A new algorithm for group tracking

Wang, Huaili; Wang, Desheng; Tian, Lisheng; Ding, Pengfei

doi:10.1109/icr.2001.984916

2001 CIE International Conference on Radar Proceedings (Cat No.01TH8559)

DOI: 10.1109/icr.2001.984916

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A new algorithm for group tracking

Huaili Wang

Desheng Wang²,

Lisheng Tian³

et al.

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“…Blackman divided the problem into centroid group target tracking and queue group target tracking. Later Dru mmond and some others [3] proposed a "groupcluster" tracking algorithm.Recently, Gadaleta et al summed up the tracking matching problem of co mmonly "groupcluster " [4] and they proposed a tracking system [5] of "group-clustering" Multi-Frame Assignment. For group target feature measurement and resolution, the multi-target inverse synthetic aperture radar (ISAR) imaging and time-frequency analysis were propsed in [6,7,8,9].…”

mentioning

confidence: 99%

Based on Improved ESPRIT Algorithm Radar Multi-target Recognition

Jia

Yang

et al. 2013

2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing

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At present, application of dense targets is one of the important means of penetration. In many observation conditions, the echoes from the dense targets mixed with many aliasing signals, and conventional radar signal processing algorithms do not take the aliasing signals into account. Therefore it is difficult for conventional algorithms to recognize multi-targets. In this paper, an improved ES PRIT algorithm is proposed which can recognize the multi-targets from the aliasing echoes and greatly reduce the computational complexity without changing the algorithm accuracy, especially can obtain a better estimation in the case of low S NR environment. The proposed algorithm can firstly quickly realize the estimate of scattering center parameters of target echoes, and then based on the estimation, the aliasing targets can be recognized. The Simulation also verifies the improved ES PRIT algorithm has a better identification and recognition capability of aliasing targets in low SNR condition. Moreover because of reduction of the computational complexity, the performance of proposed algorithm is faster than conventional methods, especial ly in the case of multiple aliasing scattering centers.Keywords-identification and recognition of multi-target, ESPRIT algorithm, aliasing target, the estimate of scattering center parameter

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confidence: 99%

Based on Improved ESPRIT Algorithm Radar Multi-target Recognition

Jia

Yang

et al. 2013

2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing

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Group tracking based on hypothesis management aided MCMC-PF algorithm

Wang

Han

Wei

2016

2016 CIE International Conference on Radar (RADAR)

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The Algorithm of the Clutter and Interference Deletion Based on the Image Technique of the Group Segmentation

Wang¹,

Jia²,

Tang³

2016

Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling

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A new algorithm for group tracking

Cited by 3 publications

References 5 publications

Based on Improved ESPRIT Algorithm Radar Multi-target Recognition

Based on Improved ESPRIT Algorithm Radar Multi-target Recognition

Group tracking based on hypothesis management aided MCMC-PF algorithm

The Algorithm of the Clutter and Interference Deletion Based on the Image Technique of the Group Segmentation

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