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针对接收信号质量恶化的环境,提出了一种适用于信号遮蔽环境的改进GPS+PDR组合定位算法。该方法用短时间内的陀螺仪积分数据校正数字罗盘的航向偏差,在一定程度上消除了数字罗盘受到的偶发干扰。采用约束残差的无迹卡尔曼滤波(UKF)算法对GPS和行人航迹推算(PDR)定位信息进行融合处理,有效克服了PDR定位中累积航向误差产生的位置漂移问题,提高了算法的定位精度和稳定性。试验结果表明,改进算法能有效抑制数字罗盘的漂移误差,航向相对误差平均降低56%;行人步行时,GPS定位标准误差为2.67 m,单纯PDR定位标准误差为6.83 m;随机给予若干点GPS数据辅助定位,标准误差降至3.12m;全程融合GPS与PDR定位,标准误差可降至1.94 m。
Aiming at the environment that the received signal quality is deteriorated, an improved GPS + PDR combined positioning algorithm is proposed for signal occlusion environment. The method corrects the course deviation of the digital compass with the integral data of the gyroscope in a short time, to a certain extent, eliminates the sporadic interference of the digital compass. The unscented Kalman filter (UKF) algorithm with constrained residuals is used to integrate the GPS and pedestrian trajectory estimation (PDR) localization information to effectively overcome the position drift caused by accumulated heading errors in PDR positioning and improve the positioning of the algorithm Accuracy and stability. The experimental results show that the improved algorithm can effectively suppress the drift error of digital compass and the average relative heading error decreases by 56%. When the pedestrian walk, the standard error of GPS positioning is 2.67 m and the standard error of simple PDR positioning is 6.83 m. Assisted positioning, standard error down to 3.12m; full integration of GPS and PDR positioning, the standard error can be reduced to 1.94m.