基于无线传感网的室内定位技术研究

发布时间：2018-06-05 07:02

本文选题：室内定位 + 无线传感器网络　；参考：《华东师范大学》2015年硕士论文

【摘要】：随着移动互联网技术的蓬勃发展,基于位置的服务(Location Based Services, LBS)越来越成为人们生活中必不可少的需求。其中定位技术,即位置信息的获取,是实现基于位置的服务的必要前提和关键。卫星导航系统已经广泛应用于室外的LBS中,但是由于卫星信号无法穿透墙壁等障碍物,使用卫星导航系统无法实现室内准确定位,制约了室内LBS的发展。基于无线传感器网络的室内定位技术正好弥补了GPS室内定位的不足,可以为地下停车场等场所提供实时的位置和导航信息。目前,已有的室内无线定位技术大多需要额外的硬件设备,定位成本高,不易于推广。基于接收信号强度指示(Received Signal Strength Indicator, RSSI)的定位技术不需要添加额外设备,其中RSSI可直接在无线通信过程中获得。因此基于RSSI的定位技术成为室内定位研究的首选方案。本文在对无线传感器网络定位算法深入分析的基础上,对基于RSSI的定位算法,即基于RSSI测距的定位算法和基于特征指纹的定位算法分别开展了系统地调查与研究。本文的研究内容和主要贡献归纳如下：(1)在对信号传播模型研究的基础上,提出基于RSSI的自适应分段曲线拟合室内定位算法。通过实验验证本文提出的改进算法拥有更好的定位精度和更好的环境适应性。(2)研究现有基于特征指纹的定位算法。将定位过程划分为四个阶段,分别讨论定位各阶段原始RSSI预处理方法、求解近邻量度、k近邻选择和位置坐标确定方法对室内定位精度的影响,确定适合当前室内环境的最优定位算法。(3)设计基于无线传感网的定位算法可供选择的室内定位原型系统。实验结果表明改进后的基于RSSI定位算法和优化后的基于特征指纹的定位算法具有更高的定位精度。
[Abstract]:With the rapid development of mobile Internet technology, location Based Services, LBS) has become an indispensable requirement in people's daily life. Location technology, that is, the acquisition of location information, is the necessary prerequisite and key to realize location-based services. Satellite navigation system has been widely used in outdoor LBS, but because satellite signal can not penetrate obstacles such as walls, the use of satellite navigation system can not achieve accurate indoor positioning, which restricts the development of indoor LBS. The indoor location technology based on wireless sensor network can make up for the deficiency of GPS indoor location, and can provide real-time location and navigation information for underground parking and other places. At present, most of the existing indoor wireless positioning technology need additional hardware equipment, positioning cost is high, it is difficult to be popularized. The location technique based on received signal strength indication received Signal Strength Indicator, RSSI) does not need to add additional equipment, where RSSI can be obtained directly during wireless communication. Therefore, positioning technology based on RSSI has become the first choice of indoor positioning research. Based on the deep analysis of wireless sensor network localization algorithm, this paper makes a systematic investigation and research on the location algorithm based on RSSI, that is, the location algorithm based on RSSI ranging and the location algorithm based on characteristic fingerprint. The research contents and main contributions of this paper are summarized as follows: (1) based on the research of signal propagation model, an adaptive segmented curve fitting indoor localization algorithm based on RSSI is proposed. Experimental results show that the improved algorithm has better localization accuracy and better environmental adaptability.) the existing localization algorithms based on feature fingerprint are studied. The positioning process is divided into four stages, and the original RSSI pretreatment method for each stage is discussed respectively, and the influence of nearest neighbor measurement and location coordinate determination method on indoor positioning accuracy is solved. To determine the optimal location algorithm suitable for the current indoor environment, the prototype system of indoor location based on wireless sensor network is designed. The experimental results show that the improved localization algorithm based on RSSI and the optimized algorithm based on feature fingerprint have higher localization accuracy.
【学位授予单位】：华东师范大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP212.9;TN929.5

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