@conference {514,
	title = {Subspace Averaging for Source Enumeration in Large Arrays},
	booktitle = {IEEE Statistical Signal Processing Workshop (SSP)},
	year = {2018},
	month = {June},
	address = {Freiburg, Germany},
	abstract = {Subspace averaging is proposed and examined as a method of enumerating sources in large linear arrays, under conditions of low sample support. The key idea is to exploit shift invariance as a way of
extracting many subspaces, which may then be approximated by a
single extrinsic average. An automatic order determination rule for
this extrinsic average is then the rule for determining the number
of sources. Experimental results are presented for cases where the
number of array snapshots is roughly half the number of array elements, and sources are well separated with respect to the Rayleigh
limit.},
	author = {Santamar{\'\i}a, Ignacio and Ram{\'\i}rez, David and Louis L. Scharf}
}
