基于兴趣域的自适应高分辨率参数估计及其在汽车雷达中的应用

Saeid K. Dehkordi, N. Appenrodt, J. Dickmann, C. Waldschmidt
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引用次数: 2

摘要

在驾驶辅助系统的运行阶段,需要对汽车雷达进行高分辨率处理,以提高目标检测和分类的概率。由于与整个数据集的高分辨率处理相关的大量计算需求,这些方法的实时应用仍然是一个挑战。本文提出了一种计算效率高的方法来实现这一目标,即只处理感兴趣区域,并利用多维变量分辨率来满足不同应用的必要要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Region of Interest Based Adaptive High Resolution Parameter Estimation with Applications in Automotive Radar
High resolution processing for automotive radar is required to enhance the probability of target detection and classification in proceeding stages of driver assistance systems. As a result of the large computational demand associated with high resolution processing of the entire data set, real-time application of such methods remains a challenge. This paper presents a computationally efficient approach to achieve this goal by only processing Regions of Interest with the capability of utilizing a multi-dimensional variable resolution to meet necessary requirements for different applications.
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