为保障室内人员及物品安全,满足人们日常生活中对室内各个物品准确位置认知的需求,需要对室内定位系统进行设计;当前方法是利用红外线、超声波或射频识别技术对室内定位系统进行设计,系统中硬件设备昂贵,设备安装过程复杂,导致系统安装对环境要求太高,不适合应用于规模较大的室内,存在定位系统设计效率低、速度慢的问题;为此,提出一种基于超宽带技术的室内定位系统设计方法;该方法首先利用历史室内定位系统设计方法和当前室内定位系统设计需求,构建室内定位系统硬件,然后以该硬件为依据,采用模糊C均值法将室内物品特征空间信息数据,划分为若干个类,并将这若干个数据类别中数据点最多的类别留下,最后依据基于类匹配的室内粗定位和利用加权K近邻算法的室内精定位,完成对室内定位系统的设计;实验结果证明,所提方法可以准确地对室内定位系统进行设计,减少室内定位时间,提高定位效率,为该领域的研究发展提供有力依据.%In order to ensure the safety of indoor personnel and goods,and meet the needs of people's daily life,the indoor positioning system should be designed.The current method is to design the indoor positioning system using ultrasonic or infrared,radio frequency identification technology,system hardware equipment expensive,complex installation process,cause the system installation requirements of the environment is too high,not suitable for large scale indoor positioning system design,the problems of low efficiency and slow speed.This paper presents a design method of indoor positioning system based on UWB technology.This method firstly uses the history of indoor positioning system design method and the design requirements of the indoor positioning system,indoor positioning system hardware construction,and then to the hardware on the basis of using fuzzy C means method of indoor items feature space information data,divided into several categories,and a number of data categories in the largest category of data points left fine positioning and indoor use,indoor location class matching based on weighted K nearest neighbor algorithm based,complete the design of indoor positioning system.The experimental results show that the proposed method can be used to design the indoor positioning system,reduce the indoor positioning time and improve the positioning efficiency.
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