Sensor fusion method for passive acoustic arrays

Abstract

For passive acoustic arrays, a general method is described that ranks and selects multiple microphone configurations within the array that are likely to produce accurate position estimates. This method segments a two-dimensional array into various configurations of microphone pairs and flattens these configurations into one-dimension for comparison. Each configuration is ranked based on the microphones' spatial information (known a-priori) and incoming bearing estimates. These rankings select different microphone pair configurations, whose position estimates are combined in a weighted-average algorithm. Simulations and experimental results show that this method selects microphone configurations that provide the least position error. Through a fusion algorithm, which combines individual microphone pair data, an array's position accuracy can improve.