Sparse Recovery Beamforming and Upscaling in the Ray Space
- Resource Type
- Conference
- Authors
- Yu, S.; Jin, C.; Antonacci, F.; Sarti, A.
- Source
- ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2021 - 2021 IEEE International Conference on. :776-780 Jun, 2021
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Location awareness
Source separation
Array signal processing
Signal processing algorithms
Transforms
Parallel processing
Microphone arrays
ray space transform
sparse recovery method
microphone arrays
upscaling
sound fields
- Language
- ISSN
- 2379-190X
We have been exploring the integration of sparse recovery methods into the ray space transform over the past years and now demonstrate the potential and benefits of beamforming and upscaling signals in the integrated ray space and sparse recovery domain. A primary advantage of the ray space approach derives from its robust ability to integrate information from multiple arrays and viewpoints. Nonetheless, for a given viewpoint, the ray space technique requires a dense array that can be divided into sub-arrays enabling the plenacoustic approach to signal processing. In this work, we explore a method to upscale an array beyond the limits imposed by the inter-microphone distances associated with the array and the concomitant spatial aliasing. In other words, sparse recovery enables one to synthesize or interpolate signals corresponding to an array with a greater number of microphones with a smaller inter-microphone distance. A critical issue is whether or not this interpolative synthesis actually improves array signal processing. This work shows that upscaling signals in the integrated ray space and sparse recovery domain can improve both source localization and separation.