A Robust Framework to Design Optimal Radar Deployment for Range-Based Target Localization Technique

In this paper, the problem of designing the optimal positions of monostatic radars composing a multiplatform network is pursued. Leveraging the CRB of the target position based on radar range measurements, two different figures of merit (independent of the actual target location) are considered. Unlike the state-of-the-art techniques, which usually rely on the restrictive assumption that the target is at the center of the sensing region and study the determination of the optimal angular orientation of the nodes, a new approach to design the optimal radar deployment (without knowing target location) is developed. Specifically, a region where the target is likely to be present is considered and either the trace of the CRB averaged over the grid points sampling the surveillance area (shortly average CRB), or the maximum trace of CRB over the mentioned grid points (shortly worst-case CRB) is minimized. Hence, an optimization framework based on block majorization-minimization (referred to as block-MM) is proposed to deal with the formulated resource allocation problems. Remarkably, regardless of the considered figures of merit, the design objective decreases monotonically along the iteration steps of the proposed algorithm. The developed methodology can also efficiently handle the case of nonuniform measurement noise. Finally, via numerical simulations, the effectiveness of the developed methods is shown.