Maximum likelihood direction of arrival estimator based on modified ant colony optimization

Linlin Mao, Qunfei Zhang, Jianguo Huang, Jing Han

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A novel maximum likelihood direction of arrival estimator based on modified ant colony optimization is proposed to lighten the exponentially increasing computation burden introduced by multidimensional grid search. By integrating chaos initialization and local search, modified ant colony optimization can overcome the drawbacks of ant colony optimization, such as low convergence speed and being easily trapped in local optimum. It is shown via simulations that the proposed method can keep the excellent performance of the original maximum likelihood direction of arrival estimator and reduce the computation evidently. Due to the initialization via chaotic sequences and local search in the solution update procedure, the proposed method reduces the sensitivity of parameters, and thus outperforms the maximum likelihood estimator based on ant colony for its higher precision and less computation.

Original languageEnglish
Title of host publication2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013 - Conference Proceedings
DOIs
StatePublished - 2013
Event2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013 - Xi'an, Shaanxi, China
Duration: 22 Oct 201325 Oct 2013

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450

Conference

Conference2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013
Country/TerritoryChina
CityXi'an, Shaanxi
Period22/10/1325/10/13

Keywords

  • ant colony optimization
  • computational complexity
  • direction of arrival
  • Maximum likelihood

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