Robust Sound Source Localization considering Similarity of Back-Propagation Signals

Abstract

We present a novel, robust sound source localization algorithm considering back-propagation signals. Sound propagation paths are estimated by generating direct and reflection acoustic rays based on ray tracing in a backward manner. We then compute the back-propagation signals by designing and using the impulse response of the backward sound propagation based on the acoustic ray paths. For identifying the 3D source position, we use a well-established Monte Carlo localization method. Candidates for a source position are determined by identifying convergence regions of acoustic ray paths. Those candidates are validated by measuring similarities between back-propagation signals, under the assumption that the back-propagation signals of different acoustic ray paths should be similar near the ground-truth sound source position. Thanks to considering similarities of back-propagation signals, our approach can localize a source position with an averaged error of 0.55 m in a room of 7 m by 7 m area with 3 m height in tested environments. We also place additional 67 dB and 77 dB white noise at the background, to test the robustness of our approach. Overall, we observe a 7 % to 100 % improvement in accuracy over the state-of-the-art method.