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Statistical modelling of measured automotive radar reflections

机译:测量自动雷达反射的统计建模

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A statistical analysis was performed on measured radar reflections from a broad range of personal vehicle classes. The outcome of this study is two-fold: 1.) An improved understanding of the radar scattering components of automobiles, which informs the design of surrogate test targets for evaluating automotive pre-collision system (PCS) radars, and 2.) statistical models for evaluating surrogate targets and characterizing target models for PCS radar system designs. We examined the validity of two-parameter distribution models applied to measurements of subject vehicle's radar cross-section (RCS) and found the Weibull distribution to be the best fit. In evaluating the goodness-of-fit of the Weibull distribution model, using the Kolmogorov-Smirnov test, we deem an acceptable fit between the model and the measured RCS data for our intended project outcome.
机译:对来自广泛个人车辆的测量雷达反射进行了统计分析。本研究的结果是两倍:1。)改进了汽车雷达散射部件的了解,这通知了代理测试目标来评估汽车预碰撞系统(PCS)雷达和2.)统计模型用于评估PCS雷达系统设计的代理目标和特征目标模型。我们检查了应用于主题车辆雷达横截面(RCS)测量的两参数分配模型的有效性,并发现Weibull分布是最合适的。在评估Weibull分布模型的健康方面,使用Kolmogorov-Smirnov测试,我们认为模型和测量的RCS数据之间的可接受拟合,以获得我们预期的项目结果。

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