| 结合位置指纹和行人航迹的室内定位技术 |
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| 引用本文： | 罗思奇,罗笑玲,李敏澄,李志锋,陈建城,周娴玮,潘家辉.结合位置指纹和行人航迹的室内定位技术[J].计算机系统应用,2017,26(5):272-278. |
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| 作者姓名： | 罗思奇 罗笑玲 李敏澄 李志锋 陈建城 周娴玮 潘家辉 |
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| 作者单位： | 华南师范大学 软件学院, 南海 528225,华南师范大学 软件学院, 南海 528225,华南师范大学 软件学院, 南海 528225,华南师范大学 软件学院, 南海 528225,华南师范大学 软件学院, 南海 528225,华南师范大学 软件学院, 南海 528225,华南师范大学 软件学院, 南海 528225 |
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| 基金项目： | 广东大学生科技创新培育专项资金（“攀登计划”专项资金）（pdjh2016b0129）；国家自然科学基金青年科学基金（61503143）；广东省自然科学基金博士科研启动项目（2014A030310244） |
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| 摘 要： | 主要对室内定位技术展开研究，首先通过手持智能设备收集指定范围样本点的坐标及wifi热点信息；然后应用位置指纹定位方法进行绝对定位；为了提高行走过程中定位的准确性和实时性，采用行人航迹推算算法，即通过手机传感器采集并经处理的数据进行步频检测、步长估算和方向检测，实现相对位置变化的估算.行人航迹算法克服位置指纹定位的不稳定性，而位置指纹定位算法及时调整行人航迹算法带来的累积误差.实验结果表明两种室内定位技术的结合有效提高了室内定位的准确性，能充分应用到实际生活中.
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| 关 键 词： | 室内定位 安卓平台 wifi 位置指纹定位 行人航迹推算 |
| 收稿时间： | 2016/9/4 0:00:00 |
| 修稿时间： | 2016/11/3 0:00:00 |
Indoor Positioning Technology Based on Location Fingerprint and Pedestrian Track |
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| LUO Si-Qi,LUO Xiao-Ling,LI Min-Cheng,LI Zhi-Feng,CHEN Jian-Cheng,ZHOU Xian-Wei and PAN Jia-Hui.Indoor Positioning Technology Based on Location Fingerprint and Pedestrian Track[J].Computer Systems& Applications,2017,26(5):272-278. |
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| Authors: | LUO Si-Qi LUO Xiao-Ling LI Min-Cheng LI Zhi-Feng CHEN Jian-Cheng ZHOU Xian-Wei and PAN Jia-Hui |
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| Affiliation: | School of Software, South China Normal University, Nanhai 528225, China,School of Software, South China Normal University, Nanhai 528225, China,School of Software, South China Normal University, Nanhai 528225, China,School of Software, South China Normal University, Nanhai 528225, China,School of Software, South China Normal University, Nanhai 528225, China,School of Software, South China Normal University, Nanhai 528225, China and School of Software, South China Normal University, Nanhai 528225, China |
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| Abstract: | On this paper, the research mainly focuses on the technology of indoor location. First, we collect coordinates of sample spots by handheld smart device in the specified range and information of wifi wireless hotspot, with which the location fingerprint technique is applied to absolute positioning; In order to improve the real-time performance and accuracy of indoor positioning, the pedestrian dead reckoning algorithm which will measure stride frequency, estimate step size and detect the direction with data collected and processed by the mobile phone sensor is used to achieve relative position estimation. The pedestrian dead reckoning algorithm can overcome the instability of the location fingerprint technique and the latter can reduce the cumulative error that the former brings. The result shows the combination of the two technologies is able to effectively improve the accuracy of indoor location and be fully used in the real world. |
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| Keywords: | indoor positioning Android platform wifi location fingerprinting technique pedestrian dead reckoning |
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