Fast IPPM for Distributed Cooperative Localization With Hybrid Information

Abstract

This letter addresses the problem of distributed cooperative localization using the joint range and angle measurements. With the appealing properties of fully distributed implementation and low complexity at each agent, a convex formulation named fast iterative parallel projection method (FastIPPM) is exploited to solve the cooperative localization problem. In pursuit of faster convergence, gradient descent with momentum is utilized. Simulation results validate the superior performance of the proposed algorithm compared with existing ones. After adopting the acceleration techniques, the FastIPPM shows a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times$ </tex-math></inline-formula> – <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\times$ </tex-math></inline-formula> speed-up. In addition, positioning accuracy and convergence stability in sparse networks have also been greatly enhanced.