摘要
由于磁场无处不在的特点,使得磁场定位广泛应用于目标定位和状态检测中,然而在含有复杂铁磁质环境下,磁场信号的变化会导致定位精度下降甚至不能定位等问题.针对上述问题,提出了一种将磁场定位与BP神经网络相结合的方法,并进行了实验验证.结果表明,基于BP神经网络的磁场定位方法可用于含有铁磁质的复杂环境定位.定位精度与数据采集时磁源的移动步长、磁场传感器数量及传感器电子噪声有关,移动步长越小,传感器数量越多,电子噪声越小,定位精度越高.
The ubiquitous nature of magnetic fields makes magnetic field localization widely used in target localization and condition detection.However,in the environment containing complex ferromagnetic mass,the variation of the magnetic field signal can lead to problems such as degradation of localization accuracy or even failure to localize.To address these problems,a method combining magnetic field localization with BP neural network is proposed,and experimental verified.The results show that the BP neural network-based magnetic field localization method can be used for the localization of complex environments containing ferromagnetic materials.The localization accuracy is related to the movement step of the magnetic source,the number of magnetic field sensors and the electronic noise of the sensors during data acquisition.The smaller the movement step,the more the sensors and the smaller the electronic noise, the higher the localization accuracy.
作者
王华英
孙海军
张雷
王学
黄艳宾
郭海军
WANG Huaying;SUN Haijun;ZHANG Lei;WANG Xue;HUANG Yanbin;GUO Haijun(College of Mathematical Science and Engineering,Hebei University of Engineering,Handan 056038,China;Hebei Computational Optical Imaging and Photoelectric Detection Technology Innovation Center,Handan 056038,China;Hebei International Joint Research Center for Computational Optical Imaging and Intelligent Sensing,Handan 056038,China)
出处
《河北大学学报（自然科学版）》
CAS
北大核心
2022年第6期657-664,共8页
Journal of Hebei University(Natural Science Edition)
基金
国家自然科学基金资助项目(62175059)
河北省创新能力提升计划资助项目(20540302D)
邯郸市科学技术与发展计划项目(21422111246,19422031008-4)。
关键词
磁场
传感器
定位
BP神经网络
定位精度
magnetic field
sensor
positioning
BP neural network
positioning accuracy
