Orientation Matters: Learning Radiation Patterns of Multi-Rotor UAVs In-Flight to Enhance Communication Availability Modeling

2026-04-03

AI Summary

This study addresses the challenge posed by dynamic changes in antenna radiation patterns due to attitude variations of multirotor UAVs during flight, which significantly affect communication modeling and link prediction. The authors propose a novel method for simultaneous learning and decoupling of heterogeneous quadrotor radiation patterns by designing jointly calibrated trajectories to collect in-flight data in an anechoic, isotropic environment. Radiation patterns are modeled using either spherical harmonic expansions or induced sample-weighted averaging, and linear regression is employed to concurrently estimate the individual radiation patterns of two distinct UAVs. This approach enables, for the first time, online decoupling of heterogeneous UAV radiation patterns during flight and facilitates rapid recalibration following payload modifications. Experimental results on real-world datasets demonstrate a root-mean-square error of 3.6 dB, approaching the lower bound imposed by measurement noise, thereby validating the method’s effectiveness and practical feasibility.

Abstract

The paper presents an approach for learning antenna Radiation Patterns (RPs) of a pair of heterogeneous quadrotor Uncrewed Aerial Vehicles (UAVs) by calibration flight data. RPs are modeled either as a Spherical Harmonics series or as a weighted average over inducing samples. Linear regression of polynomial coefficients simultaneously decouples the two independent UAVs' RPs. A joint calibration trajectory exploits available flight time in an obstacle-free anechoic altitude. Evaluation on a real-world dataset demonstrates the feasibility of learning both radiation patterns, achieving 3.6 dB RMS error, the measurement noise level. The proposed RP learning and decoupling can be exploited in rapid recalibration upon payload changes, thereby enabling precise autonomous path planning and swarm control in real-world applications where setup changes are expected.

Problem

• Radiation Patterns
• UAVs
• Communication Availability
• In-Flight Calibration
• Antenna Modeling

Innovation

• Radiation Patterns
• Spherical Harmonics
• UAV Calibration
• Decoupling
• Autonomous Path Planning