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摘要: 室内定位是近些年国内外研究的热点, 但是目前的室内定位技术在适用性、稳定性和推广性方面仍然存在诸多问题.针对目前室内定位技术的不足, 面向公共室内场景的人员自定位问题, 本文创新性地提出以室内广泛存在、均匀分布的消防安全出口标志为路标(Landmark), 提出以Wi-Vi指纹-WiFi与视觉(Vision)信息相融合的指纹, 为位置表征的多尺度定位方法.该方法首先利用室内广泛存在的WiFi无线信号进行粗定位, 缩小定位范围; 然后在WiFi定位的基础上通过视觉全局和局部特征匹配实现图像级定位和验证; 最后参考消防安全出口标志的空间坐标精确计算用户的位置信息.实验中, 通过市面上流行的不同型号智能手机在12 000平米办公楼和4万平米商场分别进行实地定位测试.测试结果表明:该方法可以达到实时定位的要求, 图像级定位准确率均在97 %以上, 平均定位误差均在0.5米以下.本文所提出的基于Wi-Vi指纹智能手机定位方法为高精度室内定位问题建议了一种新的解决思路.Abstract: Indoor positioning is a hot research topic in recent years. Existing methods still have the problems of poor applicability and low stability in different indoor situations. Aiming at solving the localization problem for public indoor environment, this paper for the first time proposes to use exit signs as landmarks that are widely distributed in the indoor environment. By applying these landmarks, a novel multi-scale positioning method is proposed based on Wi-Vi Fingerprint - WiFi and vision integrated fingerprint. The proposed method consists of coarse positioning from WiFi matching, image-level positioning and verification from holistic and local visual feature matching, and positioning refinement from metric positioning based on the space coordinates of exit sign. The proposed method has been tested in an indoor office building of 12 000 square meters and a shopping mall of 40 000 square meters, respectively, by using different smartphones. Experimental results show that the proposed Wi-Vi fingerprint method can achieve real-time positioning with more than 97 % accuracy rate for image-level positioning. In both test scenarios, the average positioning errors are less than half meters. The proposed Wi-Vi fingerprint method suggests a new solution to accurate indoor positioning.
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Key words:
- Indoor positioning /
- WiFi fingerprint /
- vision-based positioning /
- multi-scale positioning
1) 本文责任编委 徐德 -
图 1 WiFi与视觉相融合的定位指纹— Wi-Vi指纹
Fig. 1 WiFi and vision integrated positioning fingerprint — Wi-Vi fingerprint
图 3 基于Wi-Vi指纹定位的Android软件使用示意图
Fig. 3 Illustration of the Wi-Vi based Android application
图 4 办公楼4、5楼CAD平面图(方块表示标志消防安全出口标志; 预先对每个出口标志进行编号)
Fig. 4 CAD map of the fourth and fifth floor of office building (Exit signs are represented by blocks; Exit signs are pre-numbered)
图 5 奥山世纪城3楼和−1楼CAD平面图(方块表示消防安全出口标志, −1楼标志过于密集, 仅用虚线标出出口标志集中区域; 预先对每个出口标志进行编号)
Fig. 5 CAD map of the third floor and −1st floor of Orsun century city (Exit signs are represented by blocks, signs of −1st floor are not listed here due to too dense of signs; Exit signs are pre-numbered)
图 10 度量级定位修正后的最终定位结果
Fig. 10 The results of final positioning after matric positioning
表 1 Wi-Vi指纹
Table 1 Wi-Vi fingerprint
索引 Wi-Vi特征 值 1 WiFi指纹 MAC [00238975abc0, 24dec63766a0, 24dec637ac40, 24dec638f120, 00238979acc0, 002389799c80, 24dec6379740, 24dec6390fe0, 24dec63905e0, 24dec6376f40, 002389798be0, 00238975b1b0] RSSI (dBm) [-81, -81, -83, -81, -63, -81, -82, -73, -78, -83, -86, -85] 图像数据 全局特征 [211, 80, 47, 62, 40, 234, 93, 24, 180, 91, 195, 245, 215, 156, 59, 121, 196, 129, 255, 199, 175, 5, 119, 117, 209, 35, 120, 129, 124, 85, 190, 83] 局部特征 (416, 306), [157, 73, 7, 244, 149, 70, 239, 252, 148, 226, 66, 66, 113, 99, 49, 227, 88, 100, 50, 239, 105, 212, 61, 174, 41, 139, 239, 4, 63, 121, 48, 160] …… 单应矩阵 [1.1, 3.2, 336.0; 0, 3.5, 281.0; 0, 0, 1] 参考坐标(mm) (8 000, 7 800, 2 200); (8 000, 8 050, 2 200); (8 000, 8 050, 1 050); (8 000, 7 800, 1 050) 
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