2023 APS Logo

IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

July 23–28, 2023 • Portland, Oregon, USA

23-28 July 2023 • Portland, Oregon, USA

IEEE AP-S/URSI 2023

23-28 July 2023 • Portland, Oregon, USA

TU-A4.1P.7

A Comparison of Machine Learning Algorithms for Micro-Doppler Based Drone Classification

Mohammed Rashid, Jeffrey A. Nanzer, Michigan State University, United States
Session:
Radar Cross Section and Target Characterization
Track:
AP-S: Propagation & Scattering
Location:
A 105 (OCC)
Session Time:
Tue, 25 Jul, 13:20 - 17:00 PDT (UTC -7)
Presentation Time:
Tue, 25 Jul, 15:40 - 16:00 PDT (UTC -7)
Session Co-Chairs:
Edwin Marengo, Northeastern University and Mohammed Rashid, Michigan State University
Presentation
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Discussion
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Session TU-A4.1P
TU-A4.1P.1: Application of Vector Radiative Transfer Theory for Real-time Chaff Cloud Simulation
Jun-Seon Kim, Dong-Yeob Lee, Dong-Wook Seo, Korea Maritime and Ocean University, Korea (South)
TU-A4.1P.2: Efficient Full-Wave Computation of the Monostatic Radar Cross Section
Asger Limkilde, Oscar Borries, Peter Meincke, Erik Jørgensen, TICRA, Denmark
TU-A4.1P.3: Free-Running X-Band Electric Field Mapping with Acoustically Modulated Scattering
Yu Huang, Tingyou Guo, Yuchen Gu, Alan Bettermann, Daniel van der Weide, University of Wisconsin at Madison, United States
TU-A4.1P.4: An Application of Angular Network Equations: Exact Solution of the PEC Wedge in Biaxial Media
Vito Daniele, Guido Lombardi, Politecnico di Torino, Italy
TU-A4.1P.5: Recovery of Missing Radar Returns with Compressive Sensing
Ismail Jouny, Lafayette College, United States
TU-A4.1P.6: Radar change detection in the time domain
Edwin Marengo, David Tahmoush, Northeastern University, United States
TU-A4.1P.7: A Comparison of Machine Learning Algorithms for Micro-Doppler Based Drone Classification
Mohammed Rashid, Jeffrey A. Nanzer, Michigan State University, United States
Resources
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