DocumentCode
3228317
Title
Direction finding of signal subspace fitting based on cultural bee colony algorithm
Author
Gao, Hongyuan ; Han, Xiaodong
Author_Institution
Coll. of Inf. & Commun. Eng., Harbin Eng. Univ., Harbin, China
fYear
2010
fDate
23-26 Sept. 2010
Firstpage
966
Lastpage
970
Abstract
Based on weighted signal subspace fitting and the minimum redundant array, a minimum redundant-weighted signal subspace fitting (MR-WSSF) algorithm is proposed. The proposed algorithm utilized few virtual elements and expanded the number of effective aperture array, while significantly improving the performance of the original WSSF algorithms. In order to fit the proposed direction finding algorithm based on the minimum redundant array and WSSF, a cultural bee colony (CBC) algorithm is proposed and applied to MR-WSSF. In the proposed CBC algorithm, it is key idea that cultural bee colony is to acquire problem-solving knowledge from the artificial bee colony and in return make use of that knowledge to bee colony and guide the search in fast velocity. Monte-Carlo simulations have proved that the proposed CBC-MR-WSSF method has some good performance such as high precision solution and the capability of using a small number of elements to find more signal sources.
Keywords
Monte Carlo methods; array signal processing; optimisation; problem solving; CBC algorithm; MR-WSSF algorithm; Monte-Carlo simulation; aperture array; artificial bee colony; cultural bee colony algorithm; direction finding; minimum redundant array; minimum redundant-weighted signal subspace fitting; problem-solving knowledge; artificial bee colony; cultural algorithm; direction finding; minimum redundancy linear arrays; weighted signal subspace fitting;
fLanguage
English
Publisher
ieee
Conference_Titel
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-6437-1
Type
conf
DOI
10.1109/BICTA.2010.5645128
Filename
5645128
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