Abstract
A recently proposed adaptive acoustic beamformer based on the maximization of the output SNR (Max-SNR beamformer) has an advantage of requiring no information of transfer functions. A key technology to implement Max-SNR beamformers is to estimate generalized eigenvector (GEV) of covariance matrices of target signal and noise, which are basically unknown. We develop a novel GEV tracking algorithm with decaying time windows that enable Max-SNR beamformer to adapt rapidly moving sources. Simulation results support the analysis.
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Tanaka, T., Shiono, M. (2014). Acoustic Beamforming with Maximum SNR Criterion and Efficient Generalized Eigenvector Tracking. In: Ooi, W.T., Snoek, C.G.M., Tan, H.K., Ho, CK., Huet, B., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2014. PCM 2014. Lecture Notes in Computer Science, vol 8879. Springer, Cham. https://doi.org/10.1007/978-3-319-13168-9_41
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DOI: https://doi.org/10.1007/978-3-319-13168-9_41
Publisher Name: Springer, Cham
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