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More reliable classification of radar data from dynamic scenarios

机译:从动态方案中更可靠地分类雷达数据

摘要

Procedure (100) for classifying radar data (2) obtained by recording radar radiation emitted from a transmitter and reflected by at least one object (20) with at least one detector, using the steps:Provide (110) radar data (2) containing observations recorded at different times (2a-2c) of a scene (1);Determine (120) at least one part (2') of the radar data (2), which is rotated and/or scaled in at least one of the observations (2a-2c) compared to at least one other of the observations (2a-2c);Determine (130) a fixed point (3) of rotation and/or scaling;Transform (140) at least a two-dimensional representation (4a-4c) of at least one part of the observations (2a-2c) into logarithmic polar coordinates with the determined fixed point (3) as origin;Images (150) of at least one transformed two-dimensional representation (4a'-4c') on at least one class (6a-6d) of a predetermined classification (6) by at least one classification (5), comprising a neural network with at least one folding layer.Procedure (200) for training a classifier (5).
机译:步骤(100)用于分类通过记录从发射器发射的雷达辐射而获得的雷达数据(2),并使用至少一个检测器反射至少一个物体(20),使用步骤:提供(110)雷达数据(2)含有在场景(1)的不同时间(2A-2C)的观测的观察;确定(120)与至少一个观察结果相比,雷达数据(2)的至少一个部分(2'),其在至少一个观察(2a-2c)中旋转和/或缩放(2a-2c)(2a -2c);确定(130)旋转和/或缩放的固定点(3);将观察结果(2A-2C)的至少一个部分的至少一个部分(2A-2C)的二维表示(4A-4C)变换为具有所确定的固定点(3)作为原点的对数极坐标;在包括神经网络的至少一个分类(6)的至少一个类(6a-6d)上的至少一个转换的二维表示(4a'-4c')的图像(150),包括神经网络至少有一个折叠层。步骤(200)用于培训分类器(5)。

著录项

  • 公开/公告号DE102019220069A1

    专利类型

  • 公开/公告日2021-06-24

    原文格式PDF

  • 申请/专利权人 ROBERT BOSCH GMBH;

    申请/专利号DE201910220069

  • 发明设计人 KOBA NATROSHVILI;

    申请日2019-12-18

  • 分类号G01S7/41;G01S13/89;

  • 国家 DE

  • 入库时间 2022-08-24 19:33:10

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