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首页> 外文期刊>Quality Control, Transactions >Classification and Spectral Mapping of Stationary and Moving Objects in Road Environments Using FMCW Radar
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Classification and Spectral Mapping of Stationary and Moving Objects in Road Environments Using FMCW Radar

机译:FMCW雷达路面环境中静止和移动物体的分类和光谱映射

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摘要

In order to establish a reliable map of the road environment, this paper aims to classify the stationary and moving objects unlike the previous researches which generally focus on object recognition. The characteristics of the radar signals of stationary and moving objects were analyzed and the relation between the slope of pattern in radar time-frequency spectrum and relative velocity of the object was described mathematically. To discriminate the stationary and moving objects, the difference between the measured velocity by the slope and the velocity of the ego-vehicle was proposed as a feature. The statistical characteristics of stationary and moving objects according to the proposed feature were modeled using Gaussian model. To investigate the performance of the proposed method, the similarity between modeling of stationary and moving objects was quantified. Additionally, the receiver operating characteristics (ROC) curve and the correlation coefficient between the proposed feature and the ground-truth feature map was applied to verify the performance.
机译:为了建立道路环境的可靠地图,本文旨在对静止和移动物体进行分类,这与前面的研究通常关注对象识别。分析了静止和移动物体的雷达信号的特性,并在数学上描述了雷达时频谱中的图案斜率与物体的相对速度之间的关系。为了区分静止和移动物体,提出了由斜率的测量速度与自我车辆的速度之间的差异作为特征。根据所提出的特征的静止和移动物体的统计特性使用高斯模型进行建模。为了研究所提出的方法的性能,量化了静止和移动物体的建模之间的相似性。另外,应用了接收器操作特性(ROC)曲线和所提出的特征与地面真理特征图之间的相关系数来验证性能。

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