@conference {553,
	title = {Source Enumeration in Non-White Noise and Small Sample Size via Subspace Averaging},
	booktitle = {European Signal Processing Conference (EUSIPCO)},
	year = {2019},
	month = {September},
	address = {La Coru{\~n}a, Spain},
	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.},
	author = {Garg, Vaibhav and Santamar{\'\i}a, Ignacio}
}
