Using real spatial correlation matrices for improved array processing

The authors examine the maximum number of signals whose parameters can be estimated with a linear, equally spaced array of M sensors. The conventional view is that, when none of the signals is fully correlated, this number is one less than the number of sensors; however, the authors show how to make the extension to one less than twice the number of sensors. This increase in the number of signals is accomplished by using length 2M real signal vectors rather than the usual length M complex vectors. It is shown that 2M of these real vectors are linearly independent with probability one, and, thus, angles of arrival can be unambiguously estimated for 2M-1 signals