摘要：The complex relationship between array spatial gain pattern and microphone distribution limits the effective use of traditional methods to optimize the element placements of microphone arrays. This paper presents a genetic algorithm (GA) for microphone array optimization problems with the purpose of maximizing beamforming SNR for given possible distribution of sound sources. Functions based on the statistical geometry descriptors are applied as the objective functions of GA. Three optimization experiments involving linear and planar arrays in continuous and discrete design spaces are performed under various acoustic scenes. Results demonstrate that proposed algorithm sorts out these superior geometries with significant SNR improvement over randomly generated arrays and regular arrays. High successful rate, rapid convergence speed, and fast processing time observed in all the experiments demonstrate the feasibility of this algorithm as a practical tool for microphone array optimization.
