Sensor Placement Strategies for Target Localization via 3-D AOA Measurements

In this article, we present a numerically efficient approach to optimally place wireless sensors for 3-D angle-of-arrival target localization. The proposed algorithm employs a block majorization–minimization method, in which each subproblem corresponding to a specific block involves a tailored surrogate of the objective function restriction. Unlike existing methods that focus solely on A-optimal design criteria, the proposed architecture can also be extended to handle the D-optimal design and exploits a bespoke parameterization in terms of trigonometric functions. This resulting algorithm has an iterative structure and provides, at each step a closed-form solution for sensors' azimuth and elevation angles, ensuring guaranteed convergence. Extensive numerical simulations are conducted to demonstrate the effectuality of the placement algorithm in scenarios involving uniform and nonuniform noise, as well as diverse receiver-target distances. The results indicate that this technique can outperform existing methods, particularly in terms of computational complexity, and appears well-suited for practical applications.