recently a few fusionists including Mahler 1 and Mori 2 are using a set theory approach for a unified data fusion theory which is a correlation free paradigm 3 This paper uses the set theory approach as a basis for a method of fusing kinematic-continuous data and identification-discrete feature information. The set of features are high range resolution radar range-bin locations and amplitudes which are collected over a small aperture and a scrambled method is used to order a feature set. Once features are ordered, a recursive belief filter operates in feature space to combine track and identification measurements. The intersection of track and identification methods results in a simultaneous tracking and identification algorithm which accumulates evidence for belief in targets and rules out non-plausible targets.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1999
- Accession Number
- ADA392193
Entities
People
- Erik Blasch
- Lang Hong
Organizations
- Air Force Research Laboratory