本文選題：無(wú)線傳感網(wǎng) + 三維定位��； 參考：《蘭州交通大學(xué)》2015年碩士論文

【摘要】：近年來(lái),無(wú)線傳感器網(wǎng)絡(luò)(Wireless Sensor Network,WSN)在智能醫(yī)療監(jiān)護(hù)、環(huán)境監(jiān)控、軍事偵察等諸多領(lǐng)域發(fā)揮著越來(lái)越重要的作用。WSN在諸多領(lǐng)域的應(yīng)用都需要對(duì)節(jié)點(diǎn)自身位置的定位,離開(kāi)了位置信息,WSN感知的數(shù)據(jù)也就失去了意義。目前WSN定位技術(shù)的研究主要集中在二維平面,而現(xiàn)實(shí)環(huán)境中的傳感器節(jié)點(diǎn)基本都分布在三維場(chǎng)景中。因此,研究具有高精度、低成本、低能耗的無(wú)線傳感器網(wǎng)絡(luò)三維空間節(jié)點(diǎn)定位技術(shù)及求精方法已成為目前WSN研究最重要的方向之一。首先,本文綜述了無(wú)線傳感器網(wǎng)絡(luò)的研究背景、意義以及支撐WSN網(wǎng)絡(luò)的關(guān)鍵技術(shù),同時(shí)對(duì)無(wú)線傳感器定位技術(shù)以及目前國(guó)內(nèi)外發(fā)展現(xiàn)狀,特別是對(duì)目前定位技術(shù)中具有代表性的定位模型、算法進(jìn)行了闡述。隨后介紹了定位技術(shù)的相關(guān)概念、性能指標(biāo)及其分類(lèi)。其次,定位技術(shù)的定位精度很大程度上取決于WSN網(wǎng)絡(luò)中錨節(jié)點(diǎn)密度的大小,而錨節(jié)點(diǎn)的多少直接決定網(wǎng)絡(luò)成本的高低。另外,國(guó)內(nèi)外研究目前大多停留在二維層面,對(duì)三維空間下的定位技術(shù)研究還不充分。因此,本文對(duì)三維空間下基于移動(dòng)錨節(jié)點(diǎn)輔助定位技術(shù)進(jìn)行了學(xué)習(xí)后,提出改進(jìn)算法:在三維場(chǎng)景下基于接收信號(hào)強(qiáng)度指示(Received Signal Strength Indicator,RSSI)測(cè)距并利用移動(dòng)錨節(jié)點(diǎn)輔助定位算法,同時(shí),采用移動(dòng)錨節(jié)點(diǎn)按照改進(jìn)軌跡移動(dòng),不僅能夠?qū)崿F(xiàn)三維定位,而且可以解決在固定錨節(jié)點(diǎn)較少環(huán)境下對(duì)未知節(jié)點(diǎn)的定位問(wèn)題。再次,RSSI測(cè)距硬件要求低,定位精度較高,但RSSI測(cè)距需要依靠傳感器節(jié)點(diǎn)接收信號(hào)的強(qiáng)弱來(lái)實(shí)現(xiàn)定位,容易被環(huán)境等因素所干擾,導(dǎo)致由RSSI得出的位置信息存在著一定誤差,本文通過(guò)對(duì)RSSI測(cè)距的原理、影響因素、其改進(jìn)算法ERSS的學(xué)習(xí)研究后,在ERSS算法的基礎(chǔ)上對(duì)RSSI值進(jìn)行修正,對(duì)符合ERSS條件的RSSI值通過(guò)加權(quán)質(zhì)心算法,再進(jìn)行擴(kuò)展卡爾曼濾波處理,實(shí)現(xiàn)對(duì)RSSI的優(yōu)選,從而提高定位精度。最后,通過(guò)Matlab搭建了一個(gè)能夠適用于多種算法的公共平臺(tái),通過(guò)仿真驗(yàn)證,本文改進(jìn)方法與傳統(tǒng)定位方法相比,在定位精度、執(zhí)行時(shí)間、網(wǎng)絡(luò)覆蓋率等方面有了一定的提升。
[Abstract]:In recent years, Wireless Sensor Network (WSN) plays a more and more important role in many fields, such as intelligent medical monitoring, environmental monitoring, military reconnaissance and so on. Without location information, WSN-aware data is meaningless. At present, the research of WSN localization technology is mainly focused on the two-dimensional plane, and the sensor nodes in the real environment are basically distributed in the three-dimensional scene. Therefore, it has become one of the most important research directions of WSN to study the location technology and refinement method of wireless sensor networks with high precision, low cost and low energy consumption. First of all, this paper summarizes the research background, significance and key technologies supporting WSN. At the same time, the wireless sensor positioning technology and the current development situation at home and abroad are discussed. Especially, the typical localization model and algorithm are introduced. Then the concept, performance index and classification of positioning technology are introduced. Secondly, the location accuracy of location technology depends on the density of anchor nodes in WSN network to a large extent, and the number of anchor nodes directly determines the cost of the network. In addition, most of the research at home and abroad at present stay at the two-dimensional level, the positioning technology in three-dimensional space is not enough. Therefore, after studying the mobile anchor node aided location technology in 3D space, an improved algorithm is proposed: based on received signal strength indicator (RSSI) ranging in 3D scene and using mobile anchor node aided location algorithm. At the same time, moving anchor nodes can not only realize 3D positioning, but also solve the problem of locating unknown nodes in less fixed anchor nodes. Thirdly, the hardware requirement of RSSI ranging is low, and the positioning accuracy is high. However, RSSI ranging needs to rely on the strong or weak signal received by sensor nodes to realize location, which is easily interfered by environment and other factors, which leads to some errors in the location information obtained by RSSI. After studying the principle of RSSI ranging, the influencing factors and the improved algorithm ERSS, the RSSI value is modified on the basis of ERSS algorithm, and the RSSI value according to ERSS condition is modified by weighted centroid algorithm, and then the extended Kalman filter is used to deal with the RSSI value. To achieve the optimal selection of RSSI, thus improve the positioning accuracy. Finally, a common platform which can be applied to many algorithms is built by Matlab. Through simulation, the improved method is compared with the traditional localization method, and has a certain improvement in location accuracy, execution time, network coverage and so on.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：TN929.5;TP212.9

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