基于GPS/WiFi/MARGE组合定位算法

Integrated Positioning Algorithm Based on GPS/WiFi/MARG

摘要:

为了解决传感器MEMS进行姿态估计易受外界干扰的问题,首先设计了基于四元数的扩展卡尔曼滤波器,通过自适应地建立协方差矩阵和引入传感器偏差补偿的方法实现三自由度的姿态测量;其次,提出了基于粒子滤波和卡尔曼滤波的数据融合算法,实现了能有效解决接收信号强度时域浮动的WiFi/MARG 组合定位系统；最后设计了自适应加权算法,对WiFi/MARG和GPS/MARG两子系统进行融合,构建了能实现室内外的无缝定位的GPS/WiFi/MARGE定位系统,结果表明,该算法比WiFi/MARG和GPS/MARG系统的最大误差分别减少了51%和82%,平均定位误差减少53%和62%,有效地提高了定位精度。

Abstract:

In order to solve the sensor MEMS is vulnerable to outside interference when pose estimation, firstly design the extended Calman filter based on the number of four dirnentions, the attitude measurement of three degree of freedom is realized by the method adaptively establish covariance matrix and the introduction of sensor error compensation. secondly, the particle filter and Calman filter data fusion algorithm based on the WiFi/MARG integrated positioning system can effectively solve the floating received signal strength time; finally the adaptive weighted algorithm design, the WiFi/MARG and GPS/MARG sub system integration, construction of GPS/WiFi/MARGE positioning system to achieve seamless positioning of indoor and outdoor, experimental results show that the algorithm is better than the maximum the error of WiFi/MARG and GPS/MARG system were reduced by 51% and 82%, the average localization error is reduced by 53%and 62%, effectively improve the positioning accuracy.