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A Cross-Correlation Technique for Vehicle Detections in Wireless Magnetic Sensor Network

机译:无线磁传感器网络中车辆检测的互相关技术

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摘要

Vehicle detections are an important research field and attract many researchers. Most research efforts have been focused on vehicle parking detection (VPD) in indoor parking lot. For on-street parking, strong noise disturbances affect detection accuracy. To deal with vehicle detections in on-street environment, we propose two vehicle detection algorithms based on a cross-correlation technique in wireless magnetic sensor networks. One is for VPD, and the other one is for vehicle speed estimation (VSE). The proposed VPD algorithm combines the state-machine detection and the cross-correlation detection. In the VSE, speed estimation is based on the calculation of the normalized cross correlation between the signals of two sensors along the road with a certain spacing. Experimental results show that the VPD has an accuracy of 99.65% for arrival and 99.44% for departure, while the VSE has an accuracy of 92%.
机译:车辆检测是一个重要的研究领域,吸引了许多研究人员。大多数研究工作集中在室内停车场的车辆停车检测(VPD)。对于路边停车,强烈的噪声干扰会影响检测精度。为了处理路内环境中的车辆检测,我们提出了两种基于互相关技术的无线磁传感器网络中的车辆检测算法。一种是用于VPD,另一种是用于车速估算(VSE)。提出的VPD算法结合了状态机检测和互相关检测。在VSE中,速度估算是基于沿道路以特定间距的两个传感器的信号之间的归一化互相关计算得出的。实验结果表明,VPD的到达准确度为99.65%,离场的准确度为99.44%,而VSE的准确度为92%。

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