一种改进的高斯粒子滤波室内定位算法

发布时间：2018-04-12 16:57

本文选题：WiFi室内定位 + 惯性传感器　；参考：《计算机工程与应用》2017年14期

【摘要】：在无线室内定位研究中,为减少离线指纹数据库建立阶段的大量数据采集工作,提出利用手机内置惯性传感器加速度数据,计算用户运动路径,在经过指纹点时自动采集该指纹点的数据,自动动态建立指纹库的方法。针对手机内置传感器采集的加速度数据存在非线性噪声等干扰,提出了改进的高斯粒子滤波GPF(Gaussian Particle Filter)算法,将加速度样本经改进滤波算法获得较好的估值后,再进行运动路径计算。对状态变量服从线性变化,观测方程为非线性变化的系统模型有显著效果。实验结果表明,经改进的算法计算出的路径效果优于高斯粒子滤波算法和卡尔曼滤波算法,并且减少了计算复杂度。新方法建立数据库后,节约了大量的离线数据采集工作,但是精度与传统指纹库方法相比基本一致。
[Abstract]:In the research of wireless indoor positioning, in order to reduce a large amount of data acquisition in the establishment of off-line fingerprint database, the acceleration data of the built-in inertial sensor in the mobile phone is proposed to calculate the user's motion path.The method of automatically collecting the fingerprint data and establishing the fingerprint database automatically when passing through the fingerprint point.In view of the nonlinear noise and other interference in the acceleration data collected by the built-in sensor of mobile phone, an improved Gao Si particle filter GPF(Gaussian Particle filter algorithm is proposed. After the acceleration sample is estimated by the improved filtering algorithm,Then the motion path is calculated.The system model with linear variation of state variable and nonlinear variation of observation equation has remarkable effect.The experimental results show that the path effect calculated by the improved algorithm is better than that of Gao Si particle filter and Kalman filter, and the computational complexity is reduced.
【作者单位】：新疆大学信息科学与工程学院;中国移动通信集团新疆有限公司;
【基金】：中国移动通信集团新疆有限公司研究发展基金项目(No.XJM2013-01)
【分类号】：TN713;TP212

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