Second-Order Characterization of Micro Doppler Radar Signatures of Drone Swarms

We propose an analytic model for the second-order characteristics of the radar return signal from a swarm of rotor drones. We consider the case of a swarm of identical drones, with each a number of rotors comprised of a number of rotor blades. By considering the orientation and speed of each rotor as stochastic variables, we derive expressions for the autocorrelation function (ACF) and power spectral density (PSD). The ACF and PSD are in the form of an infinite series with coefficients that drop to zero at a predictable limit. Thus in practical applications, the series may be truncated. As a special case, we show that for deterministic rotor speed, the ACF can be expressed in closed form. We further investigate how system parameters (Blade length, Rotor speed, number of blades, and number of drones) influence the derived expressions for the ACF and PSD.

Authors

Institutions

Publication Details

Journal
IEEE Signal Processing Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lsp.2025.3596514
Primary Topic
Radio Astronomy Observations and Technology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Second-Order Characterization of Micro Doppler Radar Signatures of Drone Swarms

Troels Pedersen, Anders Malthe Westerkam, Rasmus Erik Villadsen, Alba Spliid Damkjær
IEEE Signal Processing Letters
Radio Astronomy Observations and Technology
article

Second-Order Characterization of Micro Doppler Radar Signatures of Drone Swarms

Troels Pedersen, Anders Malthe Westerkam, Rasmus Erik Villadsen, Alba Spliid Damkjær
article en

Abstract

We propose an analytic model for the second-order characteristics of the radar return signal from a swarm of rotor drones. We consider the case of a swarm of identical drones, with each a number of rotors comprised of a number of rotor blades. By considering the orientation and speed of each rotor as stochastic variables, we derive expressions for the autocorrelation function (ACF) and power spectral density (PSD). The ACF and PSD are in the form of an infinite series with coefficients that drop to zero at a predictable limit. Thus in practical applications, the series may be truncated. As a special case, we show that for deterministic rotor speed, the ACF can be expressed in closed form. We further investigate how system parameters (Blade length, Rotor speed, number of blades, and number of drones) influence the derived expressions for the ACF and PSD.

IEEE Signal Processing LettersVol. 32
Aalborg University (DK)
Openalex Percentile: Top 86%
Radio Astronomy Observations and Technology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Second-Order Characterization of Micro Doppler Radar Signatures of Drone Swarms — Troels Pedersen, Anders Malthe Westerkam, et al. · IEEE Signal Processing Letters (2025) | TGRS Research Map | TGRS