本文關(guān)鍵詞： 無(wú)線網(wǎng)絡(luò) 定位 隱馬爾可夫模型　出處：《上海交通大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著無(wú)線網(wǎng)絡(luò)的日益普及以及GPS[1]系統(tǒng)的廣泛使用,無(wú)線網(wǎng)絡(luò)中用戶的位置信息越發(fā)重要。目前各種互聯(lián)網(wǎng)產(chǎn)品都會(huì)推出基于LBG(Location Based Service)的服務(wù),其中無(wú)線設(shè)備用戶的物理位置信息是這些服務(wù)的基礎(chǔ)。然而普遍使用著的GPS系統(tǒng)存在著很多問題,如在一些有遮蔽物的應(yīng)用場(chǎng)景中無(wú)法使用,因而無(wú)線網(wǎng)絡(luò)中的定位問題仍然有很大的空間供人們研究。 目前被廣泛研究的定位方法根據(jù)其所利用的測(cè)量信息可以被分為兩種[16],一種是以細(xì)粒度[10]的精確測(cè)量值為主要依據(jù)的基于距離的定位方法；另一種是以粗粒度的較不精確的測(cè)量值為主要依據(jù)的基于連接信息[31]的定位方法。對(duì)于基于距離的定位方法,其主要思路是依靠獲得的精確測(cè)量值計(jì)算無(wú)線信號(hào)發(fā)射源與接收源之間的距離,之后求解其相對(duì)位置。對(duì)于基于連接信息的定位方法,其主要思路是依靠獲得的連接信息判斷無(wú)線信號(hào)發(fā)射源與接收源距離間的關(guān)系,之后求解各節(jié)點(diǎn)可能的范圍,最后根據(jù)相應(yīng)目標(biāo)函數(shù)得到其相對(duì)位置。 我們通過(guò)對(duì)大規(guī)模無(wú)線網(wǎng)絡(luò)用戶數(shù)據(jù)的分析,發(fā)現(xiàn)用戶在移動(dòng)過(guò)程中具有移動(dòng)范圍穩(wěn)定性、移動(dòng)過(guò)程時(shí)空相關(guān)性以及社會(huì)相關(guān)性。并設(shè)計(jì)了基于這些特性的定位方法SOMA。最終通過(guò)基于真實(shí)的無(wú)線網(wǎng)絡(luò)移動(dòng)數(shù)據(jù)的實(shí)驗(yàn)驗(yàn)證了SOMA的性能。 實(shí)驗(yàn)發(fā)現(xiàn),SOMA的定位精確度比已知的定位方案的精確度高了不少,以平均絕對(duì)誤差MAE為指標(biāo),MDS[30]的MAE值比SOMA高了近6倍；TSLRL[24]比SOMA高了近10倍,TSL比SOMA高了近10倍,LRL比SOMA高了近11倍,而Centroid[12]方法比SOMA高了近5倍。實(shí)驗(yàn)充分證明了我們的發(fā)現(xiàn)，即用戶移動(dòng)過(guò)程中存在著很強(qiáng)的社會(huì)相關(guān)性，對(duì)其加以利用可以極大的提高用戶的定位的精確度。就我們目前的知識(shí)，，這是第一次有人將該特性應(yīng)用于無(wú)線網(wǎng)絡(luò)用戶的定位問題中來(lái)。
[Abstract]:With the increasing popularity of wireless networks and GPS. [(1) widespread use of the system. The location information of users in wireless networks is becoming more and more important. At present, a variety of Internet products will launch services based on LBG(Location Based Service. The physical location information of wireless device users is the basis of these services. However, there are many problems in the commonly used GPS system, such as in some application scenarios with shelter. Therefore, there is still a lot of space for people to study the localization problem in wireless networks. Currently widely studied localization methods can be divided into two types according to the measurement information they use. [16], one is fine grained. [10] based on distance based positioning methods based mainly on precise measurements of coarse-grained values; another method based on connection information based on less precise measurements of coarse granularity. [The main idea of this method is to calculate the distance between the wireless signal transmitting source and the receiving source based on the obtained accurate measurement value. Then the relative position is solved. For the location method based on the connection information, the main idea is to judge the relationship between the radio signal transmitting source and the receiving source distance based on the connection information obtained. Then the possible range of each node is solved and its relative position is obtained according to the corresponding objective function. By analyzing the user data of large-scale wireless network, we find that the user has the stability of mobile range in the process of moving. Finally, a localization method based on these characteristics is designed. Finally, the performance of SOMA is verified by experiments based on real wireless network mobile data. The experimental results show that the accuracy of SOMA is much higher than that of the known positioning scheme, and the average absolute error (MAE) is taken as the index. [The MAE value of 30] is nearly 6 times higher than that of SOMA. [24] TSL is nearly 10 times higher than SOMA, nearly 10 times higher than SOMA, 11 times higher than SOMA, and Centroid. [The method is nearly 5 times higher than SOMA. The experiment fully proves our finding that there is a strong social correlation in the process of user movement. It is the first time that this feature has been applied to the location problem of wireless network users for the first time as far as our current knowledge is concerned.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TN929.5;P228.4

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