A Single-Anchor Cooperative Positioning Method Based on Optimized Inertial Measurement for UAVs

Abstract

Benefiting from its structural simplicity and low cost, the inertial/ranging integrated navigation system is widely utilized in multi-agent applications, particularly in unmanned aerial vehicles (UAVs). As the deployment of UAVs in complex environments becomes more prevalent, accurate positioning in sparse observation scenarios has become increasingly important. In satellite-denied environments with few anchors, traditional filtering methods for positioning suffer from poor effectiveness due to the lack of constraints. This article proposes a method to enhance positioning accuracy in such environments by optimizing the inertial outputs of each UAV. The optimization process is based on the range measurements between the UAVs and a single anchor. By solving the optimization function derived using Bayesian theory, the optimized inertial outputs of the UAVs can be obtained. These optimized inertial data are then used in place of the original measurements for position estimation in the filter, resulting in improved performance. Simulation and real-world experiments validate that the proposed method can enhance UAVs’ positioning accuracy in single-anchor environments, surpassing the performance of a single optimizer or filter. Furthermore, the positions estimated by cooperative agents demonstrate higher accuracy than those estimated by individual agents, as more ranging measurements are incorporated.