无线自组网定位新技术研究

无线自组网定位新技术研究(任务书,开题报告,论文17000字)
摘  要
    在科学技术日新月异，经济迅速发展的当今社会，人们对各方面的技术体验要求提高，无线定位技术就是其中一个。
目前室外定位技术基本成熟，比如采用基于人造卫星定位和基于移动运营网的基站等定位技术，但由于室内环境通常障碍物，干扰源多，它们的定位精度不高，因此并不适用于室内。而在室内场所，网络广泛被广泛使用，布设便捷，通讯快速，可作为室内定位的支持技术。本课题为无线自组网定位新技术的研究，主要就是针对室内定位，通过几种无线组网技术方案比较，笔者最终选定用wifi定位方案，定位过程：客户端侦查周围各个AP的MAC地址（全球唯一），接收同时无线路由器AP发射的RSSI信号，检测强弱（信号强弱反映客户端与不同位置AP之间的距离），然后将MAC地址和信号强弱发送给相应的服务器，服务器利用这些信息数据，同时查询这些预先AP设定好的位置，通过某种（或几种算法融合）定位算法，最终估测出客户端所处的位置。
接下来是定位算法的研究。我深入学习各种定位算法：非距离定位算法包括质心，凸规划，DV-Hop ，APIT 算法和距离式定位算法包括RSSI（信号强度），AOA（到达角度）TOA（到达时间），TDOA（到达时间差）TOF（飞行时间））三边测量定位算法，三角测量法(triangulation)，Bounding-Box 算法以及指纹定位技术。我从最基础的三边测量定位算法入手，弄清原理，分析误差原因，并改进算法。后面我研究了另一种完全不同的方法：指纹定位技术，实现了NN  、KNN 、WKNN 、Bayes算法定位，并且通过实验确定了含有与外界具体环境有关的最佳参数，实现误差最小，最后我尝试改进指纹算法。最终在本次研究的所有方法中选出一种定位精度最高的方法。 [资料来源：http://think58.com]
关键词：无线定位；WiFI自组网；RSSI；三边定位；指纹定位

Abstract
    In the rapid development of science and technology, the rapid development of the economy today, people on all aspects of the technical experience requirements, wireless positioning technology is one of them.
    At present, outdoor positioning technology is basically mature, such as the use of satellite positioning based on mobile positioning and base station positioning technology, but because the indoor environment is usually obstacles, interference sources, their positioning accuracy is not high, it does not apply to indoor. In the indoor places, the network is widely used, widely deployed, fast communication, can be used as indoor positioning support technology. This topic is the research of wireless ad hoc network positioning new technology, mainly for indoor positioning, through several wireless networking technology program comparison, the author finally selected with wifi positioning program, positioning process: the client to detect the MAC address of each AP (The only one in the world), receiving the RSSI signal transmitted by the wireless router AP at the same time, detecting the strength (the signal strength reflects the distance between the client and the different AP), and then sending the MAC address and signal strength to the corresponding server, Using these information data, at the same time query the location of these pre-AP settings, through some (or several algorithm fusion) positioning algorithm, and ultimately estimate the location of the client. [资料来源：http://www.THINK58.com]
    The next step is to study the localization algorithm. (APE) algorithm and distance-based localization algorithm include RSSI (Signal Intensity), AOA (Arrival Angle) TOA (arrival time), TDOA (arrival), and so on. Time difference) TOF (flight time) triangulation positioning algorithm, triangulation method, Bounding-Box algorithm and fingerprint positioning technology. I start with the most basic triangulation positioning algorithm, find out the principle, analyze the cause of the error, and improve the algorithm. I have studied another completely different method: fingerprint positioning technology, to achieve the NN, KNN, WKNN, Bayes algorithm positioning, and through experiments to determine the specific environment with the outside of the best parameters, to achieve the smallest error, and finally I Try to improve the fingerprint algorithm. Finally, in this study all the methods to select a positioning accuracy of the highest method.
Key words:Wireless positioning; WiFI ad hoc network; RSSI; trilateral positioning; fingerprint positioning [资料来源：http://think58.com]

目录
摘  要    I
Abstract    II
1 绪论    1
1.1 论文研究背景和意义    1
1.2 室内无线定位技术研究现状    2
1.3 研究内容    3
1.4研究计划和目标    3
2 WiFi无线自组网定位方法比较    5
2.1 基于距离测量的定位方法    5
2.1.1 到达时间法 TOA    5
2.1.2 到达时间差法 TDOA    5
2.1.3 到达角度法 AOA    6
2.1.4 基于RSSI信号强度的三边定位法    6
2.2 无关距离的定位方法    7
2.2.1 多边形几何质心法    7
2.2.2 基于 RSSI 的指纹定位法    8
2.3 基于 RSSI 的指纹定位匹配算法    9
2.3.1 NNSS算法    9
2.3.2 KNN算法    9
2.3.3 WKNN 算法    10
2.3.4 朴素贝叶斯算法    10

3 三边定位算法研究    13
3.1 三边定位算法局限性分析    13
3.2 改进三边定位算法设计    14
3.2.1用理想条件下的三边定位算法模拟现实环境定位    14
3.2.2三边定位改进方案一：分类思想    15
3.2.3三边定位改进方案二：增加AP数量    16
3.2.4改进三边定位算法思路总结    18
3.3 本章小结    19
4 指纹定位匹配算法研究    20
4.1 NNSS 算法    21
4.2 KNN算法    21
4.3 WKNN 算法    22
4.4 朴素贝叶斯算法    24
4.5 朴素贝叶斯改进算法一    24
4.6朴素贝叶斯改进算法二    26
4.7 贝叶斯定位算法改进心得    27
5 总结与展望    29
5.1总结    29
5.2不足与展望    30
参考文献    31
致谢    32

[资料来源：THINK58.com]

 

[资料来源：http://www.THINK58.com]