Angle tracking of the desired target in the presence of interference is a common radar problem. It can occur when the desired target is competing with a jammer, clutter, or multipath. Angle statistics can vary signifi...
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Angle tracking of the desired target in the presence of interference is a common radar problem. It can occur when the desired target is competing with a jammer, clutter, or multipath. Angle statistics can vary significantly for a tracking radar depending upon the nature of this interference. The angular mean and variance are presented for three different statistical two-target types for single and multiple measurements. Previously derived values are presented for completeness in conjunction with derivations not found in the open literature. The signal-to-noise ratio is assumed to be large so that the effects of receiver noise may be neglected.
This paper presents multi sensor fusion architecture to fuse multi target tracks from the Radar and an Infrared Search & Track (IRST) system. The proposed architecture uses global nearest neighborhood (GNN) algori...
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ISBN:
(纸本)9781713867890
This paper presents multi sensor fusion architecture to fuse multi target tracks from the Radar and an Infrared Search & Track (IRST) system. The proposed architecture uses global nearest neighborhood (GNN) algorithm for data association between target tracks of Radar and IRST. Further a GNN based central track manager is proposed to maintain the fused tracks from Radar and IRST. The Radar track outputs are modelled in Cartesian coordinates, providing the target position and velocity states with their corresponding covariance, while the radar detections are in polar coordinates. The IRST track output provides angle only information of the targets with their corresponding covariance. Simulations are carried out in single aircraft - multi target scenario and it is observed that the fused track output has improved angle accuracy with lesser variance.
This paper presents multi sensor fusion architecture to fuse multi target tracks from the Radar and an Infrared Search & Track (IRST) system. The proposed architecture uses global nearest neighborhood (GNN) algori...
详细信息
This paper presents multi sensor fusion architecture to fuse multi target tracks from the Radar and an Infrared Search & Track (IRST) system. The proposed architecture uses global nearest neighborhood (GNN) algorithm for data association between target tracks of Radar and IRST. Further a GNN based central track manager is proposed to maintain the fused tracks from Radar and IRST. The Radar track outputs are modelled in Cartesian coordinates, providing the target position and velocity states with their corresponding covariance, while the radar detections are in polar coordinates. The IRST track output provides angle only information of the targets with their corresponding covariance. Simulations are carried out in single aircraft - multi target scenario and it is observed that the fused track output has improved angle accuracy with lesser variance.
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