Sense and Avoid in UAS (eBook, PDF)

Research and Applications
Redaktion: Angelov, Plamen

• Format: PDF

Produktbeschreibung

There is increasing interest in the potential of UAV (Unmanned Aerial Vehicle) and MAV (Micro Air Vehicle) technology and their wide ranging applications including defence missions, reconnaissance and surveillance, border patrol, disaster zone assessment and atmospheric research. High investment levels from the military sector globally is driving research and development and increasing the viability of autonomous platforms as replacements for the remotely piloted vehicles more commonly in use. UAV/UAS pose a number of new challenges, with the autonomy and in particular collision avoidance, detect and avoid, or sense and avoid, as the most challenging one, involving both regulatory and technical issues. Sense and Avoid in UAS: Research and Applications covers the problem of detect, sense and avoid in UAS (Unmanned Aircraft Systems) in depth and combines the theoretical and application results by leading academics and researchers from industry and academia. Key features: * Presents a holistic view of the sense and avoid problem in the wider application of autonomous systems * Includes information on human factors, regulatory issues and navigation, control, aerodynamics and physics aspects of the sense and avoid problem in UAS * Provides professional, scientific and reliable content that is easy to understand, and * Includes contributions from leading engineers and researchers in the field Sense and Avoid in UAS: Research and Applications is an invaluable source of original and specialised information. It acts as a reference manual for practising engineers and advanced theoretical researchers and also forms a useful resource for younger engineers and postgraduate students. With its credible sources and thorough review process, Sense and Avoid in UAS: Research and Applications provides a reliable source of information in an area that is fast expanding but scarcely covered.

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Produktdetails

• Verlag: Wiley
• Seitenzahl: 384
• Erscheinungstermin: 6. März 2012
• Englisch
• ISBN-13: 9781119963950
• Artikelnr.: 37355669

Autorenporträt

Plamen Parvanov Angelov, Lancaster University, UK Plamen Parvanov is a senior lecturer in the School of Computing and Communications at Lancaster University. He is an Associate Editor of three international journals and the founding co-Editor-in-Chief of the Springer journal Evolving Systems. He is also the Vice Chair of the Technical Committee on Standards, Computational Intelligence Society, IEEE and co-Chair of several IEEE conferences. His research in UAV/UAS is often publicised in external publications, e.g. the prestigious Computational Intelligence Magazine; Aviation Week, Flight Global, Airframer, Flight International, etc. His research focuses on computational intelligence and evolving systems, and his research in to autonomous systems has received worldwide recognition. As the Principle Investigator at Lancaster University for a team working on UAV Sense and Avoid fortwo projects of ASTRAEA his work was recognised by 'The Engineer Innovation and Technology 2008 Award in two categories: i) Aerospace and Defence and ii) The Special Award which is an outstanding achievement.

