In this paper, the five fundamental issues of target extension, target maneuvering, closely spaced targets, weak targets, and dense clutter are tackled simultaneously in the framework of a new tracking approach that is capable of effectively detecting multiple closely-spaced maneuvering weak and extended targets in densely cluttered environment. The proposed technique finds its foundation in the track-before-detect (TBD) paradigm, proven to be effective in tracking weak targets in presence of dense clutter. The approach consists of two stages. In the first stage, a 3-dimensional projection based TBD algorithm allows addressing the problem of target extension, weak targets, and dense clutter. Straight line tracklets are obtained at the end of the first stage. In the second stage, tracklets association is performed to obtain the target trajectories. The issue of closely spaced targets and target maneuvering is addressed in this second stage. To illustrate the effectiveness of the proposed approach, synthetic data, real data from a netted radar system, and real data from a high resolution radar are processed both with the proposed algorithm and with several existing algorithms. The obtained results reveal that the proposed method can outperform the competing approaches in various scenarios.

Yan, B., Paolini, E., Xu, N., Sun, Z., Xu, L. (2021). Multiple maneuvering extended targets detection by 3D projection and tracklet association. SIGNAL PROCESSING, 179, 1-19 [10.1016/j.sigpro.2020.107821].

Multiple maneuvering extended targets detection by 3D projection and tracklet association

Paolini E.;
2021

Abstract

In this paper, the five fundamental issues of target extension, target maneuvering, closely spaced targets, weak targets, and dense clutter are tackled simultaneously in the framework of a new tracking approach that is capable of effectively detecting multiple closely-spaced maneuvering weak and extended targets in densely cluttered environment. The proposed technique finds its foundation in the track-before-detect (TBD) paradigm, proven to be effective in tracking weak targets in presence of dense clutter. The approach consists of two stages. In the first stage, a 3-dimensional projection based TBD algorithm allows addressing the problem of target extension, weak targets, and dense clutter. Straight line tracklets are obtained at the end of the first stage. In the second stage, tracklets association is performed to obtain the target trajectories. The issue of closely spaced targets and target maneuvering is addressed in this second stage. To illustrate the effectiveness of the proposed approach, synthetic data, real data from a netted radar system, and real data from a high resolution radar are processed both with the proposed algorithm and with several existing algorithms. The obtained results reveal that the proposed method can outperform the competing approaches in various scenarios.
2021
Yan, B., Paolini, E., Xu, N., Sun, Z., Xu, L. (2021). Multiple maneuvering extended targets detection by 3D projection and tracklet association. SIGNAL PROCESSING, 179, 1-19 [10.1016/j.sigpro.2020.107821].
Yan, B.; Paolini, E.; Xu, N.; Sun, Z.; Xu, L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/802400
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