The biggest issue when Count-Battery Radar is the increase in operator fatigue and emergency response requirements due to clutter. In terms of radar performance, it is expected that the simultaneous detection ability of real targets will be improved when clutter is eliminated in real time. clutter is an unwanted signal generated when a signal transmitted from an antenna reaches the target and is then received by the antenna again, and much research is being conducted to remove clutter. In this study, an AI based target/clutter classification model is developed to reflect the requirements of operators and to complement the current target/clutter classification algorithm. Unnecessary beam waste caused by clutter can be prevented and accuracy can be improved. The performance of developed model was verified using data collected in the actual field.
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Kim et al. (2024) studied this question.
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