Inhaltsangabe

Preface xv About the Editor xix About the Contributors xxi Part I Introduction 1 Introduction 3 George Limnaios, Nikos Tsourveloudis and Kimon P. Valavanis 1.1 UAV versus UAS 3 1.2 Historical Perspective on Unmanned Aerial Vehicles 5 1.3 UAV Classification 9 1.4 UAV Applications 14 1.5 UAS Market Overview 17 1.6 UAS Future Challenges 20 1.7 Fault Tolerance for UAS 26 References 31 2 Performance Tradeoffs and the Development of Standards 35 Andrew Zeitlin 2.1 Scope of Sense and Avoid 35 2.2 System Configurations 36 2.3 S&A Services and Sub-functions 38 2.4 Sensor Capabilities 39 2.4.1 Airborne Sensing 39 2.4.2 Ground-Based Sensing 41 2.4.3 Sensor Parameters 41 2.5 Tracking and Trajectory Prediction 42 2.6 Threat Declaration and Resolution Decisions 43 2.6.1 Collision Avoidance 43 2.6.2 Self-separation 45 2.6.3 Human Decision versus Algorithm 45 2.7 Sense and Avoid Timeline 46 2.8 Safety Assessment 48 2.9 Modeling and Simulation 49 2.10 Human Factors 50 2.11 Standards Process 51 2.11.1 Description 51 2.11.2 Operational and Functional Requirements 52 2.11.3 Architecture 52 2.11.4 Safety, Performance, and Interoperability Assessments 52 2.11.5 Performance Requirements 52 2.11.6 Validation 53 2.12 Conclusion 54 References 54 3 Integration of SAA Capabilities into a UAS Distributed Architecture for Civil Applications 55 Pablo Royo, Eduard Santamaria, Juan Manuel Lema, Enric Pastor and Cristina Barrado 3.1 Introduction 55 3.2 System Overview 57 3.2.1 Distributed System Architecture 58 3.3 USAL Concept and Structure 59 3.4 Flight and Mission Services 61 3.4.1 Air Segment 61 3.4.2 Ground Segment 65 3.5 Awareness Category at USAL Architecture 68 3.5.1 Preflight Operational Procedures: Flight Dispatcher 70 3.5.2 USAL SAA on Airfield Operations 72 3.5.3 Awareness Category during UAS Mission 75 3.6 Conclusions 82 Acknowledgments 82 References 82 Part II Regulatory Issues and Human Factors 4 Regulations and Requirements 87 Xavier Prats, Jorge Ramírez, Luis Delgado and Pablo Royo 4.1 Background Information 88 4.1.1 Flight Rules 90 4.1.2 Airspace Classes 91 4.1.3 Types of UAS and their Missions 93 4.1.4 Safety Levels 96 4.2 Existing Regulations and Standards 97 4.2.1 Current Certification Mechanisms for UAS 99 4.2.2 Standardization Bodies and Safety Agencies 102 4.3 Sense and Avoid Requirements 103 4.3.1 General Sense Requirements 103 4.3.2 General Avoidance Requirements 106 4.3.3 Possible SAA Requirements as a Function of the Airspace Class 108 4.3.4 Possible SAA Requirements as a Function of the Flight Altitude and Visibility Conditions 109 4.3.5 Possible SAA Requirements as a Function of the Type of Communications Relay 110 4.3.6 Possible SAA Requirements as a Function of the Automation Level of the UAS 111 4.4 Human Factors and Situational Awareness Considerations 112 4.5 Conclusions 113 Acknowledgments 114 References 115 5 Human Factors in UAV 119 Marie Cahillane, Chris Baber and Caroline Morin 5.1 Introduction 119 5.2 Teleoperation of UAVs 122 5.3 Control of Multiple Unmanned Vehicles 123 5.4 Task-Switching 124 5.5 Multimodal Interaction with Unmanned Vehicles 127 5.6 Adaptive Automation 128 5.7 Automation and Multitasking 129 5.8 Individual Differences 131 5.8.1 Attentional Control and Automation 131 5.8.2 Spatial Ability 134 5.8.3 Sense of Direction 135 5.8.4 Video Games Experience 135 5.9 Conclusions 136 References 137 Part III SAA Methodologies 6 Sense and Avoid Concepts: Vehicle-Based SAA Systems (Vehicle-to-Vehicle) 145 t
pán Kop
iva, David ilák and Michal P
choüek 6.1 Introduction 145 6.2 Conflict Detection and Resolution Principles 146 6.2.1 Sensing 146 6.2.2 Trajectory Prediction 147 6.2.3 Conflict Detection 148 6.2.4 Conflict Resolution 149 6.2.5 Evasion Maneuvers 150 6.3 Categorization of Conflict Detection and Resolution Approaches 150 6.3.1 Taxonomy 150 6.3.2 Rule-Based Methods 151 6.3.3 Game Theory Methods 152 6.3.4 Field Methods 153 6.3.5 Geometric Methods 154 6.3.6 Numerical Optimization Approaches 156 6.3.7 Combined Methods 158 6.3.8 Multi-agent Methods 160 6.3.9 Other Methods 163 Acknowledgments 166 References 166 7 UAS Conflict Detection and Resolution Using Differential Geometry Concepts 175 Hyo-Sang