Direction finding: a signal subspace approach

The classical direction-finding problem is concerned with the task of detecting and estimating the directions from which multiple energy wavefronts impinge on an array of sensors. The problem is formulated in the signal subspace, leading to a number of benefits, chief among which is the ability to resolve closely spaced coherent sources. In order to realize this potential, however, a parametric optimization problem must be solved. An effective nonlinear programming algorithm is developed for this purpose along with a parameter initialization procedure. Numerical examples are presented to demonstrate the superresolution capability of the signal subspace algorithm.<
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