Autonomous 3D Moving Target Encirclement and Interception with Range measurement

TL;DR

This paper presents an autonomous 3D drone strategy for detecting, encircling, and neutralizing hostile UAVs in complex conditions like GPS denial, validated through real-world experiments and simulations.

Contribution

It introduces a novel 3D encirclement and interception strategy using noisy distance measurements and adaptive control, effective in GPS-denied and non-line-of-sight scenarios.

Findings

Effective detection and interception demonstrated in real-world UAV experiments.

Adaptive encirclement control enables transition from protection to neutralization.

Strategy maintains robustness under noisy distance measurements.

Abstract

Commercial UAVs are an emerging security threat as they are capable of carrying hazardous payloads or disrupting air traffic. To counter UAVs, we introduce an autonomous 3D target encirclement and interception strategy. Unlike traditional ground-guided systems, this strategy employs autonomous drones to track and engage non-cooperative hostile UAVs, which is effective in non-line-of-sight conditions, GPS denial, and radar jamming, where conventional detection and neutralization from ground guidance fail. Using two noisy real-time distances measured by drones, guardian drones estimate the relative position from their own to the target using observation and velocity compensation methods, based on anti-synchronization (AS) and an X$-$Y circular motion combined with vertical jitter. An encirclement control mechanism is proposed to enable UAVs to adaptively transition from encircling and protecting a target to encircling and monitoring a hostile target. Upon breaching a warning threshold, the UAVs may even employ a suicide attack to neutralize the hostile target. We validate this strategy through real-world UAV experiments and simulated analysis in MATLAB, demonstrating its effectiveness in detecting, encircling, and intercepting hostile drones. More details: https://youtu.be/5eHW56lPVto.