Convex Combination Based Target Localization with Noisy Angle of Arrival Measurements
Target localization based on angle of arrival (AoA) is an important branch of location estimation research. Due to the noisy measurements from sensors and the non-linear inverse trigonometry function, the AoA-based localization induces a non-convex optimization that is difficult to solve with both high speed and accuracy simultaneously. To achieve a fast and accurate algorithm, we propose a convex combination scheme. By introducing a highly accurate linear approximation to the inverse trigonometric function, the objective is converted to a convex function, which can be solved efficiently with linear least-squares approach. The key point of the convex combination scheme is to express the coordinate of the target as the convex combination of a set of virtual anchors around its real position. Simulations demonstrate that the accuracy of this method is very close to the Cramer-Rao lower bound and that the comprehensive performance, including the accuracy and speed, is significantly improved compared to other state-of-the-art methods.