PDAF with multiple clutter regions and target models

This paper presents the theory of a new multiple model probabilistic data association filter (PDAF). The analysis is generalized for the case of multiple nonuniform clutter regions within the measurement data that updates each model of the filter. To reduce the possibility of clutter measurements fo...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2003-01, Vol.39 (1), p.110-124
Main Authors: Colegrove, S.B., Davey, S.J.
Format: Article
Language:English
Subjects:
Aircraft components
Algorithms
Amplitudes
Australia
Clutter
Displays
Electronic systems
Filtering theory
Filters
Nonuniform
Observability
Radar tracking
State vectors
Target tracking
Testing
Time measurement
Tracking
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Summary:This paper presents the theory of a new multiple model probabilistic data association filter (PDAF). The analysis is generalized for the case of multiple nonuniform clutter regions within the measurement data that updates each model of the filter. To reduce the possibility of clutter measurements forming established tracks, the solution includes a model for a visible target. That is, a target that gives sensor measurements that satisfy one of the target models. Other features included in the algorithm are the selection of a fixed number of nearest measurements and the addition of signal amplitude to the target state vector. The nonuniform clutter model developed here is applicable to tracking signal amplitude. Performance of this algorithm is illustrated using experimentally recorded over-the-horizon radar (OTHR) data.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2003.1188897