Direction finding of signal subspace fitting based on cultural bee colony algorithm
Hongyuan Gao, Xiaodong Han · 2010
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.