Reinforcement Learning Based Non-Cooperative Radio Localization Assisted by UAV Swarm

Haoyu Chen

Keywords: Radio localization, unmanned aerial vehicles, received signal strength.

TL;DR: In this paper, we propose a non-cooperative radio localization scheme based on RSS

Abstract:

The accuracy of non-cooperative radio localization aided by unmanned aerial vehicles (UAVs) depends on the swarm size and the spatial distribution. In this paper, we propose a non-cooperative radio localization scheme that chooses the cooperative UAVs based on the received signal strength (RSS) of the radio device, previous shared RSS from neighboring UAVs, and the previous localization error to increase the accuracy with reduced energy consumption. Based on the weighted least squares approach, the position of the radio device is estimated to evaluate the localization error to formulate the cooperative UAVs selection distribution with increased accuracy.
Simulations based on the ten UAVs show that the proposed scheme decreases the root-mean-square error and energy consumption over the benchmark.

Submission Number: 5