A target tracking system using sensors of multiple modalities

Shuqing Zeng
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引用次数: 1

Abstract

Radar sensors and camera based vision systems will be used to provide object data in many Advanced Driver Assistance Systems (ADAS). In this paper, a multi-sensor target tracking system that combines data from a Frequency-Modulated Continuous Wave (FMCW) radar, multiple Short-Range Radars (SRR), a camera-based object detection system and vehicular dynamic sensors is described. Each object sensor individually measures the range, range rate and azimuth angle information of all objects within the observation region. The proposed system 1 groups objects from different sensors in overlapped observation region; 2 tracks an object across different sensor field of views; 3 reports the Cartesian coordinates of objects with improved accuracy and reduced rates of false detection and missed detection. The proposed target tracking system was implemented in a retrofitted vehicle. Only about two-percent CPU usage is needed for an 800 MHz embedded processor. The output data was directly used by several vehicle features suc...
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一种使用多模态传感器的目标跟踪系统
雷达传感器和基于摄像头的视觉系统将用于在许多高级驾驶辅助系统(ADAS)中提供目标数据。本文介绍了一种结合调频连续波雷达(FMCW)、多部近程雷达(SRR)、基于摄像头的目标检测系统和车载动态传感器数据的多传感器目标跟踪系统。每个目标传感器分别测量观测区域内所有目标的距离、距离速率和方位角信息。该系统将来自不同传感器的目标分组在重叠的观测区域;2在不同的传感器视野中跟踪一个物体;3报告物体的笛卡尔坐标,提高了精度,降低了误检率和漏检率。所提出的目标跟踪系统在一辆改装车辆上实施。一个800兆赫的嵌入式处理器只需要大约2%的CPU使用率。输出数据直接用于车辆的几个特征,如…
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来源期刊
International Journal of Vehicle Autonomous Systems
International Journal of Vehicle Autonomous Systems Engineering-Automotive Engineering
CiteScore
1.30
自引率
0.00%
发文量
0
期刊介绍: The IJVAS provides an international forum and refereed reference in the field of vehicle autonomous systems research and development.
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