Using Angle of Arrival for Improving Indoor Localization

TL;DR

This paper investigates using the MUSIC algorithm to estimate the angle of arrival of audio signals in indoor environments, enhancing localization for security systems through simulation and real-world data.

Contribution

It demonstrates the implementation of the MUSIC algorithm for real-time AOA estimation and source separation in indoor scenes, advancing audio localization techniques.

Findings

Successful implementation of MUSIC for real-time AOA estimation

Detection of two simultaneous audio sources in real scenes

Potential integration with multimodal security systems

Abstract

In this paper, we primarily explore the improvement of single stream audio systems using Angle of Arrival calculations in both simulation and real life gathered data. We wanted to learn how to discern the direction of an audio source from gathered signal data to ultimately incorporate into a multi modal security system. We focused on the MUSIC algorithm for the estimation of the angle of arrival but briefly experimented with other techniques such as Bartlett and Capo. We were able to implement our own MUSIC algorithm on stimulated data from Cornell. In addition, we demonstrated how we are able to calculate the angle of arrival over time in a real life scene. Finally, we are able to detect the direction of arrival for two separate and simultaneous audio sources in a real life scene. Eventually, we could incorporate this tracking into a multi modal system combined with video. Overall, we are able to produce compelling results for angle of arrival calculations that could be the stepping stones for a better system to detect events in a scene.