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A Study on Intelligent Anti-Drone System using AI-based Long-Range Detection and Identification

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dc.contributor.advisor 최지웅 -
dc.contributor.author Woo-Cheol Jin -
dc.date.accessioned 2026-01-23T10:54:16Z -
dc.date.available 2026-01-23T10:54:16Z -
dc.date.issued 2026 -
dc.identifier.uri https://scholar.dgist.ac.kr/handle/20.500.11750/59625 -
dc.identifier.uri http://dgist.dcollection.net/common/orgView/200000943818 -
dc.description Anti-UAV System, Radar, Camera, RF Scanner, Jammer -
dc.description.tableofcontents 1. Introduction 1
1.1 Background and Motivation 1
1.2 Components of an Anti-Drone System 2
1.3 Characteristics of Anti-Drone System Components 3
1.4 Contributions of this Dissertation 5
2. Radar: AI-Based Long-Range Detection 8
2.1 Theoretical Background 8
2.2 System Model 12
2.2.1 Angle Estimation via 2D MUSIC Algorithm 17
2.3 Conventional Spatial Detection Algorithms: CFAR and DBSCAN 18
2.4 Proposed Method: Spatiotemporal Detection Algorithm with Angular Constraints 21
2.4.1 Concept and Motivation 21
2.4.2 3D-DCNN Architecture for Spatiotemporal Filtering 24
2.5 Experimental Environment and Scenario 26
2.5.1 Hardware: The TORIS AESA Radar System 27
2.5.2 Field Test Scenario 28
2.6 Experiment Results 29
2.6.1 Performance Evaluation Metrics 29
2.6.2 Experiment Result 30
2.7 Chapter Summary 34
3. Radio Frequency Signal Scanner: Long-Range Detection 36
3.1 Theoretical Background 36
3.2 System Model 39
3.3 Detection and DOA Estimation using MUSIC 41
3.3.1 MUSIC algorithm 41
3.4 Hardware Implementation 43
3.4.1 Antenna Array Design 44
3.4.2 RF Module and Signal Acquisition 47
3.5 Experimental Setup 48
3.6 Experimental Results and Discussion 49
3.6.1 Detection Performance Results 49
3.6.2 Theoretical Analysis of Multipath-Induced Elevation Error 52
3.7 Chapter Summary 57
4. Infrared Camera: Motion-Based Bird-Drone Classification for Long- Range Surveillance 59
4.1 Theoretical Background 59
4.2 System Model 61
4.3 Proposed Spatiotemporal Identification Algorithm 64
4.3.1 Spatio-Temporal Classification using Fourier Descriptors 67
4.3.2 CNN Architecture for Motion Pattern Classification 71
4.3.3 Appearance-Based Classification using 2D-CNN 72
4.4 Analysis of Classification Results 73
4.5 Chapter Summary 76
5. Jammer: Robust Directional Jamming Strategies Against UAV Location Inaccuracy 78
5.1 System Model 80
5.2 Radar Detection Process 81
5.2.1 Radar System Model 81
5.2.2 Radar based UAV Detection Process 83
5.3 Conventional Beam Control Schemes 84
5.3.1 Directional Antenna-based Beam Control Scheme (DA) 85
5.3.2 Beamforming based Beam Control Scheme (Steering) 87
5.4 Beam Control Scheme Considering Location Information Inaccuracy 88
5.4.1 Jamming Region Determination 89
5.4.2 Proposed Beam Control Scheme with Adaptive Beamwidth 90
5.4.3 Woodward-Lawson Method (WL) 92
5.4.4 Fourier Transform Method 93
5.4.5 Parks-McClellan Algorithm (PM) 94
5.4.6 Random Beam Control Scheme with Conventional Method 97
5.5 Performance Evaluation 98
5.6 Chapter Summary 108
6. Conclusion 110
6.1 Summary of the Dissertation 110
6.2 Contributions and Significance 111
6.3 Limitations and Future Work 112
References 114
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dc.format.extent 124 -
dc.language eng -
dc.publisher DGIST -
dc.title A Study on Intelligent Anti-Drone System using AI-based Long-Range Detection and Identification -
dc.title.alternative AI 기반 장거리 탐지 및 식별 기술을 이용한 지능형 안티드론 시스템 연구 -
dc.type Thesis -
dc.identifier.doi 10.22677/THESIS.200000943818 -
dc.description.degree Doctor -
dc.contributor.department Department of Electrical Engineering and Computer Science -
dc.date.awarded 2026-02-01 -
dc.publisher.location Daegu -
dc.description.database dCollection -
dc.citation XT.ID 진66 202602 -
dc.date.accepted 2026-01-19 -
dc.contributor.alternativeDepartment 전기전자컴퓨터공학과 -
dc.subject.keyword Anti-UAV System, Radar, Camera, RF Scanner, Jammer -
dc.contributor.affiliatedAuthor Woo-Cheol Jin -
dc.contributor.affiliatedAuthor Ji-Woong Choi -
dc.contributor.alternativeName 진우철 -
dc.contributor.alternativeName Ji-Woong Choi -
dc.rights.embargoReleaseDate 2031-02-28 -
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