本文選題：定位技術(shù) + 無線局域網(wǎng)��； 參考：《蘭州交通大學(xué)》2016年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)的高速發(fā)展和移動智能終端的普及應(yīng)用,人們對基于位置服務(wù)(Location Based Services,LBS)的需求日益增加。目前LBS已經(jīng)被廣泛應(yīng)用于社會生活和工業(yè)生產(chǎn)的多個領(lǐng)域,LBS應(yīng)用中最關(guān)鍵的部分是對位置信息的獲取,即定位技術(shù),定位技術(shù)的好壞直接影響著LBS的應(yīng)用效果。盡管衛(wèi)星導(dǎo)航定位技術(shù)比較成熟,能夠滿足大多數(shù)室外位置服務(wù)的需求,但當將其應(yīng)用在室內(nèi)時并不能取得理想的效果,因此對室內(nèi)定位技術(shù)的研究越來越受到人們的關(guān)注。現(xiàn)有的室內(nèi)定位技術(shù)大多數(shù)都需要相關(guān)的專用硬件設(shè)備,使得定位成本高、應(yīng)用不靈活,很難得到大范圍的應(yīng)用和推廣�；跓o線局域網(wǎng)(Wireless Local Area Networks,WLAN)的室內(nèi)定位技術(shù)無需專用的硬件設(shè)備,僅利用相應(yīng)的軟件便可通過移動智能終端進行定位,定位成本低并能滿足大多數(shù)室內(nèi)定位精度的要求,因此WLAN定位技術(shù)成為了室內(nèi)定位的首選。在WLAN室內(nèi)定位中,位置指紋定位算法以定位精確度高、抗干擾能力強、定位成本低、支持多終端設(shè)備等優(yōu)點成為應(yīng)用最廣泛的定位算法。盡管如此,位置指紋定位仍存在尚待完善的部分,如RSS時變性會造成定位精度下降和指紋庫過期等。本文針對該問題給出了相應(yīng)的解決方案,通過實驗對比證明了方案的可行性。本文主要工作如下:(1)為能真實的反映RSS分布情況,提出了一種基于混合高斯分布模型的位置指紋定位算法。針對不同的RSS概率分布,采用相對應(yīng)的分布模型對其進行曲線擬合,擬合曲線更符合真實的RSS分布,因此構(gòu)建的位置指紋數(shù)據(jù)庫更加可靠。借鑒重疊度在地圖匹配和膚色檢測中的應(yīng)用,使用兩個指紋特征RSS分布的重疊度表示兩個位置指紋之間的相似度,對與待測點指紋相似度最大的前K個參考點,依據(jù)相似度大小再次分配不同權(quán)值進行質(zhì)心加權(quán)運算,以估計待測點位置。(2)針對RSS的時變特性導(dǎo)致位置指紋庫過期的問題,本文提出一種利用用戶反饋信息對指紋庫進行更新和維護的方法。用戶反饋的信息包括自身所在位置和該點采集的各AP信號強度,依據(jù)打分機制對定位點指紋所包含的AP進行打分,刪除關(guān)閉的AP和添加開啟的AP以對指紋庫進行更新。考慮到定位結(jié)果與用戶實際位置不一致的情況,允許用戶更正自身位置,并用聚類檢測方法判斷用戶更正結(jié)果是否可信。實驗結(jié)果表明,利用用戶反饋的信息更新指紋庫比不更新和人工低頻更新指紋庫的定位效果更好。
[Abstract]:With the rapid development of the Internet and the widespread application of mobile intelligent terminals, the demand for location based Services (LBS) is increasing day by day. At present, LBS has been widely used in many fields of social life and industrial production. The most important part of LBS application is the acquisition of location information, that is, location technology, which directly affects the application effect of LBS. Although satellite navigation and positioning technology is mature and can meet the needs of most outdoor location services, it can not achieve ideal results when it is applied indoors, so more and more attention has been paid to the research of indoor positioning technology. Most of the existing indoor positioning technology needs special hardware equipment, which makes the positioning cost high, the application is inflexible, and it is difficult to be widely used and popularized. The indoor positioning technology based on Wireless Local Area Network (WLAN) does not need special hardware equipment. It can be located by mobile intelligent terminal only by using the corresponding software. The positioning cost is low and can meet the requirements of most indoor positioning accuracy. Therefore, WLAN positioning technology has become the first choice of indoor positioning. In WLAN indoor positioning, location fingerprint location algorithm has become the most widely used location algorithm because of its high accuracy, strong anti-interference ability, low positioning cost and support for multi-terminal equipment. In spite of this, there are still some parts to be improved in location fingerprint location, for example, RSS time-varying will result in the decrease of location accuracy and the expiration of fingerprint database. In this paper, the corresponding solution to this problem is given, and the feasibility of the scheme is proved by experiment. The main work of this paper is as follows: (1) in order to reflect the distribution of Gao Si, a location fingerprint location algorithm based on hybrid Gao Si distribution model is proposed. According to the different RSS probability distribution, the corresponding distribution model is used to fit the curve, the fitting curve is more consistent with the real RSS distribution, so the location fingerprint database is more reliable. Based on the application of overlap degree in map matching and skin color detection, the overlap degree of RSS distribution of two fingerprint features is used to represent the similarity between two position fingerprints. According to the similarity magnitude, different weights are assigned to weight to estimate the location of the point to be measured. (2) due to the time-varying nature of RSS, the fingerprint database of position is out of date. In this paper, a method of updating and maintaining fingerprint database using user feedback information is presented. The feedback information includes the position of the user and the intensity of each AP signal collected at this point. According to the scoring mechanism, the AP contained in the fingerprint of the location point is graded, the closed AP is deleted and the open AP is added to update the fingerprint database. Considering that the location result is not consistent with the user's actual location, the user is allowed to correct his own position, and the clustering detection method is used to judge whether the user's correction result is credible or not. The experimental results show that the location effect of the fingerprint database updated by the user feedback is better than that of the unupdated fingerprint database and the artificial low-frequency fingerprint database.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TN925.93

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本文編號：2101393