1st Edition
Situation Assessment in Aviation Bayesian Network and Fuzzy Logic-based Approaches
Situation Assessment in Aviation focuses on new aspects of soft computing technologies for the evaluation and assessment of situations in aviation scenarios. It considers technologies emerging from multisensory data fusion (MSDF), Bayesian networks (BN), and fuzzy logic (FL) to assist pilots in their decision-making.
Studying MSDF, BN, and FL from the perspective of their applications to the problem of situation assessment, the book discusses the development of certain soft technologies that can be further used for devising more sophisticated technologies for a pilot's decision-making when performing certain tasks: airplane monitoring, pair formation, attack, and threat. It explains the concepts of situation awareness, data fusion, decision fusion, Bayesian networks, fuzzy logic type 1, and interval type 2 fuzzy logic. The book also presents a hybrid technique by using BN and FL and a unique approach to the problem of situation assessment, beyond visual range and air-to-air combat, by utilizing building blocks of artificial intelligence (AI) for the future development of more advanced automated systems, especially using commercial software.
The book is intended for aerospace R&D engineers, systems engineers, aeronautical engineers, and aviation training professionals. It will also be useful for aerospace and electrical engineering students taking courses in Air Traffic Management, Aviation Management, Aviation Operations, and Aviation Safety Systems.
1. Introduction. 2. Situation Awareness. 3. Situation Assessment. 4. Theory of Fuzzy Logic. 5. Fuzzy Logic-based Decision Fusion and Fuzzy Filtering. 6. Performance Evaluation of Fuzzy Logic-based Decision System. 7. Situation Assessment Models and Use of Fuzzy Logic. 8. Interval Type 2 Fuzzy Logic (IT2FL)-based Decision System. 9. IT2 Fuzzy Logic Decision Fusion for Formation-Flying Recognition. 10. Bayesian Mental Models of a Pilot for SA in Air-to-Air Combat. 11. Fuzzy Logic and Bayesian Network-based SA in Air-to-Air Combat. 12. Approaches of Artificial Intelligence-based Situation Awareness and Assessment. Appendix A. Aviation Safety and Security. Appendix B. Aviation Sustainability. Appendix C. Situation Assessment Case Study-1. Appendix D. Situation Assessment Case Study-2.
Biography
Jitendra R. Raol received his B.E. and M.E. degrees in electrical engineering from M.S. University (MSU) of Baroda, Vadodara, in 1971 and 1973, respectively, and a Ph.D. (in electrical & computer engineering) from McMaster University, Hamilton, Canada, in 1986. He joined the National Aeronautical Laboratory (NAL) in 1975. At CSIR-NAL, he was involved in the activities on human pilot modeling in fix- and motion-based research flight simulators. He re-joined NAL in 1986 and retired in July 2007 as Scientist-G (and Head of Flight Mechanics and Control division at CSIR-NAL).
He was a Fellow of the IEE/IET (United Kingdom) and a senior member of the IEEE (United States). He is a life-fellow of the Aeronautical Society of India and a life member of the Systems Society of India. He has published nearly 160 research papers and numerous technical reports. He had guest-edited two special issues of Sadhana and two special issues of the Defense Science Journal (New Delhi, India). He has co-authored an IEE/IET Control Series book, Modeling and Parameter Estimation of Dynamic Systems (2004) and several CRC Press books: Flight Mechanics Modeling and Analysis (2009); Nonlinear Filtering: Concepts and Engineering Applications (2017); Control Systems: Classical, Modern, and AI based Approaches (2019). He has also authored several CRC Press books: Multi-Sensor Data Fusion with MATLAB (2010), and Data Fusion Mathematics: Theory and Practice (2015). He has also edited a CRC Press book: Mobile Intelligent Autonomous Systems (2012).
Sudesh K. Kashyap obtained his BE degree in Electronics Engineering (1995) from Gorakhpur University; ME in Electrical Engineering (1999) from MS University of Vadodara, Gujarat; and PhD in Electrical and Electronics Engineering (2008) from University of Mysore, Karnataka. He worked as a Project Assistant at CSIR-NAL & a Software engineer in Private company (Hewlett Packard) between 1999-2002. He joined CSIR-NAL as a scientist in Year 2002. Presently, he is working as a Senior Principal Scientist and is Group Head of System Identification and Data Fusion group of Flight Mechanics and Control Division at CSIR-NAL, Bangalore. His core expertise is in the area of Linear & Non-linear estimation, Multi-Sensor data fusion, Data Association, Track Fusion, Situation/Threat Assessment, HUD Symbology, Enhanced & Synthetic Vision System, Store Separation Trajectory Estimation, INS-GPS Integration, Target localisation, etc. He has published several National and International journal/conference papers. He received the CSIR-NAL Excellence Award in the field of ‘Technology’ for ‘LCA Stores Separation Trajectory Estimation’. He was awarded CSIR, India, Software copyright on ‘Data Acquisition Software for EVS Flight Experiment’. He also jointly holds two SW copyrights for: i) data fusion SW for real time target tracking in an integrated test range, and ii) SW for evaluation of fuzzy implication functions.
Lakshmi Shrinivasan earned her BE and MTech degrees in Electronics from Shivaji University and VTU in 1999 and 2007, respectively. She earned her PhD degree from Jain University, Bangalore in 2018. She has published several research papers in International and National journals and conferences and received the Best Research paper award in 2015 at a Research Retreat National conference organized by the Jain University. Currently, she is working as an Associate Professor at Ramaiah Institute of Technology in the Department of Electronics and Communication Engineering, teaching several undergraduate and postgraduate courses. She has guided several student projects, many of them received Best Project Awards at the Institute levels and received Karnataka Science and Technology Council (KSCST) & MSRIT Alumni Association Funds. Since 2021, she has been working on a consultancy project, which is focused on battery management and prediction techniques using estimation and prediction algorithms and digital dashboard for Electric Vehicles. Her research interests are Data Fusion, Situation Assessment, Fuzzy logic, Artificial Intelligence, Embedded System Design, VLSI, and Digital Twin Solutions for Situation Assessment.
