基于蓝牙的室内定位系统设计与实现

发布时间：2018-05-18 08:20

本文选题：室内定位 + 神经网络　；参考：《东华大学》2017年硕士论文

【摘要】：如今随着科技的不断进步,几乎人人都拥有一部属于自己的智能手机,并希望手机给他们的日常生活带来更多的便利,其中基于位置的服务(LBS)受到很多人欢迎,室内定位技术在医院远程看护、工厂资产管理、推送信息等领域蕴含着巨大的发展空间,近年来成为一个研究热点问题。传统的蓝牙技术由于功耗高、穿透性差、信号传输距离短等原因,在室内定位领域没有得到广泛的应用,而低功耗蓝牙4.0通信标准的发布后,功耗、传输距离、信号强度等方面都有了明显的改善,定位技术得到广泛应用。本文改进了现有的室内定位算法,在该改进的算法基础上,设计了基于低功耗蓝牙技术的定位系统,主要的工作如下:(1)在BLE室内定位技术的基础上,提出了改进的基于RSSI(接收信号强度指示)的BP神经网络指纹算法,用该算法进行室内定位。对传统BP神经网络的不足进行了改进,在数据离线采集阶段利用改进的离群群点检测算法和计算平均值的方法确保指纹数据库的准确性,在位置在线定位阶段通过几何距离法提高定位的精度。(2)设计了蓝牙模块中倒F天线以及iBeacon广播基站的软硬件设计。(3)利用android移动客户端与iBeacon基站协同完成数据采集和处理的过程,利用本文提出的新算法进行定位,将计算量大的工作交给服务器来处理,智能手机只负责信息采集与结果展示,有效的降低了系统的维护成本,提高了系统响应速度,测试结果显示平均定位误差为1.87m,与类似文献报道的方法相比,定位误差降低了28%,且可以满足基本的室内定位要求。
[Abstract]:Nowadays, with the development of science and technology, almost everyone has a smartphone of their own and hopes that it will bring more convenience to their daily life, among which location-based service LBSis is popular with many people. Indoor positioning technology has great development space in the field of hospital remote nursing, factory asset management, push information and so on, and has become a hot research issue in recent years. Because of the high power consumption, poor penetration and short signal transmission distance, the traditional Bluetooth technology has not been widely used in the field of indoor positioning, but the low power Bluetooth 4.0 communication standard, power consumption, transmission distance, and so on, The signal intensity has been improved obviously, and the localization technology has been widely used. In this paper, the existing indoor positioning algorithm is improved. On the basis of the improved algorithm, a positioning system based on low-power Bluetooth technology is designed. The main work is as follows: 1) based on the BLE indoor positioning technology, An improved BP neural network fingerprint algorithm based on RSSI (received signal intensity indication) is proposed. The shortcomings of traditional BP neural network are improved, and the accuracy of fingerprint database is ensured by using the improved outlier detection algorithm and the method of calculating average value in the off-line data acquisition stage. In the phase of position online positioning, the precision of location is improved by geometric distance method.) the inverted F antenna in Bluetooth module and the hardware and software design of iBeacon broadcast base station are designed. The software and hardware design of android mobile client and iBeacon base station are used to complete the process of data acquisition and processing. Using the new algorithm proposed in this paper to locate, the work of large amount of calculation is handed over to the server to handle. The smart phone is only responsible for information collection and result display, which effectively reduces the maintenance cost of the system and improves the system response speed. The test results show that the average positioning error is 1.87m. compared with the similar methods reported in the literature, the positioning error is reduced by 28% and can meet the basic indoor positioning requirements.
【学位授予单位】：东华大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN925

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