This project will develop methods for analysis of complex environments using state-of-the-art data and image processing techniques. Analytical scene understanding is required for many emerging applications in autonomous or assisted operation such as driving, safety, security and defence. Thales is a world leader in the research and development of data and image processing technologies for transportation, defence, security and space applications, and this project will build upon a significant capability established over many years. Situations such as urban environments are dynamic and rich in features, and present significant challenges of complexity. Autonomous operation requires solutions able to classify scenes in terms of both static and dynamic features. They must be able to identify routes, buildings, places, people, vehicles, drones and other objects of interest, and to assess threats and hazards in day/night operation. The project will create novel situational awareness solutions using algorithms based on powerful concepts such as deep learning and contextual analysis. Modern sensor technology has enabled a proliferation of imaging devices operating all across the electro-magnetic spectrum. Private cars and other vehicles are already equipped with a growing array of situational awareness devices including specialist cameras for low-light imaging. The project will use data from multiple networked cameras using diverse imaging modalities such as 3-D and thermal imaging, non-imaging sensors such as radar and GPS, and meta-data such as digital maps. It will adapt and create image processing, data analysis and fusion methodologies to exploit this data. The project will produce demonstrations of scene analysis in urban and other data-rich environments.