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This book introduces advanced sparsity-driven models and methods and their applications in radar tasks such as detection, imaging and classification. Compressed sensing (CS) is one of the most active topics in the signal processing area. By exploiting and promoting the sparsity of the signals of interest, CS offers a new framework for reducing data without compromising the performance of signal recovery, or for enhancing resolution without increasing measurements.

Over the last ten years, the numbers of unmanned air vehicles (UAVs) or “drones” have changed from being just a few specialist systems, used for scientific data gathering and military purposes, to them proliferating in huge numbers. They are used across a broad range of different leisure, commercial and military activities. UAVs can be used for: movement of items in factories for manufacturing, passenger and freight transportation, can take various roles in the agriculture and forestry industries (dispensing seeds, watering and monitoring crops), remote sensing for the oil and gas industries, traffic flow monitoring, support of emergency services, hobbies, security, military and many other applications.