Chunhui Zhao

Unmanned Aircraft Systems: Safety and Security Issues presents a holistic view of the safety and security problems associated with unmanned systems. The title considers the various safety and security issues involved and draws up a blueprint for future UAV safety and security systems. Three sections present the technical elements of UAS safety and security, the safety technologies and system design of UAS, such as sense and avoidance, navigation and control, and the security technologies and system design of UAS, including cybersecurity anomaly detection and information intrusion response. This is the first book to deal holistically with UAS safety and operational threats and to consider the system and operational characteristics of UAS in terms of safety and security solutions.

Spatio-Temporal Learning Using Irregular Data for Complex Dynamic Processes introduces learning, modeling, and monitoring methods for highly complex dynamic processes with irregular data. Two classes of robust modeling methods are highlighted, including low-rank characteristic of matrices and heavy-tailed characteristic of distributions. In this class, the missing data, ambient noise, and outlier problems are solved using low-rank matrix complement for monitoring model development. Secondly, the Laplace distribution is explored, which is adopted to measure the process uncertainty to develop robust monitoring models. The book not only discusses the complex models but also their real-world applications in industry.

Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.

Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.