GNSS-denied geolocalization of UAVs by visual matching of onboard camera images with orthophotos

TL;DR

This paper introduces a GNSS-free UAV localization method using onboard camera images and orthophotos, employing a Monte-Carlo approach that relaxes camera orientation constraints and relies solely on inertial data and map matching.

Contribution

It presents a novel Monte-Carlo localization technique that enables UAVs to localize without GNSS, using arbitrary camera orientation and orthorectified images based on environment planarity.

Findings

Successfully localizes UAVs globally with modest initialization

Requires only inertial measurements, a non-downward camera, and orthophotos

Achieves reliable localization with low map resolution

Abstract

Localization of low-cost Unmanned Aerial Vehicles (UAVs) often relies on Global Navigation Satellite Systems (GNSS). GNSS are susceptible to both natural disruptions to radio signal and intentional jamming and spoofing by an adversary. A typical way to provide georeferenced localization without GNSS for small UAVs is to have a downward-facing camera and match camera images to a map. The downward-facing camera adds cost, size, and weight to the UAV platform and the orientation limits its usability for other purposes. In this work, we propose a Monte-Carlo localization method for georeferenced localization of an UAV requiring no infrastructure using only inertial measurements, a camera facing an arbitrary direction, and an orthoimage map. We perform orthorectification of the UAV image, relying on a local planarity assumption of the environment, relaxing the requirement of downward-pointing camera. We propose a measure of goodness for the matching score of an orthorectified UAV image and a map. We demonstrate that the system is able to localize globally an UAV with modest requirements for initialization and map resolution.