Rong Wang – författare

This thesis presents research focusing on the improvement of high-resolution global black carbon (BC) emission inventory and application in assessing the population exposure to ambient BC. A particular focus of the thesis is on the construction of a high-resolution (both spatial and sectorial) fuel consumption database, which is used to develop the emission inventory of black carbon. Above all, the author updates the global emission inventory of black carbon, a resource subsequently used to study the atmospheric transport of black carbon over Asia with the help of a high-resolution nested model. The thesis demonstrates that spatial bias in fuel consumption and BC emissions can be reduced by means of the sub-national disaggregation approach. Using the inventory and nested model, ambient BC concentrations can be better validated against observations. Lastly, it provides a complete uncertainty analysis of global black carbon emissions, and this uncertainty is taken into account in the atmospheric modeling, helping to better understand the role of black carbon in regional and global air pollution.

This book describes the resilient navigation techniques under the background of collaboration in swarm. The significance of this work is that it focuses on the navigation enhancement by collaboration in swarm rather than ground infrastructure, which exploit potentialities of swarm in GNSS restricted environment.

Although unmanned swarm is receiving greater attention, both through theoretical research and through increasing mention in the industrial developments, the navigation promotion by effective and efficient collaboration remains largely unexplored. While my scholarly work has explored some of the modeling, error characteristic, fusion algorithm, fault detection, and isolation aspects of the “adaptive navigation system” (such as the navigation system of robots and ground vehicles, aircrafts, aerospace vehicles, and unmanned aerial vehicles), the present book proposes the specialized investigation on the navigation with the resilient character, which could maintain the performance by essential collaboration with members in swarm in GNSS degradation environment.

This book focused on the resilient navigation techniques under the background of collaboration in swarm. The key techniques of collaborative resilient navigation are proposed, including the collaboration framework, collaborative observation modeling, geometry optimization, integrity augmentation, and fault detection. The experiments are also carried out to validate the effectiveness of the corresponding techniques.