Radar Target Tracking via Robust Linear Filtering
Отслеживание радиолокационных целей с помощью робастной линейной фильтрации
2007-11-21
SCID: 54.1/g4xkjhmw
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converted radar measurementsmeasurement conversionradar target trackingrobust linear Kalman filter
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Abstract (AI)
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.
Key Findings
1
A robust version of a linear Kalman filter for radar target tracking is developed using a measurement conversion technique for nonlinear radar measurements.
2
The new approach is empirically compared with current state-of-the-art converted measurement-based linear filtering methods.
3
The proposed filter guarantees that the state estimation error is bounded in a probabilistic sense.
Research Object
Radar target tracking system using converted radar measurements for linear filtering
Research Subject
Robust linear Kalman-filter-based state estimation (probabilistic boundedness of estimation error) for targets using measurement conversion of nonlinear radar measurements
Publication Details
Publication Date
2007-11-21
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