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A target tracking system using sensors of multiple modalities
Author(s) -
Shuqing Zeng
Publication year - 2013
Publication title -
international journal of vehicle autonomous systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.137
H-Index - 24
eISSN - 1741-5306
pISSN - 1471-0226
DOI - 10.1504/ijvas.2013.056632
Subject(s) - computer vision , radar , object detection , artificial intelligence , computer science , tracking system , cruise control , radar engineering details , video tracking , tracking (education) , radar tracker , azimuth , advanced driver assistance systems , real time computing , object (grammar) , radar imaging , kalman filter , control (management) , telecommunications , psychology , pedagogy , physics , segmentation , astronomy
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 eld 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 retrotted 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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