X-band marine radar systems are flexible and low-cost tools for monitoring multiple targets in a surveillance area. They can provide high resolution measurements both in space and time. Such features offer the opportunity to get accurate information not only about the target kinematics, as other conventional sensors, but also about the target size. In this paper we exploit the random matrix framework to track extended targets. Proper measurement models to deal with the radar’s measurement noise and its conversion into Cartesian coordinates are presented here. Benefits of the proposed extended target tracking using converted measurements can be mainly related to the problem of the targets’ size estimation, while advantages on estimation of the targets’ kinematic features can be considered negligible. The validity of the proposed approach has been demonstrated by using both simulated and real data. Gains up to 70% for the targets’ width estimation accuracy and around 65% for the length are observed on real data. The integration of the proposed model into the gamma Gaussian inverse Wishart probability hypothesis density tracker is also provided and tested on real data.

Converted measurements Bayesian extended target tracking applied to x-band marine radar data

Vivone G.
;
Braca P.;
2017-01-01

Abstract

X-band marine radar systems are flexible and low-cost tools for monitoring multiple targets in a surveillance area. They can provide high resolution measurements both in space and time. Such features offer the opportunity to get accurate information not only about the target kinematics, as other conventional sensors, but also about the target size. In this paper we exploit the random matrix framework to track extended targets. Proper measurement models to deal with the radar’s measurement noise and its conversion into Cartesian coordinates are presented here. Benefits of the proposed extended target tracking using converted measurements can be mainly related to the problem of the targets’ size estimation, while advantages on estimation of the targets’ kinematic features can be considered negligible. The validity of the proposed approach has been demonstrated by using both simulated and real data. Gains up to 70% for the targets’ width estimation accuracy and around 65% for the length are observed on real data. The integration of the proposed model into the gamma Gaussian inverse Wishart probability hypothesis density tracker is also provided and tested on real data.
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4725359
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