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This project is part of DARPA Beyond Linear Processing (BLiP) that proposes integrating compressive sensing techniques, artificial intelligence, machine learning, and track-before-detect algorithms into a comprehensive processing string for radar systems. This effort focuses on the control, interfaces, and impact each algorithm has on the system's processing. The challenges result from designing the algorithms to work together cohesively to minimize signal loss that has been traditionally accepted within existing radar systems. The objective is the ability to reduce the antenna or front-end hardware, which is the prime cost driver in fielding radars today. Integrating processing from recent signal processing advances is a cost-effective alternative to improve a radar's sensitivity, accuracy, and volume coverage.
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Osadciw et al. (2024) studied this question.
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