Source Enumeration in Non-White Noise and Small Sample Size via Subspace Averaging
| Title | Source Enumeration in Non-White Noise and Small Sample Size via Subspace Averaging |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Garg, V., and I. Santamaría |
| Conference Name | European Signal Processing Conference (EUSIPCO) |
| Month Published | September |
| Conference Location | La Coruña, 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. |
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