基于智能手机的WiFi的室内定位研究

发布时间：2018-10-17 21:54

【摘要】：位置信息是连接物理世界和网络空间的重要结合点,是物联网时代中极其重要的因素,与人类的社会生活息息相关。现在人们的生活方式已发生改变,每天80%的时间都活动在室内环境下,然而在室内环境下GPS技术无法取得令人满意的定位精度。随着WiFi网络大面积部署于各种室内场所,智能手机的使用已成“燎原”之势,基于智能手机的WiFi室内定位研究受到越来越多的关注。目前,基于智能手机的WiFi室内定位算法主要分为两种:基于无线测距的室内定位算法和基于接收信号强度指示(RSSI)指纹的室内定位算法。这两种定位算法在实际定位中遇到很多挑战,基于测距的室内定位算法是根据无线测距原理进行几何约束定位,由于室内环境的多径效应导致信号强度值波动很大,从而使得定位精度很低。基于RSSI指纹定位算法的前提是构建精确的指纹数据库,然而构建RSSI指纹数据需要花费大量的人工代价进行现场勘测采集。在针对基于测距和RSSI指纹室内定位中遇到的挑战,本文分别进行如下两个方面研究:(1)在针对无线测距误差大导致定位误差较大的问题,本文提出基于智能手机的信号自适应修正算法,采用修正因子来提高无线测距的精度,从而降低定位的误差。(2)在针对基于RSSI指纹定位中人工采集指纹数据代价的问题,本文利用无线传感器网络进行指纹数据的采集,并提出面向稀疏采样的无线指纹构建算法,利用稀疏表示技术有效降低了无线传感器网络中数据传输代价。本文的研究取得非常不错的效果。在针对测距定位中,基于智能手机的信号自适应修正算法将定位精度提高35.9%。在针对基于指纹数据定位中人工采集指纹成本的问题上,本文的面向稀疏采样的无线指纹构建算法在保证指纹数据精度的条件下,有效地降低了采集成本。
[Abstract]:Location information is an important link between the physical world and cyberspace, and is an extremely important factor in the age of the Internet of things, which is closely related to the social life of human beings. Nowadays, people's life style has changed, 80% of the time is in indoor environment. However, GPS technology can not achieve satisfactory positioning accuracy in indoor environment. With the WiFi network deployed in a wide range of indoor locations, the use of smart phones has become a "prairie fire" trend. More and more attention has been paid to the research of WiFi indoor positioning based on smart phones. At present, WiFi indoor location algorithm based on smart phone is mainly divided into two kinds: indoor location algorithm based on wireless ranging and indoor location algorithm based on received signal intensity indicating (RSSI) fingerprint. These two localization algorithms meet a lot of challenges in the actual localization. The indoor localization algorithm based on ranging is based on the principle of wireless ranging for geometric constraint localization. Because of the multipath effect of indoor environment, the signal intensity fluctuates greatly. Thus, the positioning accuracy is very low. The premise of fingerprint location algorithm based on RSSI is to build an accurate fingerprint database. However, the construction of RSSI fingerprint data requires a great deal of manual cost to carry out field survey and collection. In view of the challenges encountered in indoor location based on ranging and RSSI fingerprint, the following two aspects are studied in this paper: (1) aiming at the problem that the large error of wireless ranging leads to the large positioning error, In this paper, an adaptive signal correction algorithm based on smart phone is proposed. The correction factor is used to improve the accuracy of wireless ranging and reduce the positioning error. (2) aiming at the cost of manually collecting fingerprint data in fingerprint location based on RSSI. In this paper, we use wireless sensor networks to collect fingerprint data, and propose a sparse sampling oriented fingerprint construction algorithm. The sparse representation technology can effectively reduce the cost of data transmission in wireless sensor networks. The research in this paper has achieved very good results. In the localization of ranging, the signal adaptive correction algorithm based on smart phone can improve the precision of location by 35.9. Aiming at the cost of fingerprint acquisition based on fingerprint data location, the wireless fingerprint construction algorithm for sparse sampling can effectively reduce the cost of fingerprint acquisition under the condition of ensuring the precision of fingerprint data.
【学位授予单位】：安徽工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN92

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