Yaakov Buchris: Robust and Sparse Design of Differential Microphone Arrays (12/6/19)

Design of nearly frequency-invariant (FI) broadband beamformers for several real-world applications like audio, communication, and sonar systems, is important as such beamformers can recover the signals of interest while reducing some artifacts caused during the beamforming process. Classical approaches of FI beamforming are based on constrained optimization, analytical solutions, and coherent subspace methods. Another concept is based on differential microphone arrays (DMAs), which refer to small-size superdirective arrays obtaining nearly frequencyinvariant beampatterns.
This research focuses on a sparse design of DMAs to be applied in several array geometries, like linear, planar, concentric, and more. In such arrays, the nonuniform design of the sensors’ locations enables to obtain arrays with a better robustness to array imperfections, but with a smaller number of sensors than in the uniform design. The novelty of our work relates to the fact that we are interested in broadband signals, like speech, thus, the chosen sensors should be joint to all the frequencies in the relevant bandwidth. For that purpose, we propose an incoherent joint sparse design which obtains high performance with a feasible computational complexity.

*Ph.D. Seminar under the supervision of Prof. Israel Cohen and Jacob Benesty.

 

BIO:

Yaakov Buchris received the B.Sc. and M.Sc. degrees in electrical engineering from the Technion-Israel Institute of Technology, Haifa, in 2005, and 2011, respectively. He is currently pursuing the Ph.D. degree in electrical engineering at the Technion-Israel Institute of Technology, Haifa, Israel.
Since 2002 he has been with RAFAEL, Advanced Defense Systems Ltd, Haifa, Israel, as a Research Engineer in the underwater acoustic communication group. Since 2005, he has also been a Teaching Assistant and a Project Supervisor with the Communications Lab and the Signal and Image Processing Lab (SIPL), Electrical Engineering Department, Technion. His research interests are statistical signal processing, adaptive filtering, digital communications, and array processing.