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- W3012676927 abstract "The dynamically changing environment in which future radar systems must operate will be increasingly demanding due a number of factors. The rising congestion in the RF space, reduced availability of dedicated RF spectrum, the requirement to detect low radar cross section targets such as drones, the proliferation of wind turbines causing false detections and target masking, and ever more sophisticated countermeasures all adversely affect performance. Cognitive radar is a relatively new branch of radar research drawing inspiration from the study of brain and sensory system functions in the field of neuroscience. It is well known that bats and marine mammals such as dolphins employ echo-location for navigation and hunting, providing a remarkable degree of success in challenging environments. It is anticipated that adding cognitive capabilities to radar systems will enable performance gains to be achieved by better utilising the limited resources available and optimising the system’s interactions with the environment. This thesis addresses two topics in cognitive radar research. The first topic is the absence of any common scheme for classifying the levels of cognitive ability exhibited in radar systems by the development of a ‘scale of cognition’ explicitly targeted towards the radar problem. The second is to address the limited experimental evidence available in the radar literature by reporting on a range of practical experiments based on scenarios which may benefit from the inclusion of some level of cognition. The experiments were implemented on two experimental radar systems, UCL’s NetRAD system which has no closed-loop adaptive capability, and The Ohio State University’s (OSU) Cognitive Radar Engineering Workspace (CREW), designed for adaptive and cognitive radar research." @default.
- W3012676927 created "2020-03-27" @default.
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- W3012676927 date "2020-02-28" @default.
- W3012676927 modified "2023-09-23" @default.
- W3012676927 title "An experimental investigation of cognitive radar" @default.
- W3012676927 hasPublicationYear "2020" @default.
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