基于WLAN的AP密集分布的室内定位关键技术研究

The proposed research on indoor positioning technology based on dense AP in WLAN and the analysis of the system reliability is significant. The two main tasks: (1) the improved key technology of indoor positioning to minimize the random of RSS in order to improved confidence probability of positioning accuracy within 1m ; (2) the technology of analysis and warning cloud for system, it can enhance the reliability of location information. Recently, wireless network based indoor positioning technology has being develop rapidly, however, the expansion of location area and the rapid increase of the number of access points make indoor environments are complicated and vary significantly and the fact that the wireless signal is affected by the propagation environment greatly, existing technology for indoor positioning cannot meet the requirement of high accuracy and real-time reaction for location based services (LBS). In this proposal, there are two innovations, one is the accuracy of clustering algorithm can be improved significantly by applying ZCA whitening on the RSS signal, through the access point selection based on information gain weight, the computational complexity can be reduced and a more optimal positioning access point set can be obtained, and the nonlinear positioning characteristics of RSS signal can be fully used by applying the linear component extracting algorithm based on kernel function. In theory, all these techniques will significantly improve the confidence probability of positioning accuracy within 1m. Another innovation is to build analysis warning cloud model for location fingerprint database, it can improve the reliability of location information. To investigate the reliability and availability of the system is the key for system effectiveness. This proposal is significant because it not only address the theoretical issue, but also benefit the widely application of LBS for science and technology strategy in our country.

研究基于公共WLAN下AP密集分布的室内低成本定位关键技术及系统的可靠性分析具有重要的实际意义。研究：（1）最大化降低RSS信号随机性的关键技术，提高亚米级定位精度的置信率；（2）定位系统的分析和预警云技术，增加位置信息的可靠性。公共WLAN室内接入点大幅增多，RSS信号表现出多态性和随机性，已有的室内定位技术已不能满足基于位置信息服务对定位精度及其可靠性的要求。本项目的创新之处在于提出了将白化、信息增益权重准则、提取非线性特征函数等关键技术用于RSS信号的随机性处理，理论上，可保证在数据采集量相同情况下，大幅度提高亚米级定位精度的置信概率。另一个创新之处是将建立定位指纹库的分析和预警云模型，增加系统解算位置信息的可靠性。研究系统可靠性和有效性是保证系统发挥效能的关键，因此本项目的研究对推动国家关于科技战略中基于位置服务的广泛应用具有非常重要的理论指导意义和应用价值。

公共WLAN室内接入点大幅增多，RSS信号表现出多态性和随机性，已有的室内定位技术已不能满足基于位置信息服务对定位精度及其可靠性的要求。因此研究基于公共WLAN下AP密集分布的室内低成本定位关键技术及系统的可靠性分析具有重要的实际意义。研究：（1）最大化降低RSS信号随机性的关键技术，提高亚米级定位精度的置信率；（2）定位系统的分析和预警云技术，增加位置信息的可靠性。本项目的研究成果在于提出了将白化、信息增益权重准则、提取非线性特征函数等关键技术用于RSS信号的随机性处理，理论上，可保证在数据采集量相同情况下，大幅度提高亚米级定位精度的置信概率。另一个成果是将建立定位指纹库的分析和预警云模型，增加系统解算位置信息的可靠性。研究系统可靠性和有效性是保证系统发挥效能的关键，因此本项目的研究对推动国家关于科技战略中基于位置服务的广泛应用具有非常重要的理论指导意义和应用价值。