dumingyang20/BABNet-pytorch
This is the original implementation of the paper ''Robust Bayesian attention belief network for radar work mode recognition''.
This project helps radar system operators and signal analysts automatically identify the specific operational mode of a radar system by analyzing its pulse characteristics. It takes raw radar signal parameters, like radio frequency (RF), pulse width (PW), and pulse repetition interval (PRI), and outputs a classification of the radar's current working mode. This is designed for professionals managing or monitoring radar systems.
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Use this if you need to accurately and robustly classify the operational mode of a radar system from its pulse descriptive word (PDW) sequences, even when signals are noisy or incomplete.
Not ideal if you are working with optical, acoustic, or other non-radar signal types, or if you need to design new radar waveforms rather than classify existing ones.
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Python
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Apache-2.0
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Last pushed
Nov 03, 2024
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