Target Detection and Information Extraction in Radar Images

Dear Colleagues,

Radar signal processing techniques for detection and classification are the focus of intense research due to the continuous evolution of threats like unmanned systems. Border security, traffic management (air, maritime, and ground), and the security for critical infrastructures and smart cities, including public spaces, are applications that demand new solutions.

Radars must face the detection of small low reflectivity targets (aerial and maritime drones, inflatable or wood boats, ultralight aircraft, etc.), in complex environments (rural and coastal with complex relief, semi-urban and urban with big buildings, urban furniture, etc.), being the possibility of designing and integrating smart distributed sensor networks in the application scenario of great interest. Low cost and low probability of intercept (LPI) solutions can be key elements in these sensor networks for reducing reconfiguration and updating cost and for avoiding potential electromagnetic interferences, reducing the possibility of being intercepted and counter-measured. On the other hand, the possibility of threat classification and recognition is the desired result to evaluate the risk associated with the detected object in the considered complex environments.

This Special Issue will collect work on the most recent advances in radar detection and classification techniques. Contributions can tackle topics ranging from the signal processing carried out by a specific sensor node to the fusion of data provided by a set of nodes in a distributed sensor network, including (but not limited to) the following:

Target RCS and clutter modeling at frequencies used by active radars and opportunity illuminators used by passive ones.

Wideband signal processing for radar detection and classification, including sparse frequency signals and the use of compressive sensing techniques.

Neyman–Pearson approximation based on statistical signal models, including the use of intelligent agents.

Smart distributed sensor networks: sensor distribution and data fusion for detection, tracking, and imaging.

Novel classification and recognition techniques, at tracking and radar imaging levels.

Dr. M. Pilar Jarabo Amores
Dr. David de la Mata Moya
Guest Editors

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