论文标题
使用准静态磁场检测的行人死算系统
Pedestrian Dead Reckoning System using Quasi-static Magnetic Field Detection
论文作者
论文摘要
基于卡尔曼滤波器的惯性导航系统（INS）是一种可靠，有效的方法，用于估计室内行人的位置。基于经典的INS方法论，称为IEZ（INS-EKF-ZUPT）使用了扩展的Kalman过滤器（EKF），这是一个零速度更新（ZUPT）来计算人的位置和态度。但是，标题误差是整个行人死亡估算（PDR）系统的关键因素，对于基于IEZ的PDR系统无法观察到。为了最大程度地减少误差，电子com-pass（EC）算法成为有效方法。但是磁干扰可能对其产生很大的负面影响。在本文中，根据检测结果，提出了准静态磁场检测（QMD）方法以检测纯磁场，然后选择EC算法或启发式标题漂移还原算法（HDR），从而实现了两种方法的互补。同时，将QMD，EC和HDR算法集成到IEZ框架中，以形成一种新的PDR解决方案，该解决方案命名为Advanced IEZ（AIEZ）。
Kalman filter-based Inertial Navigation System (INS) is a reliable and efficient method to estimate the position of a pedestrian indoors. Classical INS-based methodology which is called IEZ (INS-EKF-ZUPT) makes use of an Extended Kalman Filter (EKF), a Zero velocity UPdaTing (ZUPT) to calculate the position and attitude of a person. However, heading error which is a key factor of the whole Pedestrian Dead Reckoning (PDR) system is unobservable for IEZ-based PDR system. To minimize the error, Electronic Com-pass (EC) algorithm becomes a valid method. But magnetic disturbance may have a big negative effect on it. In this paper, the Quasi-static Magnetic field Detection (QMD) method is proposed to detect the pure magnetic field and then selects EC algorithm or Heuristic heading Drift Reduction algorithm (HDR) according to the detection result, which implements the complementation of the two methods. Meanwhile, the QMD, EC, and HDR algorithms are integrated into the IEZ framework to form a new PDR solution which is named Advanced IEZ (AIEZ).
