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Analytical investigation of two-object DOA estimation

机译:两目标DOA估计的分析研究

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Current automotive radar systems measure the distance, the relative velocity and the direction of objects in their environment. This information enables the car to support the driver. When objects cannot be completely separated by their distance or relative velocity, a two object direction of arrival estimator must normally be used to separate the objects. In this paper we take a close look at the Cramér-Rao bound of the two-object estimation problem. We show the influence of the objects'' phase difference and their signal power. Furthermore, criterions are introduced, which can be used to optimize the average direction estimation performance of an antenna array. It turns out that there are array and angle combinations which are more sensitive to phase difference changes than others.
机译:当前的汽车雷达系统测量环境中物体的距离,相对速度和方向。该信息使汽车能够为驾驶员提供支持。当物体无法通过其距离或相对速度完全分开时,通常必须使用两个物体的到达方向估算器来分开物体。在本文中,我们仔细研究了两目标估计问题的Cramér-Rao界。我们展示了对象的相位差及其信号功率的影响。此外,引入了可用于优化天线阵列的平均方向估计性能的标准。事实证明,存在阵列和角度组合比其他组合对角度差变化更敏感的阵列。

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