Hybridization of Genetic Algorithm and IBMUSIC Applied to DOA Estimation under Coherent Signals

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Title:	Hybridization of Genetic Algorithm and IBMUSIC Applied to DOA Estimation under Coherent Signals
Authors:	Hung, Jui-Chung;洪瑞鍾;Lin, Chien-Chou
Contributors:	臺北市立教育大學資訊科學系
Keywords:	Genetic Algorithm;Direction-of-Arrival (DOA);Multiple Signal Classification (MUSIC)
Date:	2011
Issue Date:	2017-07-24 11:28:01 (UTC+8)
Abstract:	This paper introduces a new hybrid of genetic algorithm (GA) and iteration beamspace multiple signal classification (IBMUSIC) suitable for making direction-of-arrival (DOA) in coherent signals. In general, the problem of estimation the DOA in coherent signals is more difficult to solve and conventional DOA estimation methods such as minimum variance distortionless response (MVDR) and multiple signal classification (MUSIC) algorithm produce mistake results owing to the existence of coherent terms. In this situation, we adopt the method of conjugate with a GA for selecting the initial search angle of IBMUSIC estimation. Moreover, the received data is projected onto the steering vectors of signal complement space by GA estimation, and then the coherent terms can be decrease. We use this tool to estimate the DOA in coherent signals to achieve low computational complexity and an excellent performance. Finally, numerical example was analyzed to illustrate the design procedure and confirm the performance of the proposed method.
Relation:	accepted, Applied Mathematics & Information Sciences，p489-496
Appears in Collections:	[Department of Computer Science] Periodical Articles

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