Advances in UAV-Assisted Localization: Joint Source and UAV Parameter Estimation

Abstract

This paper presents efficient estimators to address the problem of source localization aided by unmanned aerial vehicles (UAVs) with unknown location parameters. Leveraging semidefinite relaxation technique and successive weighted least squares estimation, the source and UAV parameters are simultaneously estimated in both mixed line-of-sight/non-line-of-sight (NLOS) and NLOS scenarios. The proposed estimators are shown to approximately achieve the Cramer-Rao bound (CRB) under mild Gaussian noise conditions when the measurement noises are small compared to the associated ranges. Numerical simulations demonstrate that localization without prior UAV location information is still possible with a meter-level positioning and sub-meter per seconds velocity estimation accuracy.