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Radar Micro-Doppler Simulations of Classification Capability with Frequency

机译:雷达微多普勒用频率进行分类能力模拟

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Classifying human signatures using radar requires a detailed understanding of the RF scattering phenomenology associated with humans as well as their motion. We model humans engaged in the activity of walking and analyze the separability of different body parts with frequency as well as lookdown angle. This work seeks to estimate the ability to classify the micro-Doppler signals generated by human motion, and especially arm motion, as a function of the radar frequency and other parameters. The simulations imply that for classification using arm motion, frequencies at Ku-band or higher are probably required, and that lookdown angle has a significant effect on the classification capability of the radar. Additionally, the sensitivity of the system required to isolate the motion of different body parts is estimated.
机译:使用雷达对人类签名进行分类需要详细了解与人类相关的RF散射现象学以及运动。我们模拟人类从事行走活动的活动,分析不同身体部位的可分离,以及频率以及阴扫角度。这项工作旨在估计作为雷达频率和其他参数的函数来估计分类由人动运动产生的微多普勒信号,尤其是臂运动。该模拟意味着对于使用ARM运动进行分类,可能需要KU波段或更高的频率,并且考察角度对雷达的分类能力具有显着影响。另外,估计隔离不同体部件运动所需的系统的灵敏度。

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