| Download | - Will be available here on July 25, 2027
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| DOI | Resolve DOI: https://doi.org/10.1109/DSP65409.2025.11075208 |
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| Author | Search for: Pant, Shashank1ORCID identifier: https://orcid.org/0000-0003-3271-5011; Search for: Manning, Max; Search for: Laliberte, JeremyORCID identifier: https://orcid.org/0000-0001-7265-8926; Search for: Sevigny, Pascale; Search for: Rajan, Sreeraman; Search for: Balaji, Bhashyam |
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| Affiliation | - National Research Council Canada. Aerospace
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| Format | Text, Article |
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| Conference | 25th International Conference on Digital Signal Processing (DSP 2025), June 25-27, 2025, Pylos (Messinia, Southwest Peloponnese), Greece |
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| Subject | drone detection; payload; portable radar; micro-Doppler; radar signal processing |
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| Abstract | In this study, a portable 66 GHz V-band radar was used to analyze the radar signatures of drones carrying four different types of payloads. Data collection took place outdoors using a DJI Mavic 2 drone to carry and release these payloads. In real aperture radar (RAR) images, drones with and without payloads appeared as indistinct blobs, which could be mistaken for any flying objects. To resolve this shortcoming, the micro-Doppler signature (spectrogram) generated by the drone's rotating propeller blades was used to detect and differentiate drones with and without payloads. Operating at a 5 cm range resolution, the radar could distinguish between the payload spectrogram and the drone spectrogram, each exhibiting unique signatures. These micro-Doppler signatures were consistent across all types of payloads, irrespective of their radar reflective properties, enabling the precise identification of the timing of various payload drops. |
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| Publication date | 2025-07-25 |
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| Publisher | IEEE |
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| Licence | - © 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Identifier | CPR-SMM-2025-0057 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | c7774c44-267c-4a2b-a79e-6bda343d66a7 |
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| Record created | 2025-12-02 |
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| Record modified | 2025-12-03 |
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