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Blind Deconvolution Processing of Loop Inductance Signals for Vehicle Reidentification

Blind Deconvolution Processing of Loop Inductance Signals for Vehicle Reidentification
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摘要 Vehicle reidentification is an elegant solution for gathering several pieces of valuable traffic information, e.g., space mean speed, travel time, vehicle tracking, and origin/destination data. Recently, a number of vehiclereidentification algorithms utilizing inductive loop signals have been proposed to take advantage of the widespread availability of loop detectors. These algorithms, however, all directly utilize the raw inductance signals for pattern matching and feature extraction without deconvolution. The raw loop signals are essentially a convolved output between the true vehicle inductance signature and the loop system function, and thus a deconvolution is needed in order to expose the detailed features of individual vehicles. The purpose of this paper is to present a recent investigation on restoration of true inductance signatures by applying a blind deconvolution process. The main advantage of blind deconvolution over the conventional deconvolution is that the computation does not require modeling of a precise loop-detector system function. Experimental results show that the proposed blind deconvolution reveals much more detailed features of inductance signals and, as a result, increases the vehicle reidentification accuracy.
出处 《Journal of Civil Engineering and Architecture》 2011年第11期957-966,共10页 土木工程与建筑(英文版)
关键词 Vehicle reidentification blind deconvolution loop inductance signals. 盲解卷积 车辆跟踪 信号 电感 环路 闭环系统 交通信息 旅行时间
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