基于WiFi无线定位的关键技术研究

发布时间：2018-07-28 19:57

【摘要】：社会高速发展的同时,室内定位服务日渐成为继室外定位技术之后又一重要的定位手段,越来越多的工作和生活领域需要精确的室内定位服务。虽然典型的室外定位技术(如：GPS定位技术)可以得到更好的定位精度,但是它的信号极容易受天气和其他外部因素影响,而且穿透建筑等障碍物的能力较差,因此,要实现精确的室内定位,需要使用其他技术解决方案。通过无线WiFi网络协助室内定位,很大程度上可以解决GPS等室外定位技术在建筑密集区域和室内区域的局限,扩展了定位的服务领域。本文主要研究的是基于WiFi网络的位置指纹识别定位技术。基于WiFi无线网络的位置指纹识别定位技术具有误差小、定位速度快、可扩展性好等特点,成为继GPS定位、声波定位等定位技术后的又一重要的定位手段。首先本论文简要介绍了国内外的基于多种不同技术方案的室内定位技术,接着介列举了多种影响室内定位精度的主要因素；然后通过对典型室内传播模型的介绍,详细分析了基于这些传播模型的定位算法。本文第三章首先介绍了几种典型的位置指纹定位算法,分析了这几种算法的优点和缺点,并针对这些缺点,创新性的提出了对数匹配算法、RSSI加权匹配算法,与传统的K加权最近邻算法(WKNN)相结合,改进了取点规则,提出了改进的综合算法。使用自主开发的定位软件进行模拟定位测试,对得到的定位结果进行仿真分析,验证了改进的综合算法的定位精度要优于典型的WKNN算法。最后,在实际环境中进行测试。使用自主开发的定位软件、笔记本电脑终端以及实验室无线路由器等设备进行定位测试。分别测试WKNN算法和改进的综合算法。最后对实验结果(即定位误差)进行分析比对,验证了改进的综合算法的定位精度在WKNN算法的基础上有了较大的提高,与第三章的软件模拟测试结果相符。
[Abstract]:At the same time, with the rapid development of society, indoor positioning service has become an important means of positioning after outdoor positioning technology. More and more work and life fields need accurate indoor positioning services. While typical outdoor positioning techniques (such as the: GPS) can achieve better positioning accuracy, their signals are extremely vulnerable to weather and other external factors and are less able to penetrate obstacles such as buildings. To achieve accurate indoor positioning, other technical solutions are required. With the help of wireless WiFi network, outdoor positioning technology, such as GPS, can solve the limitation of building intensive area and indoor area to a great extent, and expand the service field of location. This paper mainly studies the location fingerprint identification and location technology based on WiFi network. The location fingerprint identification and location technology based on WiFi wireless network has the characteristics of small error, fast positioning speed and good expansibility. It has become another important localization method after GPS positioning and acoustic positioning. First of all, this paper briefly introduces the indoor positioning technology based on many different technical schemes at home and abroad, then enumerates a variety of main factors that affect the indoor positioning accuracy, and then introduces the typical indoor propagation model. The localization algorithms based on these propagation models are analyzed in detail. In the third chapter, several typical location fingerprint location algorithms are introduced, the advantages and disadvantages of these algorithms are analyzed, and a logarithmic matching algorithm named RSSI weighted matching algorithm is proposed to solve these disadvantages. Combining with the traditional K-weighted nearest neighbor algorithm (WKNN), this paper improves the rule of taking points and proposes an improved synthesis algorithm. Using the self-developed localization software to carry on the simulation localization test, the simulation analysis to the localization result obtained, has verified the improved synthesis algorithm localization accuracy is superior to the typical WKNN algorithm. Finally, the test is carried out in a real environment. Use self-developed positioning software, notebook computer terminals and laboratory wireless routers and other equipment for location testing. The WKNN algorithm and the improved synthesis algorithm are tested respectively. Finally, the experimental results (that is, positioning errors) are analyzed and compared, and it is verified that the location accuracy of the improved synthetic algorithm is greatly improved on the basis of the WKNN algorithm, which is consistent with the results of the software simulation test in Chapter 3.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN92

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