Cultural quantum-inspired shuffled frog leaping algorithm for direction finding of non-circular signals Online publication date: Sat, 10-May-2014
by Hongyuan Gao; Congqiang Xu
International Journal of Computing Science and Mathematics (IJCSM), Vol. 4, No. 4, 2013
Abstract: In order to resolve complex continuous optimisation problem, a cultural quantum-inspired shuffled frog leaping (CQSFL) algorithm is proposed. The proposed CQSFL applies the quantum knowledge strategy and new quantum leaping equations to shuffled frog leaping algorithm, and thus has the advantages of low computational complexity and fast convergence. As a key step of CQSFL algorithm, leaping movement is modelled as guided cultural behaviour and thus may improve the capability of SFLA to find the optimal solution. Then we applied the proposed CQSFL algorithm in direction finding problem of non-circular signals, which is a hot spot in domain of communication. Then, based on CQSFL algorithm and non-circular maximum likelihood (NML) algorithm, a new direction finding method is proposed, which is called CQSFL-NML algorithm. Monte-Carlo simulations have proved that the CQSFL-NML method has good performance for non-coherent and coherent non-circular signals.
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