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Contents: Unmanned Aerial Systems Cooperative Control Contingencies Health Management for the Individual Vehicles: A Review Health Monitoring and Adaptation for UAS Formations Decision Making and Health Management for Cooperating UAS

Aviation propulsion development continues to rely upon fossil fuels for the vast majority of commercial and military applications. Until these fuels are depleted or abandoned, burning them will continue to jeopardize air quality and provoke increased regulation. With those challenges in mind, research and development of more efficient and electric propulsion systems will expand. Fuel-cell technology is but one example that addresses such emission and resource challenges, and others, including negligible acoustic emissions and the potential to leverage current infrastructure models. For now, these technologies are consigned to smaller aircraft applications, but are expected to mature toward use in larger aircraft. Additionally, measures such as electric/conventional hybrid configurations will ultimately increase efficiencies and knowledge of electric systems while minimizing industrial costs.

Getting Started with UAV Imaging Systems: A Radiometric Guide provides the tools technologists need to begin designing or analyzing the data product of a UAV imager. Covering the basics of target signatures, radiometric propagation, electro-optical systems, UAV platforms, and image quality, it is replete with examples that promote immediate application of the concepts. Reference materials at the end of each chapter, including many links to current systems and platforms, offer further guidance for readers. Engineers and scientists who specify instrument requirements; design, build, or test hardware; or analyze images for commercial, scientific, and military applications will find the book a useful addition to their working library.

Half the electric vehicle market value lies in larger road vehicles, notably cars, and here the legal restrictions are weaker or non-existent, and range anxiety compels most people to buy hybrids if they go electric at all. Over eight million hybrid cars will be made in 2025, each with a range extender, the additional power source that distinguishes them from pure electric cars. Add to that significant money spent on the same devices in buses, military vehicles, boats and so on and a major new market emerges. Whereas today's range extenders usually consist of little more than off- the- shelf internal combustion engines, these are rapidly being replaced by second- generation range extenders consisting of piston engines designed from scratch for fairly constant load. However, a more radical departure is the third- generation micro turbines and fuel cells that work at constant load.

Why are vision systems fundamental and critical to autonomous flight? What are the vision system tasks required for autonomous flight? How can those tasks be approached? It addresses the role of vision systems for autonomous operations and discusses the critical tasks required of a vision system, including taxi, takeoff, en-route navigation, detect and avoid, and landing, as well as formation flight or approach and docking at a terminal or with other vehicles. These tasks are analyzed to develop field of view, resolution, latency, and other sensing requirements and to understand when one sensor can be used for multiple applications. Airspace classifications, landing visibility categories, decision height criteria, and typical runway dimensions are introduced. The book provides an overview of sensors and phenomenology from visible through infrared, extending into the radar bands and including both passive and active systems.

The electric vehicle business will approach a massive $500 billion in 2025 with the traction motors segment capturing over $25 billion. Traction motors propelling land, water and air vehicles along can consist of one inboard motor or - an increasing trend - more than one near the wheels, in the wheels, in the transmission or ganged to get extra power. Complex trends in this industry are explained with this updated report, and future winning suppliers are identified alongside market forecasts. The information is especially important as hybrid vehicles may have the electric motor near the conventional engine or its exhaust, and this may mean they need to tolerate temperatures never before encountered in pure electric vehicles. Motors for highly price-sensitive markets such as electric bikes, scooters, e-rickshaws and micro EVs avoid the price hikes of neodymium and other rare earths in the magnets.

This third edition of Automatic Target Recognition provides a roadmap for breakthrough ATR designs―with increased intelligence, performance, and autonomy. Clear distinctions are made between military problems and comparable commercial deep-learning problems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. A reference design is provided for a next-generation ATR that can continuously learn from and adapt to its environment. The convergence of diverse forms of data on a single platform supports new capabilities and improved performance. This third edition broadens the notion of ATR to multisensor fusion. Radical continuous-learning ATR architectures, better integration of data sources, well-packaged sensors, and low-power teraflop chips will enable transformative military designs.

Automatic Target Recognition provides an inside view of the automatic target recognition (ATR) domain from the perspective of an engineer working in the field for 40 years. The algorithm descriptions and testing procedures covered in the book are appropriate for addressing military problems and unique aspects and considerations in the design, testing, and fielding of ATR systems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. The final chapter discusses the future of ATR and provides a type of Turing test for determining if an ATR system is truly smart (neuromorphic or brain-like). The Appendix provides difficult-to-find resources available to the ATR engineer.