【摘要】：無線傳感器網(wǎng)絡(luò)(Wireless Sensor Networks,WSNs)是指由大量的靜止或移動(dòng)的傳感器節(jié)點(diǎn)以自組織和多跳的方式構(gòu)建的無線網(wǎng)絡(luò),已經(jīng)應(yīng)用于眾多場(chǎng)合,如環(huán)境監(jiān)測(cè)、目標(biāo)跟蹤、交通控制、人體健康監(jiān)測(cè)、軍事以及救災(zāi)等領(lǐng)域。但是這些應(yīng)用都需要傳感器節(jié)點(diǎn)知道自身的位置信息,脫離位置信息的感知數(shù)據(jù)對(duì)于大多數(shù)應(yīng)用是沒有價(jià)值的。而通過人工部署傳感器網(wǎng)絡(luò)中的節(jié)點(diǎn)或?yàn)樾枰恢眯畔⒌墓?jié)點(diǎn)安裝GPS設(shè)備都會(huì)受到傳感器節(jié)點(diǎn)自身特點(diǎn)或應(yīng)用場(chǎng)景的限制。因此,需要傳感器節(jié)點(diǎn)通過運(yùn)行定位算法或其他機(jī)制得到自己的位置信息�，F(xiàn)有的無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位算法普遍存在著定位誤差較大、算法復(fù)雜度高、通信消耗大、不適用于移動(dòng)節(jié)點(diǎn)等其中一項(xiàng)或多項(xiàng)問題。隨著無線傳感器網(wǎng)絡(luò)技術(shù)的不斷成熟和應(yīng)用的不斷廣泛,針對(duì)移動(dòng)傳感器網(wǎng)絡(luò)的實(shí)用化節(jié)點(diǎn)定位技術(shù)具有重要的理論意義和應(yīng)用價(jià)值。本文針對(duì)移動(dòng)傳感器網(wǎng)絡(luò)中的節(jié)點(diǎn)定位問題主要完成了如下工作:本文首先分析概述了研究問題的背景和意義,并總結(jié)了現(xiàn)有的定位測(cè)距技術(shù)、定位原理以及現(xiàn)有定位算法的優(yōu)缺點(diǎn)。其次,在此基礎(chǔ)上,本文提出了一種基于矩陣填充的分布式定位算法MALL(Matrix-completion Localization)。MALL算法是利用一系列的約束條件,如節(jié)點(diǎn)間距離約束、節(jié)點(diǎn)坐標(biāo)具有低秩性、時(shí)間穩(wěn)定性等,來求解目標(biāo)函數(shù)最優(yōu)化的分布式定位算法,保證了算法較高的定位精度和易擴(kuò)展性的優(yōu)勢(shì)。由于MALL算法只涉及到凸優(yōu)化和低復(fù)雜度的非凸優(yōu)化計(jì)算,算法計(jì)算復(fù)雜度較低,能夠?qū)崿F(xiàn)移動(dòng)網(wǎng)絡(luò)節(jié)點(diǎn)的快速定位。MALL算法僅使用一跳普通鄰居節(jié)點(diǎn)信息和兩跳錨定鄰居信息來完成定位過程,具有較低的定位通信消耗。在本文中,對(duì)MALL算法的計(jì)算復(fù)雜度進(jìn)行了理論分析。最后,通過仿真實(shí)驗(yàn)對(duì)MALL算法與其他一些現(xiàn)有算法進(jìn)行了定位精度、算法運(yùn)行時(shí)間、通信消耗性能方面的比較。實(shí)驗(yàn)表明,MALL算法優(yōu)于現(xiàn)有算法。
[Abstract]:Wireless sensor network (Wireless Sensor Networks,WSNs) is a wireless network constructed by a large number of static or mobile sensor nodes in a self-organized and multi-hop manner. It has been used in many situations, such as environmental monitoring, target tracking, traffic control, and so on. Human health monitoring, military and disaster relief. However, these applications require sensor nodes to know their own location information, and sensing data without location information is of no value to most applications. However, the manual deployment of nodes in sensor networks or the installation of GPS devices for nodes that require location information will be limited by the sensor nodes' own characteristics or application scenarios. Therefore, sensor nodes need to run location algorithm or other mechanisms to obtain their own location information. The existing localization algorithms for wireless sensor networks generally have large positioning errors, high complexity and large communication consumption, so they are not suitable for one or more of the problems such as mobile nodes. With the development and wide application of wireless sensor networks (WSNs), the practical node positioning technology for mobile sensor networks (MSNs) is of great theoretical significance and application value. The main work of this paper is as follows: firstly, the background and significance of the research are analyzed and summarized, and the existing location and ranging techniques are summarized. Location principle and advantages and disadvantages of existing location algorithms. Secondly, a matrix-filled distributed localization algorithm (MALL (Matrix-completion Localization) is proposed in this paper. Mall uses a series of constraints, such as distance constraints between nodes, and the coordinates of nodes are of low rank. Time stability and so on, to solve the objective function optimization of the distributed location algorithm, to ensure the algorithm high positioning accuracy and easy to expand the advantages of the algorithm. Because the MALL algorithm only involves convex optimization and non-convex optimization with low complexity, the computational complexity of the algorithm is low. Mall algorithm only uses one-hop common neighbor node information and two-hop anchor neighbor information to complete the positioning process, which has a low location communication consumption. In this paper, the computational complexity of MALL algorithm is analyzed theoretically. Finally, the positioning accuracy, running time and communication consumption performance of the MALL algorithm are compared with other existing algorithms through simulation experiments. Experimental results show that the MALL algorithm is superior to the existing algorithms.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP212.9;TN929.5

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