Abstract
Long baseline microphone arrays, where the distance between single microphones is large, is a cost-effective method to monitor activity in a large region of interest. The high range between source and sensors in a long baseline setup, generally leads to low signal-to-noise ratios (SNR). This affect the performance of localization. This paper investigates how energy based localization (EBL) can be used for localization and tracking of both single and multiple acoustic sources, within a long baseline array. Least-Squares (LS) optimization have been used for EBL-based localization, however the localization performance is sensitive to low SNR. We propose a tracking scheme based on a cost reference particle filter (CRPF) to increase performance during low SNR. The CRPF is a new class of particle filters which is able to estimate the system state from the available observations without a priori knowledge of any probability density function. We present a modified cost function, for EBL based localization, which is incorporated in the CRPF framework to increase tracking performance during simulated wind gusts and background noise. The proposed method outperforms LS based localization in the case of low SNR.
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