INS／Magnetometer Fused Localization Algorithm Based on Particle Filter
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摘要: 针对城市峡谷场景中GPS信号容易受到建筑物的遮挡、反射,导致智能终端的GPS定位精度降低甚至无法定位的问题,本文在分析城市峡谷场景中GPS定位误差的基础上,在智能终端上实现了基于粒子滤波融合INS输出的水平速度和磁力计方位角的多传感器定位算法。实验结果表明,该算法的平均定位误差是3.19 m,相比于GPS的13.81 m,降低了769％,相比于EKF和UKF融合算法的4.84 m和4.82 m,分别降低了34.1％和33.8％.Abstract: GPS signals are more likely to be blocked or reflected by tall buildings in urban canyons, resulting in poor positioning accuracy even positioning failure to smart terminal. Based on the analysis of the GPS location error in urban canyons, horizontal velocity of INS and Azimuth of magnetometer data are fused by particle filter to positioning based on smart terminal. Experimental results show that the average error of proposed algorithm is 3.19m,which is reduced by 76.9％ compared to 13.81 m of GPS, and also reduced 34.1％ and 33.8％ compared to 4.84 m of EKF and 4.82m of UKF fusion algorithm.
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Key words:
- Multi-sensor fusion /
- particle filter /
- urban canyons /
- smart terminal
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