Application of Bee Evolutionary Genetic Algorithm to Maximum Likelihood Direction-of-Arrival Estimation
Joint Authors
Fan, Xinnan
Shi, Pengfei
Pang, Linbin
Li, Guangzhi
Zhang, Xuewu
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-25
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The maximum likelihood (ML) method achieves an excellent performance for DOA estimation.
However, its computational complexity is too high for a multidimensional nonlinear solution search.
To address this issue, an improved bee evolutionary genetic algorithm (IBEGA) is applied to maximize the likelihood function for DOA estimation.
First, an opposition-based reinforcement learning method is utilized to achieve a better initial population for the BEGA.
Second, an improved arithmetic crossover operator is proposed to improve the global searching performance.
The experimental results show that the proposed algorithm can reduce the computational complexity of ML DOA estimation significantly without sacrificing the estimation accuracy.
American Psychological Association (APA)
Fan, Xinnan& Pang, Linbin& Shi, Pengfei& Li, Guangzhi& Zhang, Xuewu. 2019. Application of Bee Evolutionary Genetic Algorithm to Maximum Likelihood Direction-of-Arrival Estimation. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1196321
Modern Language Association (MLA)
Fan, Xinnan…[et al.]. Application of Bee Evolutionary Genetic Algorithm to Maximum Likelihood Direction-of-Arrival Estimation. Mathematical Problems in Engineering No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1196321
American Medical Association (AMA)
Fan, Xinnan& Pang, Linbin& Shi, Pengfei& Li, Guangzhi& Zhang, Xuewu. Application of Bee Evolutionary Genetic Algorithm to Maximum Likelihood Direction-of-Arrival Estimation. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1196321
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196321