A polynomial rooting approach to super-resolution array design

This paper is concerned with the design of super-resolution direction finding (DF) arrays that satisfy prespecified performance levels, such as detection-resolution thresholds and Cramér–Rao bounds on error variance. The sensor placement problem is formulated in the framework of subspace-based DF techniques and a novel polynomial rooting approach to the design problem, based on the new concept of the “sensor locator polynomial (SLP),” is proposed. This polynomial is constructed using the prespecified performance levels, and its roots yield the sensor locations of the desired array. The distinguishing feature of the proposed technique is that it hinges on the properties of the array manifold, which plays a central role in all subspace-based DF algorithms.