Abstract
There are two topics in this paper: one is directive microphone array with application in nearfield acoustic holography and the other is cost-effective particle velocity sensor based on microphone array. White Noise Gain (WNG) and Directivity Index (DI) are employed as the objective functions for optimizing array filters. The method can decrease the reflections from boundaries. The proposed methods are utilized in an Equivalent Source Model (ESM)-based NAH. The proposed techniques are verified by numerical simulations and experiments, with interfering source positioned at various directions. Sound field is reconstructed using the pressure input and the particle velocity estimated by the finite difference method. A traditional method to measure particle velocity is based on the finite difference (FD) approximation of pressure gradient by using a pair of well matched pressure microphones. This approach is known to be sensitive to sensor noise and mismatch. Recently, a double hot-wire sensor termed Microflown became available in light of micro-electro-mechanical system (MEMS) technology. This sensor eliminates the robustness issue of the conventional FD-based methods. In this paper, an alternative two-microphone approach termed the u-sensor is developed from the perspective of robust adaptive filtering. With two ordinary microphones, the proposed u-sensor does not require novel fabrication technology. In the method, plane wave and spherical wave models are employed in the formulation of a Kalman filter with process and measurement noise taken into account. Both numerical and experimental investigations were undertaken to validate the proposed u-sensor technique. The results have shown that the proposed approach attained better performance than the FD method, and comparable performance to a Microflown sensor.