Theory and Applications of Spherical Microphone Array Processing by Daniel P. Jarrett Emanuël A.P. Habets & Patrick A. Naylor

Author:Daniel P. Jarrett, Emanuël A.P. Habets & Patrick A. Naylor
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

5.3 Chapter Summary and Conclusions

The focus of this chapter lies in the estimation of acoustic parameters that can provide a priori information that is potentially useful to subsequent acoustic signal enhancement algorithms. In the first part of this chapter, algorithms for DOA estimation were presented: the SRP method, the pseudointensity vector method, and two subspace methods, EB-MUSIC and EB-ESPRIT. It was noted that the pseudointensity vector method and EB-ESPRIT have a low computational cost, as they do not require an exhaustive search of the solution space.

In the second part of the chapter, we introduced two methods for estimating the SDR of a sound field. The CV method, which exploits the temporal variation of the intensity vector, only uses zero- and first-order eigenbeams, and has low computational complexity. The coherence-based method takes advantage of the fact that the coherence between eigenbeams increases with the SDR. The coherence can be computed using pairs of eigenbeams of any order; the complexity of the coherence-based method can be adjusted by changing the number of coherences that are computed. The best way of estimating the coherence using all of the available eigenbeams in a computationally efficient way remains an open question at this time.

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