高分辨率汽车雷达轮廓估计技术综述

R. Mathew, Eesh Shekhar Gharat, Siddharth Hooda
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引用次数: 0

摘要

到2024年,自动驾驶系统市场预计将达到200亿美元,2016年至2024年期间的年增长率为25.7%。通过高分辨率雷达进行轮廓估计是这些新兴行业的关键功能之一,许多技术已用于此。研究了KNN-DBSCAN、广义霍夫变换和蛮力方法。遇到的雷达横截面(RCS)的大小、对启发式的依赖、准确性和计算成本是对各种技术进行比较的一些参数。虽然对这些参数进行了深入的研究,但雷达的干扰、污染等参数在文献中还没有得到广泛的研究。
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A Review Paper on Contour Estimation Techniques in High-Resolution Automotive Radars
By 2024, the market for automated driving systems is anticipated to reach $20 billion, growing at a 25.7 percent annual pace between 2016 and 2024. Contour estimation through High-Resolution radars is one of the key functionalities of these growing industries and many techniques have been used for it. KNN-DBSCAN, Generalized Hough Transform, and brute force approach are some of the techniques studied. Size of encountered Radar cross-section (RCS), dependency on heuristics, accuracy, and computational expensive are some of the parameters against which comparison of the various techniques is done. Although these parameters are studied in-depth, there are parameters like interference and contamination of RADAR that have not been studied extensively in the literature.
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