CRAP Part II: Clutter Removal with Continuous Acquisitions Under Phase Noise
arxiv(2024)
摘要
The mitigation of clutter is an important research branch in Integrated
Sensing and Communication (ISAC), one of the emerging technologies of future
cellular networks. In this work, we extend our previously introduced method
Clutter Removal with Acquisitions Under Phase Noise (CRAP) by means to track
clutter over time. This is necessary in scenarios that require high reliability
but can change dynamically, like safety applications in factory floors. To that
end, exponential smoothing is leveraged to process new measurements and
previous clutter information in a unique matrix using the singular value
decomposition, allowing adaptation to changing environments in an efficient
way.We further propose a singular value threshold based on the Marchenko-Pastur
distribution to select the meaningful clutter components. Results from both
simulations and measurements show that continuously updating the clutter
components with new acquisitions according to our proposed algorithm Smoothed
CRAP (SCRAP) enables coping with dynamic clutter environments and facilitates
the detection of sensing targets.
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