Towards a Self-rescuing System for UAVs Under GNSS Attack

TL;DR

This paper introduces a lightweight, autonomous rescue system for UAVs that can recover from GNSS spoofing or jamming attacks by returning to the takeoff point, even under windy conditions, ensuring safety and mission success.

Contribution

The paper presents the first autonomous self-rescue system for UAVs under GNSS attacks, combining a two-phase route planning method that accounts for wind effects with fast computation.

Findings

Successfully returns UAVs to takeoff point under GNSS attack

Effective in windy conditions with minimal computation delay

First autonomous rescue solution for GNSS-compromised UAVs

Abstract

There has been substantial growth in the UAV market along with an expansion in their applications. However, the successful execution of a UAV mission is very often dependent on the use of a GNSS. Unfortunately, the vulnerability of GNSS signals, due to their lack of encryption and authentication, poses a significant cybersecurity issue. This vulnerability makes various attacks, particularly the "GNSS spoofing attack," and "GNSS jamming attack" easily executable. Generally speaking, during this attack, the drone is manipulated into altering its path, usually resulting in an immediate forced landing or crash. As far as we know, we are the first to propose a lightweight-solution that enable a drone to autonomously rescue itself, assuming it is under GNSS attack and the GNSS is no longer available, and return safely to its initial takeoff position, thereby preventing any potential crashes. During the flight, wind plays a critical role as it can instantaneously alter the drone's position. To solve this problem, we have devised a highly effective 2-phases solution: (i) Forward Phase, for monitoring and recording the forward journey, and (ii) Backward Phase, that generates a backward route, based on the Forward Phase and wind presence. The final solution ensures strong performance in consistently returning the drone to the original position, even in wind situations, while maintaining a very fast computation time.