@conference{10902/18037,
year = {2019},
url = {http://hdl.handle.net/10902/18037},
abstract = {This paper addresses the problem of source enumeration by an array of sensors in the challenging conditions of: i) large uniform arrays with few snapshots, and ii) non-white or spatially correlated noises with arbitrary correlation. To solve this problem, we combine a subspace averaging (SA) technique, recently proposed for the case of independent and identically distributed (i.i.d.) noises, with a majority vote approach. The number of sources is detected for increasing dimensions of the SA technique and then a majority vote is applied to determine the final estimate. As illustrated by some simulation examples, this simple modification makes SA a very robust method of enumerating sources in these challenging scenarios.},
organization = {This work was supported by the Ministerio de Economía y Competitividad (MINECO) of Spain, and AEI/FEDER funds of the E.U., under grants TEC2016-75067-C4-4-R (CARMEN) and BES-2017-080542.},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
publisher = {27th European Signal Processing Conference (EUSIPCO), A Coruña, 2019, 1-5.},
title = {Source enumeration in non-white noise and small sample size via subspace averaging},
author = {Garg, Vaibhav and Santamaría Caballero, Luis Ignacio},
}