Quantum-inspired cultural bacterial foraging algorithm for direction finding of impulse noise

摘要

In order to resolve direction finding problem in the presence of impulse noise, a quantum-inspired cultural bacterial foraging algorithm (QCBFA) is proposed. The proposed QCBFA applies the quantum knowledge strategy and new quantum foraging equations to bacterial foraging optimisation algorithm (BFOA), and thus has the advantages of low computational complexity and fast convergence. As a key step of QCBFA algorithm, chemotactic movement is modelled as guided cultural behaviour and thus may improve the capability of BFOA to find the optimal solution. Then we applied the proposed QCBFA to direction finding problem in the presence of impulse noise, which is a hot spot in signal processing of array. Then, based on QCBFA and infinite norm maximum likelihood (INML) algorithm, a new direction finding method is proposed, which is called as QCBFA-INML algorithm. Monte Carlo simulations have showed that the QCBFA-INML method has excellent direction finding performance for non-coherent and coherent signals in the strong impulse noise.