Passive Radar for Drone Detection and Classification

The proliferation of drones in civilian and military applications has increased the needfor effective detection and classification systems that can work 24/7 in all weather conditions. Passive radar systems, exploiting existing radio frequency emitters, offer a cost-effective and covert solution for this challenge. This paper uses micro-Doppler signatures induced by drone propellers as a distinctive feature for drone detection and classification. The detailed analysis of micro-Doppler effects is presented in the paper, together with the implementation guidelines and real-life example data analyses. Experimental results highlight the system's capability to detect and classify drones based on their micro-Doppler characteristics, offering a promising approach to enhancing situational awareness and security in civilian and military applications.

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Publication Details

Published
2025-05-21
DOI
https://doi.org/10.23919/irs64527.2025.11046011
Citations
1
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
4.99
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article

Passive Radar for Drone Detection and Classification

Krzysztof Kulpa, Marcin Bączyk, Mateusz Malanowski
1 citations
Radar Systems and Signal Processing
4.99
article

Passive Radar for Drone Detection and Classification

Krzysztof Kulpa, Marcin Bączyk, Mateusz Malanowski
article en
1 citations

Abstract

The proliferation of drones in civilian and military applications has increased the needfor effective detection and classification systems that can work 24/7 in all weather conditions. Passive radar systems, exploiting existing radio frequency emitters, offer a cost-effective and covert solution for this challenge. This paper uses micro-Doppler signatures induced by drone propellers as a distinctive feature for drone detection and classification. The detailed analysis of micro-Doppler effects is presented in the paper, together with the implementation guidelines and real-life example data analyses. Experimental results highlight the system's capability to detect and classify drones based on their micro-Doppler characteristics, offering a promising approach to enhancing situational awareness and security in civilian and military applications.

Warsaw University of Technology (PL)
Openalex Percentile: Top 6%
Radar Systems and Signal Processing
4.99
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