基于多传感融合的室内行径角度纠偏系统

Angle correction system for indoor localization based on multi-sensor fusion

针对室内定位系统易受手机姿态变化影响导致位置估计精度偏低的问题,提出一套行径角度纠偏的系列算法。将手机内通过四元数姿态解算后的数据,进行多传感器序贯式二阶卡尔曼滤波融合,对用户行径路线进行动态实时纠偏,使用户在行径过程中可随意摆动手机,不影响定位效果。实验结果表明,相比标准卡尔曼滤波,序贯分布式二阶卡尔曼滤波在手机转角纠偏方面更具有纠偏优势,利用优化后的转角进行多源融合定位能使用户行走方式更加随意,与地磁信息融合后更加明显地提高了室内定位的精度和稳定性。

Referring to the problem that the indoor positioning system is susceptible to the change of the attitude of the mobile phone, and the accuracy of the position estimation is low, a series of algorithms for correcting the deviation of the path angle were proposed. The data in the mobile phone were solved through the quaternion attitude, and the multi-sensor sequential second-order Kalman filter fusion was performed to dynamically correct the user ’s path, so that the user could swing the mobile phone as usual without affecting the positioning effect. Experimental results show that compared with the standard Kalman filter, the sequential distributed second-order Kalman filter has more corrective advantages in the correction of the corner of the mobile phone. The multi-source fusion positioning using the optimized corner can make the user walk more random. And after geomagnetic information fusion, the accuracy and stability of indoor positioning are more obviously improved.