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中文摘要：
感应线圈采集到的频率变化曲线，取决于车速、车辆自身结构及其通过感应线圈时的相对位置．针对同类车辆的频率变化曲线存在伸长或压缩情况，研究一种基于动态时间弯曲（DTW）的车型分类新方法．首先对采集到的车辆频率变化数据序列进行预处理；其次，结合DTW方法和最优聚类分析原理，选取同类车型的多个频率变化特征曲线作为分类模板，以改善单模板匹配方法的分类正确率；再次，确定同类车型的局部区分度指标，并优化调整局部区分度指标范围；最后对考察车辆的采样曲线进行多模板匹配分析，得出车型分类结论．仿真实验分析了本文方法与其他方法比较存在的优势．
英文摘要：
A vehicle＇s frequency-response curve is determined by its velocity, structural framework and the relative location to an inductive coil detector. As the frequency-response curves of vehicles of the same type are varied in length, a novel classification method based on the dynamic-time-warping （DTW） algorithm is proposed, After a pretreatment on the obtained frequency-response curves, multiple curves are selected as vehicle classification-templates for DTW algorithm and the optimal clustering method. This will improve the classification properties of the single-template matching method. Next, we determine the dissimilarity-indices and their ranges for the vehicles of the same type. Finally, the classification result is obtained by matching the sample curve to the multiple templates using DTW algorithm. A simulation is given to illustrate the advantage of the method.
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