  Herein, the problem of simultaneous localization of two sources given a
modest number of samples is examined. In particular, the strategy does not
require knowledge of the target signatures of the sources a priori, nor does it
exploit classical methods based on a particular decay rate of the energy
emitted from the sources as a function of range. General structural properties
of the signatures such as unimodality are exploited. The algorithm localizes
targets based on the rotated eigenstructure of a reconstructed observation
matrix. In particular, the optimal rotation can be found by maximizing the
ratio of the dominant singular value of the observation matrix over the nuclear
norm of the optimally rotated observation matrix. It is shown that this ratio
has a unique local maximum leading to computationally efficient search
algorithms. Moreover, analytical results are developed to show that the squared
localization error decreases at a rate faster than the baseline scheme.
