基于高斯过程粒子滤波的WIFI信号定位追踪  

Gaussian Process Particle Filter Based WIFI Signal Tracking

作　　者：成明峰 耿晶晶[1] CHENG Mingfeng;GENG Jingjing(College of Electronic Engineering,Wuhan Vocational College of Software and Engineering,Wuhan 430205,China)

机构地区：[1]武汉软件工程职业学院电子工程学院,武汉430205

出　　处：《三门峡职业技术学院学报》2023年第1期139-143,共5页Journal of Sanmenxia Polytechnic

摘　　要：提出基于高斯过程粒子滤波的模型,根据室内WIFI信号强度进行行程追踪。非参数估计的高斯过程可以量化不确定性,与参数模型相比有更高的灵活性。仿真结果表明,与粒子滤波的行程追踪模型相比,基于高斯过程粒子滤波的模型在迭代初期估计更准确,更稳定。A model based on Gaussian process particle filtering is proposed to perform route tracking based on indoor WIFI signal strengths.The non-parametric estimation of Gaussian process can quantify the uncertainty and has higher flexibility compared with the parametric model.Simulation results show that the Gaussian process particle filter-based model is more accurate and stable in estimation at the beginning of the iteration compared to the particle filter-based route tracking model.

关 键 词：高斯过程 粒子滤波 WIFI信号 定位追踪 

分 类 号：TN92[电子电信—通信与信息系统]