Source Enumeration in Non-White Noise and Small Sample Size via Subspace Averaging

Vaibhav Garg, Ignacio Santamaria
2019 2019 27th European Signal Processing Conference (EUSIPCO)  
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
more » ... sions 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.
doi:10.23919/eusipco.2019.8903064 dblp:conf/eusipco/GargS19 fatcat:xukasm3z45dbzoftzppbqtb2yq