Radar Target Tracking via Robust Linear Filtering

Radar Target Tracking via Robust Linear Filtering

In this letter, we provide a robust version of a linear Kalman filter for target tracking based on a measurement conversion technique on the nonlinear radar measurements. We prove that the state estimation error is bounded in a probabilistic sense. We compare our approach with the current state of t...

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Veröffentlicht in:IEEE signal processing letters 2007-12, Vol.14 (12), p.1028-1031
Hauptverfasser: Bishop, A.N., Pathirana, P.N., Savkin, A.V.
Format: Artikel
Sprache:eng
Schlagworte:
Conversion
Coordinate measuring machines
Filtering
Filtration
Localization
Maximum likelihood detection
Noise measurement
Nonlinear filters
radar
Radar measurement
Radar measurements
Radar tracking
robust estimation
Robustness
sensor networks
State estimation
State of the art
Target tracking
Tracking
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Beschreibung
Zusammenfassung:In this letter, we provide a robust version of a linear Kalman filter for target tracking based on a measurement conversion technique on the nonlinear radar measurements. We prove that the state estimation error is bounded in a probabilistic sense. We compare our approach with the current state of the art in converted radar measurement-based linear filtering.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2007.907993