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Detection and Localization of Drones in MIMO CW Radar
Date
2023-01-01
Author
Yazici, Ayhan
Baykal, Buyurman
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Low radar cross section and capability to fly at low speeds make drones challenging targets for radar detection. In the presence of ground moving targets the frequency spectrum is also crowded which makes the detection of the drones more difficult. Micro-Doppler effect is the main feature used to discriminate drone from other targets and clutter. Typically discrimination is performed after the detection of all the targets. Especially in target dense environments, such as cities, typical approach requires high processing power in order to detect and classify all of the targets. Coverage is also another problem of the typical monostatic radar based drone detection in cities. Coverage of monostatic radar is easily blocked by buildings. In order to cope with these problems distributed multi-input multi-output (MIMO) continuous wave (CW) radar using MIMO cyclic spectral density (CSD) analysis (MCSD) method is proposed in this paper. MCSD method detects and classifies drones using the cyclic frequency information. In order to make the system simple and low cost, a network of continuous wave radars is used and the localization is performed based on Doppler only localization approach. The simulations and experimental results demonstrate the proof of the concept. Performance and cost analyses of the MCSD method are also elaborated in the paper.
Subject Keywords
Airborne radar
,
Cyclostationary
,
deinterleaving
,
Doppler-only localization
,
Drone detection
,
Drones
,
Mathematical models
,
MIMO radar
,
Propellers
,
Radar
,
Radar cross-sections
,
Radar detection
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85174849517&origin=inward
https://hdl.handle.net/11511/106271
Journal
IEEE Transactions on Aerospace and Electronic Systems
DOI
https://doi.org/10.1109/taes.2023.3321586
Collections
Department of Electrical and Electronics Engineering, Article
Citation Formats
IEEE
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BibTeX
A. Yazici and B. Baykal, “Detection and Localization of Drones in MIMO CW Radar,”
IEEE Transactions on Aerospace and Electronic Systems
, pp. 0–0, 2023, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85174849517&origin=inward.