一种抗干扰的磁阻传感器车辆检测算法

An Anti-Interference Vehicle Detection Algorithm Based on Magnetoresistance Sensor

基于磁阻传感器的物联网在城市交通检测中逐渐被大规模应用,但城市中的地下高压电缆会产生磁场辐射,形成大范围、长时间的磁场干扰,而传统的车辆检测算法大都没有考虑到这类磁干扰,导致了误检率过高。本文提出了抗干扰的车辆检测算法,基于高压电缆磁场模型分析了磁干扰信号的特征,设计了广义形态滤波器过滤干扰信号,然后利用双阈值机制实现了车辆检测算法。实验结果表明,在高压电缆磁干扰环境下,该算法的车辆检测准确度在98%以上,优于传统算法。

The Internet of Things based on magnetoresistance sensor is gradually applied on a large scale in urban traffic detection.However,magnetic field radiation generated underground high voltage cables in cities forms a large range and long-term magnetic field interference.Most traditional vehicle detection algorithms do not take into account such magnetic interference,which leads to high false detection rate.This paper proposes an anti-interference vehicle detection algorithm,analyzes the characteristics of the magnetic interference signal,designs a generalized form filter to filter the interference signal,and then realizes the vehicle detection algorithm using a two-threshold mechanism.The experimental results show that the vehicle detection accuracy is above 98%in the high-voltage cable magnetic interference environment,which is better than the traditional algorithm.