Modelling Micro-Doppler Signature of Drone Propellers in Distributed ISAC

TL;DR

This paper introduces a mathematical model for the micro-Doppler signatures of drone propellers, aiding target classification in integrated sensing and communication systems by generating realistic data for algorithm development.

Contribution

The paper presents a novel mathematical model for drone propeller micro-Doppler signatures and validates it against real measurements, enhancing data generation for target classification algorithms.

Findings

Model accurately replicates measured micro-Doppler signatures

Generated data closely matches real-world measurements

Supports development of target classification algorithms

Abstract

Integrated Sensing and Communication (ISAC) comprises detection and analysis of non-cooperative targets by exploiting the resources of the mobile radio system. In this context, micro-Doppler is of great importance for target classification, in order to distinguish objects with local movements. For developing algorithms for target classification, it is necessary to have a large amount of target signatures. Aiming to generate these data, this paper proposes a mathematical model for the micro-Doppler of drone rotating propellers, and validate the proposed model by comparing it to measured micro-Doppler. Results show that the proposed mathematical model can generate micro-Doppler data very similar to those from measurement data.