Fingerprinting Method for Acoustic Localization using Low-Profile Microphone Arrays

Indoor localization of unknown acoustic events with MEMS microphone arrays have a huge potential in applications like home assisted living and surveillance. This article presents an Angle of Arrival (AoA) fingerprinting method for use in Wireless Acoustic Sensor Networks (WASNs) with low-profile microphone arrays. In a first research phase, acoustic measurements are performed in an anechoic room to evaluate two computationally efficient time domain delay-based AoA algorithms: one based on dot product calculations and another based on dot products with a PHAse Transform (PHAT). The evaluation of the algorithms is conducted with two sound events: white noise and a female voice. The algorithms are able to calculate the AoA with Root Mean Square Errors (RMSEs) of 3.5 degrees for white noise and 9.8 degrees to 16 degrees for female vocal sounds. In the second research phase, an AoA fingerprinting algorithm is developed for acoustic event localization. The proposed solution is experimentally verified in a room of 4.25m by 9.20m with 4 acoustic sensor nodes. Acoustic fingerprints of white noise, recorded along a predefined grid in the room, are used to localize white noise and vocal sounds. The localization errors are evaluated using one node at a time, resulting in mean localization errors between 0.65m and 0.98m for white noise and between 1.18m and 1.52m for vocal sounds.