Vehicle Speed Estimation Using Acoustic Wave Patterns
Vehicle Speed Estimation Using Acoustic Wave Patterns
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DOI：
10.1109/tsp.2008.2005750
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发表时间：
2009-01-01
影响因子：
5.4
通讯作者：
McClellan, James H.
中科院分区：
文献类型：
--
作者：
Cevher, Volkan;Chellappa, Rama;McClellan, James H.
我们通过使用记录车辆驶过噪音的单个无源声学传感器联合估计其声波模式来估计车辆的速度、轴距长度和轮胎痕迹长度。使用车辆的速度、多普勒频移因子、传感器到车辆的最近接近点的距离以及三个包络形状（ES）分量来确定声波图案，这三个包络形状分量近似于接收信号的功率包络的形状变化。我们将ES组件的参数沿着与车辆发动机RPM的估计，气缸的数量，和车辆的初始轴承，响度和速度，形成一个车辆配置文件向量。该矢量提供了可用于车辆识别和分类的指纹。我们还提供了可能的原因，为什么一些现有的方法无法提供无偏的车辆速度估计使用相同的框架。该方法说明使用车辆速度估计和分类结果与现场数据。
We estimate a vehicle's speed, its wheelbase length, and tire track length by jointly estimating its acoustic wave pattern with a single passive acoustic sensor that records the vehicle's drive-by noise. The acoustic wave pattern is determined using the vehicle's speed, the Doppler shift factor, the sensor's distance to the vehicle's closest-point-of-approach, and three envelope shape (ES) components, which approximate the shape variations of the received signal's power envelope. We incorporate the parameters of the ES components along with estimates of the vehicle engine RPM, the number of cylinders, and the vehicle's initial bearing, loudness and speed to form a vehicle profile vector. This vector provides a fingerprint that can be used for vehicle identification and classification. We also provide possible reasons why some of the existing methods are unable to provide unbiased vehicle speed estimates using the same framework. The approach is illustrated using vehicle speed estimation and classification results obtained with field data.