Shin, Antonios Tsourdos and Brian White 7.1 Introduction 175 7.2 Differential Geometry Kinematics 177 7.3 Conflict Detection 178 7.3.1 Collision Kinematics 178 7.3.2 Collision Detection 180 7.4 Conflict Resolution: Approach I 182 7.4.1 Collision Kinematics 183 7.4.2 Resolution Guidance 186 7.4.3 Analysis and Extension 188 7.5 Conflict Resolution: Approach II 191 7.5.1 Resolution Kinematics and Analysis 192 7.5.2 Resolution Guidance 193 7.6 CD&R Simulation 195 7.6.1 Simulation Results: Approach I 195 7.6.2 Simulation Results: Approach II 199 7.7 Conclusions 200 References 203 8 Aircraft Separation Management Using Common Information Network SAA 205 Richard Baumeister and Graham Spence 8.1 Introduction 205 8.2 CIN Sense and Avoid Requirements 208 8.3 Automated Separation Management on a CIN 212 8.3.1 Elements of Automated Aircraft Separation 212 8.3.2 Grid-Based Separation Automation 214 8.3.3 Genetic-Based Separation Automation 214 8.3.4 Emerging Systems-Based Separation Automation 216 8.4 Smart Skies Implementation 217 8.4.1 Smart Skies Background 217 8.4.2 Flight Test Assets 217 8.4.3 Communication Architecture 219 8.4.4 Messaging System 221 8.4.5 Automated Separation Implementation 223 8.4.6 Smart Skies Implementation Summary 223 8.5 Example SAA on a CIN - Flight Test Results 224 8.6 Summary and Future Developments 229 Acknowledgments 231 References 231 Part IV SAA Applications 9 AgentFly: Scalable, High-Fidelity Framework for Simulation, Planning and Collision Avoidance of Multiple UAVs 235 David ilák, P
emysl Volf, t
pán Kop
iva and Michal P
choüek 9.1 Agent-Based Architecture 236 9.1.1 UAV Agents 237 9.1.2 Environment Simulation Agents 237 9.1.3 Visio Agents 238 9.2 Airplane Control Concept 238 9.3 Flight Trajectory Planner 241 9.4 Collision Avoidance 245 9.4.1 Multi-layer Collision Avoidance Architecture 246 9.4.2 Cooperative Collision Avoidance 247 9.4.3 Non-cooperative Collision Avoidance 250 9.5 Team Coordination 252 9.6 Scalable Simulation 256 9.7 Deployment to Fixed-Wing UAV 260 Acknowledgments 263 References 263 10 See and Avoid Using Onboard Computer Vision 265 John Lai, Jason J. Ford, Luis Mejias, Peter O'Shea and Rod Walker 10.1 Introduction 265 10.1.1 Background 265 10.1.2 Outline of the SAA Problem 265 10.2 State-of-the-Art 266 10.3 Visual-EO Airborne Collision Detection 268 10.3.1 Image Capture 268 10.3.2 Camera Model 269 10.4 Image Stabilization 269 10.4.1 Image Jitter 269 10.4.2 Jitter Compensation Techniques 270 10.5 Detection and Tracking 272 10.5.1 Two-Stage Detection Approach 272 10.5.2 Target Tracking 278 10.6 Target Dynamics and Avoidance Control 278 10.6.1 Estimation of Target Bearing 278 10.6.2 Bearing-Based Avoidance Control 279 10.7 Hardware Technology and Platform Integration 281 10.7.1 Target/Intruder Platforms 281 10.7.2 Camera Platforms 282 10.7.3 Sensor Pod 286 10.7.4 Real-Time Image Processing 288 10.8 Flight Testing 289 10.8.1 Test Phase Results 290 10.9 Future Work 290 10.10 Conclusions 291 Acknowledgements 291 References 291 11 The Use of Low-Cost Mobile Radar Systems for Small UAS Sense and Avoid 295 Michael Wilson 11.1 Introduction 295 11.2 The UAS Operating Environment 297 11.2.1 Why Use a UAS? 297 11.2.2 Airspace and Radio Carriage 297 11.2.3 See-and-Avoid 297 11.2.4 Midair Collisions 298 11.2.5 Summary 299 11.3 Sense and Avoid and Collision Avoidance 300 11.3.1 A Layered Approach to Avoiding Collisions 300 11.3.2 SAA Technologies 300 11.3.3 The UA Operating Volume 303 11.3.4 Situation Awareness 304 11.3.5 Summary 304 11.4 Case Study: The Smart Skies Project 305 11.4.1 Introduction 305 11.4.2 Smart Skies Architecture 305 11.4.3 The Mobile Aircraft Tracking System 307 11.4.4 The Airborne Systems Laboratory 310 11.4.5 The Flamingo UAS 311 11.4.6 Automated Dynamic Airspace Controller 311 11.4.7 Summary 312 11.5 Case Study: Flight Test Results 312 11.5.1 Radar Characterisation Experiments 312 11.5.2 Sense and Avoid Experiments 319 11.5.3 Automated Sense and Avoid 324 11.5.4 Dynamic Sense and Avoid Experiments 326 11.5.5 Tracking a Variety of Aircraft 326 11.5.6 Weather Monitoring 331 11.5.7 The Future 332 11.6 Conclusion 333 Acknowledgements 333 References 334 Epilogue 337 Index 339