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A Hybrid Features-Based Target Detection Scheme for Maritime Radar

Quy, T.B. and Minh, T.H. and Viet, H.T. and Kim, P.P. and Ngoc, S.T. and Van, T.L. (2023) A Hybrid Features-Based Target Detection Scheme for Maritime Radar. In: UNSPECIFIED.

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Abstract

The popular method of automatic target detection used for most maritime radar systems is constant false alarm rate. However, this technique seems insufficient to differentiate a real target from others. To overcome such a deficiency, a hybrid features-based target detection methodology is developed to distinguish between target and non-target objects for maritime radar. This approach combines echo signal detection based on constant false alarm rate and support vector machine classification using hybrid features extracted from objects resulting from connected-component labeling. The efficacy of the proposed approach is verified with datasets recorded from a real maritime radar system. © 2023 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Offices > Office of International Cooperation
Identification Number: 10.1109/ATC58710.2023.10318886
Uncontrolled Keywords: Alarm systems; Feature extraction; Image resolution; Object detection; Object recognition; Radar target recognition; Support vector machines; Tracking radar, Automatic target detection; Constant false alarm rate; Detection scheme; Feature-based; Hybrid features; Maritime radar; Object classification; Target and non targets; Target object; Targets detection, Errors
Additional Information: cited By 0; Conference of 16th International Conference on Advanced Technologies for Communications, ATC 2023 ; Conference Date: 19 October 2023 Through 21 October 2023; Conference Code:194622
URI: http://eprints.lqdtu.edu.vn/id/eprint/11033

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