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Title: :  Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data
PaperId: :  23564
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-23564
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Prajwal G KoppaDayananda Sagar Academy of Technology and Management
Dr. Ravikumar H C Dayananda Sagar Academy of Technology and Management

Abstract

AIML
UAV classification, micro-Doppler signatures, range–Doppler images, machine learning, radar simulations, Doppler spectrum, ground-based surveillance radar, FMCW radar, CNN.
This research investigates the classification of unmanned aerial vehicles (UAVs) using micro-Doppler signatures, a crucial technique for discerning between different types of UAVs. Through the utilization of a full-wave electromagnetic CAD tool, we explore the influence of control systems on the range–Doppler signatures of various UAV configurations, including quadcopters, hexacopters, and helicopters. Our approach integrates a mechanical control-based machine learning (ML) algorithm, with convolutional neural networks (CNNs) demonstrating robust performance, achieving classification accuracies exceeding 90%. Additionally, we introduce a novel methodology for simulating radar datasets using CAD tools, enabling the generation of diverse datasets tailored to different drone types and radar parameters. Leveraging a simulated 77 GHz frequency-modulated continuous wave (FMCW) radar, our classification model attains an accuracy of over 97%. We establish a theoretical framework linking micro-Doppler signatures with UAV motion dynamics, providing insights into spectral distribution. Experimental analysis, combining simulations and measured data, underscores the potential for effective detection and classification. Furthermore, we propose a ground-based surveillance radar system for drone detection, surpassing existing methods in both accuracy and computational efficiency. Validation through field experiments with a commercial portable radar underscores the viability and effectiveness of our approach. Overall, this study contributes to advancing UAV classification techniques and enhancing drone detection capabilities in practical scenarios.

Citations

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IJARIIE Prajwal G Koppa, and Dr. Ravikumar H C . "Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 5212-5226
MLA Prajwal G Koppa, and Dr. Ravikumar H C . "Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 5212-5226.
APA Prajwal G Koppa, & Dr. Ravikumar H C . (2024). Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 5212-5226.
Chicago Prajwal G Koppa, and Dr. Ravikumar H C . "Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 5212-5226.
Oxford Prajwal G Koppa, and Dr. Ravikumar H C . 'Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 5212-5226. Available from IJARIIE, http://ijariie.com/AdminUploadPdf/Advancements_in_UAV_Detection_and_Classification__Fusion_of_Mechanical_Control_and_Sensor_Data_ijariie23564.pdf (Accessed : ).
Harvard Prajwal G Koppa, and Dr. Ravikumar H C . (2024) 'Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 5212-5226IJARIIE [Online]. Available at: http://ijariie.com/AdminUploadPdf/Advancements_in_UAV_Detection_and_Classification__Fusion_of_Mechanical_Control_and_Sensor_Data_ijariie23564.pdf (Accessed : )
IEEE Prajwal G Koppa, and Dr. Ravikumar H C , "Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 5212-5226, Mar-App 2024. [Online]. Available: http://ijariie.com/AdminUploadPdf/Advancements_in_UAV_Detection_and_Classification__Fusion_of_Mechanical_Control_and_Sensor_Data_ijariie23564.pdf [Accessed : ].
Turabian Prajwal G Koppa, and Dr. Ravikumar H C . "Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 ().
Vancouver Prajwal G Koppa, and Dr. Ravikumar H C . Advancements in UAV Detection and Classification: Fusion of Mechanical Control and Sensor Data. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(2) : 5212-5226. Available from: http://ijariie.com/AdminUploadPdf/Advancements_in_UAV_Detection_and_Classification__Fusion_of_Mechanical_Control_and_Sensor_Data_ijariie23564.pdf
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