摘要:随着网络技术的不断发展，无线传感器网络技术成为一项新兴的技术，随着人们对 位置信息的要求不断增加，无线定位技术的发展将成为一个新的热点。通过这项技术， 人们可以方便的获取写字楼、地下停车场、机场、住房内的室内定位消息。并且在军事， 工业检测，灾害搜寻，环境保护方面，这项技术也将被广泛的应用，使人们的生活得到 便利。在机械设计方面，这一技术可以应用到车辆、机器人等方面，特别是无人机的群 组控制方面的应用，可以避免无人机的相撞，确保飞行的安全。 本篇论文首先介绍了无线定位技术的背景和国内外的发展状况，接着介绍了无线传感器 定位技术及定位算法的评价，对以测距和无须测距定位算法进行了介绍并说明了它们的 优缺点最终确定基于蓝牙的 RSSI 的无线定位。通过一系列实验分析，经过拟合得到最终 的数学模型。最后实验分析得到的数学模型的正确性。定位精度大约在 0.5 米。69416

毕业论文关键词: 无线定位 RSSI BLE 拟合

Title:    Wireless location based on RSSI

Abstract:

With the continuous development of network technology and people's requirement of location information, wireless sensor network technology has developed into an advanced technology. The development of wireless location technology will become a new hot spot. Through this technology, people can easily get the indoor positioning information of office buildings, underground parking, airport and so on. In these areas such as military, industrial testing, disaster search, and environmental protection, the technology will also be widely used, and it will make people's lives convenient. In mechanical design, this technology can be applied to the vehicle, robot and other aspects。 Especially in the application of the group control of UAV, it can avoid the collision of the UAV and to ensure the safety of flight.

This paper firstly introduced the background and domestic of wireless location technology and international development situation, and then introduced the evaluation of wireless sensor positioning technology and positioning algorithm.It is also  introduced some location algorithm  and their advantages and disadvantages. Through a series of experimental analysis, the final mathematical model is obtained. Finally, the correctness of the mathematical model is obtained by the experimental analysis. The precision of position is 0.5 metres.

Keywords：Wireless location  BLE  RSSI Fitting

目录

1 绪论 1

1.1 本论文的研究背景及意义 1

1.2 国内外发展现状 1

1.3 论文的研究内容 3

2 无线传感器定位技术 4

2.1 无线传感器网络体系及特点 4

2.2 无线传感器网络的定位方法 5

2.2.1 基于 TOA 的测距方法 6

2.2.2 基于 AOA 的测距方法 6

2.2.3 基于 RSSI 的测距方法 7

2.3 基于测距的定位算法 8

2.3.1 三边测量算法 8

2.3.2 三角定位算法 9

2.3.3 最大似然估计法 10

2.4 基于无需测距的定位算法