| 摘要: |
| 针对目前室内定位技术中位置漂移、定位结果偏差较大的问题，提出了一种融合行人航迹推算（PDR）、地标匹配修正和地图辅助的室内行人定位方法。该方法利用基于惯性传感器的PDR技术计算行人位置信息，利用行走过程中的传感器读数特征识别室内特定地标点，与地标库数据进行匹配后，修正PDR轨迹产生的累积误差。室内地图辅助主要是通过判断行人是否位于走廊等区域，限制轨迹穿墙，约束PDR定位轨迹。实验结果表明，融合定位算法得到的轨迹优于纯惯性递推算法得到的轨迹，更加接近真实的行走轨迹，定位精度提高了51.2%，平均定位误差降至1.8m，满足室内定位需求。 |
| 关键词: 室内定位 地标匹配 卡尔曼滤波 行人航迹推算 |
| DOI： |
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| 基金项目:国家重点研发计划（2017YFC0803400）;中国科学院空天信息创新研究院重点部署项目(E0Z214010F |
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| Indoor Location Method Based on Map-assisted Pedestrian Dead Reckoning |
| HU Qian,ZHANG Wen-chao,WEI Dong-yan,YUAN Hong |
| (School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China 2. Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100094, China) |
| Abstract: |
| Aiming at the problems of position drift and large deviation of the positioning results in the current indoor positioning technology, an indoor pedestrian positioning method that integrates Pedestrian Dead Reckoning (PDR), landmark matching correction and map assistance is proposed. This method uses PDR technology based on inertial sensors to calculate pedestrian location information, and uses sensor reading characteristics during walking to identify specific indoor landmark points, and after matching with landmark library data, it corrects the cumulative error generated by the PDR trajectory. Indoor map assistance is mainly to determine whether pedestrians are located in corridors and other areas, restricting the trajectory through the wall, and constrains the PDR positioning trajectory. The experimental results show that the trajectory obtained by the fusion positioning algorithm is better than the trajectory of the pure inertial recursive algorithm, and is closer to the real walking trajectory. The positioning accuracy is improved by 51.2%, and the average positioning error is reduced to 1.8m, which meets the indoor positioning requirements. |
| Key words: Indoor positioning Landmark matching Kalman filtering Pedestrian dead reckoning |
