Pages

Friday, August 15, 2014

Compressed beamforming

Sound source localization with sensor arrays involves the estimation of the direction-of-arrival (DOA) from a limited number of observations. Compressive sensing (CS) is a method for solving such underdetermined problems, which achieves simultaneously sparsity, thus super-resolution, and computational speed. We formulate the DOA estimation problem in the CS framework and show that CS has superior performance compared to traditional DOA estimation methods. A bias and resolution analysis is performed to indicate the limitations of CS. We show that the bias is related to the beampattern, thus can be predicted. To demonstrate the super-resolution capabilities and the robustness of CS, the method is applied to experimental data from ocean acoustic measurements for source tracking with single-snapshot data.



Join the CompressiveSensing subreddit or the Google+ Community and post there !
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.

No comments:

Post a Comment