Title :
Bayesian compressive sensing for DOA estimation using the difference coarray
Author :
Xiangrong Wang ; Amin, Moeness G. ; Ahmad, Fauzia ; Aboutanios, Elias
Author_Institution :
Sch. of Electr. Eng., Univ. of New South Wales, Sydney, NSW, Australia
Abstract :
In this paper, we utilize Bayesian Compressive Sensing (BCS) for direction-of-arrival (DOA) estimation based on the coarray. This enables estimation of more sources than the number of physical antennas. We adopt the covariance vectorization technique to construct the received signal vectors of coarrays for both fully and partially augmentable arrays. We then apply the single measurement vector BCS (SMV-BCS) for DOA estimation. Supporting simulation results for both sparse linear arrays and circular arrays demonstrate the effectiveness of the proposed approach in terms of high resolution and estimation accuracy compared to the MUSIC and sparse signal reconstruction based methods.
Keywords :
Bayes methods; compressed sensing; covariance analysis; direction-of-arrival estimation; vectors; Bayesian compressive sensing; DOA estimation; MUSIC; SMV-BCS; circular arrays; coarrays; covariance vectorization technique; direction-of-arrival estimation; received signal vectors; single measurement vector BCS; sparse linear arrays; sparse signal reconstruction based methods; Antennas; Dictionaries; Teleworking; Bayesian compressive sensing; DOA estimation; coarray; covariance vectorization; single vector measurement;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178398