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The goal of our project, as part of DARPA's Beyond Linear Processing (BLiP) program, is to investigate and demonstrate the potential gain of implementing nonlin-ear and iterative signal processing for radio frequency (RF) systems. Specifically, given National Oceanic and Atmospheric Administration (NOAA) radar data, our goal is to demonstrate gains while decreasing cost and power to apertures. This is a phased array radar, and this paper discusses the use of sparsity to enable tracking in low signal regimes by taking advantage of multiple measurements. This is challenging because of the radar scan time and both moving and stationary clutter in the scene.
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Pine et al. (2024) studied this question.
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