A New Iterative Weighted Least Squares Algorithm for 1-D SA Localization

Three-dimensional (3-D) target localization using one-dimensional (1-D) space angle (SA) measurements from linear arrays has recently gained significant attention. Each 1-D SA measurement defines a conical surface, and the intersection of multiple such surfaces determines the target's location in 3-D space. However, state-of-the-art methods for solving the 1-D SA localization problem are often either suboptimal or computationally intensive. In this paper, we propose a novel iterative weighted least squares (IWLS) algorithm to address the problem. To provide deeper insights, we present a geometric interpretation of the iterative process, highlighting its physical significance. Furthermore, we analyze the computational complexity of the proposed algorithm and compare it with existing methods. Simulation results demonstrate that the proposed algorithm not only achieves higher estimation accuracy but also requires less computational time compared to state-of-the-art approaches.