A Joint Optimization Algorithm for Two-Dimensional Microphone Array Estimation

The traditional single microphone can only process the speech signal in the time domain or frequency domain, while the microphone array system introduces the spatial information of the sound source and has a wide range of applications. However, in practical applications, a model of the microphone array is required, which greatly limits the randomness of the microphone array. Although the microphone array can be estimated from the sound source array, it is necessary to know the coordinate information of the sound source relative to the reference microphone. In this paper, a new generalized weighting function (GCC-SPγβ) is adopted to reduce the influence of noise on delay estimation. We also propose a Microphone Joint Optimization Algorithm (MJOA) to invert the localization of microphones by using an array of sound sources. The algorithm builds a mathematical model through a delay estimation algorithm and solves the entire system of equations by introducing each unknown microphone. In this paper, the virtual sound source method is used, and the indoor impulse response of the indoor sound field is established by MATLAB simulation, and the two-dimensional simulation of the sound source is carried out. The experimental results show that the improved algorithm is more robust than the spherical interpolation algorithm (SIA). It has certain practical application value.