【摘要】：無(wú)線傳感器網(wǎng)絡(luò)[1-4](Wireless Sensor Network：WSN)由一組微小型功能齊全的MEMS裝置構(gòu)成，這些微型裝置包括傳感器、無(wú)線發(fā)射器和接收器、電源，它們分布在一個(gè)地理區(qū)域中對(duì)該區(qū)域進(jìn)行實(shí)時(shí)監(jiān)測(cè)[5]。無(wú)線傳感器網(wǎng)絡(luò)本身具有計(jì)算處理能力，網(wǎng)絡(luò)中的各節(jié)點(diǎn)之間可以互相通信以便獲取網(wǎng)絡(luò)中的數(shù)據(jù)，同時(shí)節(jié)點(diǎn)之間還可以自動(dòng)組織網(wǎng)絡(luò)并且協(xié)同進(jìn)行工作。與傳統(tǒng)的單一大型傳感器或有線通信裝置相比，無(wú)線傳感器網(wǎng)絡(luò)內(nèi)部主要靠無(wú)線通信，這使得無(wú)線傳感器網(wǎng)絡(luò)在精度、靈活性、經(jīng)濟(jì)性、可靠性等諸多方面都有明顯的優(yōu)越性[6]。無(wú)線傳感器網(wǎng)絡(luò)邊緣檢測(cè)[7]對(duì)于實(shí)現(xiàn)無(wú)線傳感器網(wǎng)絡(luò)優(yōu)質(zhì)應(yīng)用至關(guān)重要，是網(wǎng)絡(luò)實(shí)現(xiàn)高效應(yīng)用的支撐技術(shù)之一。在無(wú)線傳感器網(wǎng)絡(luò)應(yīng)用中，邊緣檢測(cè)在目標(biāo)跟蹤、覆蓋檢測(cè)和路由構(gòu)造等方面都發(fā)揮著舉足輕重的作用。 論文研究了無(wú)線傳感器網(wǎng)絡(luò)邊緣節(jié)點(diǎn)的識(shí)別問(wèn)題，在一個(gè)無(wú)線傳感器網(wǎng)絡(luò)中，鄰居節(jié)點(diǎn)之間可以直接建立連接，并且可以估計(jì)與附近節(jié)點(diǎn)的距離（并不是實(shí)際的距離）。論文的目的是在不依靠網(wǎng)絡(luò)中節(jié)點(diǎn)的坐標(biāo)信息的情況下，僅僅通過(guò)節(jié)點(diǎn)之間的連接關(guān)系和鄰居節(jié)點(diǎn)之間的距離來(lái)尋找邊緣節(jié)點(diǎn)。 論文首先提出一種尋找網(wǎng)絡(luò)邊緣節(jié)點(diǎn)的算法并分別應(yīng)用于分布式與集中式場(chǎng)景中，網(wǎng)絡(luò)中的節(jié)點(diǎn)分布在一個(gè)有邊界、無(wú)坐標(biāo)、低密度、隨機(jī)部署的無(wú)線傳感器網(wǎng)絡(luò)中，此算法的關(guān)鍵思想是在集中式場(chǎng)景中提出的，并且擴(kuò)展到了分布式場(chǎng)景中，通過(guò)仿真實(shí)驗(yàn)證明分布式實(shí)現(xiàn)相對(duì)于真實(shí)的無(wú)線傳感器網(wǎng)絡(luò)更加有效，而且分布式算法相對(duì)于集中式算法能夠檢測(cè)出更高質(zhì)量的網(wǎng)絡(luò)邊界，尤其是在稀疏網(wǎng)絡(luò)中由于節(jié)點(diǎn)之間的稀疏連接而不能收集到所有節(jié)點(diǎn)的位置信息，分布式算法具有很高的優(yōu)勢(shì)。之后論文在幾何知識(shí)與拓?fù)渲R(shí)相結(jié)合的前提下提出了一種無(wú)線傳感器網(wǎng)絡(luò)邊緣檢測(cè)新的分布式算法，基于有向樹(shù)擴(kuò)展的多邊形包圍檢測(cè)算法，算法對(duì)于網(wǎng)絡(luò)節(jié)點(diǎn)的密度沒(méi)有限制要求，仿真結(jié)果表明該算法有效避免了錯(cuò)檢、漏檢情況的發(fā)生，判別方法簡(jiǎn)單準(zhǔn)確，，有效提高了無(wú)線傳感器網(wǎng)絡(luò)邊緣檢測(cè)的效率和精度。 論文研究無(wú)線傳感器網(wǎng)絡(luò)邊緣檢測(cè)技術(shù)，旨在對(duì)現(xiàn)有算法進(jìn)行詳細(xì)分析并設(shè)計(jì)相應(yīng)新的優(yōu)化算法，不需要任何節(jié)點(diǎn)的位置信息，僅依靠節(jié)點(diǎn)之間的連通性質(zhì)來(lái)完成所需任務(wù)，并且在邊緣檢測(cè)實(shí)現(xiàn)的基礎(chǔ)上本文對(duì)無(wú)線傳感器網(wǎng)絡(luò)的應(yīng)用方面進(jìn)行了概括總結(jié)，并詳細(xì)介紹了無(wú)線傳感器網(wǎng)絡(luò)中目標(biāo)跟蹤技術(shù)的相關(guān)算法及應(yīng)用。
[Abstract]:The wireless sensor network [1-4] (Wireless Sensor Network:WSN) is made up of a set of small and fully functional MEMS devices, which include sensors, wireless transmitters and receivers, and power sources. They are distributed in a geographic area to monitor the region in real time [5]. The wireless sensor network itself has the computing power, The nodes in the network can communicate with each other so that the data in the network can be obtained. At the same time, the nodes can also automatically organize the network and work together. Compared with the traditional single large sensor or cable communication device, the wireless sensor network is mainly based on wireless communication, which makes the wireless sensor network with precision and flexibility. There are obvious advantages in many aspects, such as activity, economy, reliability and so on. [6]. wireless sensor network edge detection [7] is very important for the realization of high quality application of wireless sensor networks. It is one of the support technologies for efficient application of network. In wireless sensor network applications, edge detection is tracking, covering detection and routing. All of them play a decisive role.
The paper studies the recognition of the edge nodes of wireless sensor networks. In a wireless sensor network, the neighbor nodes can directly establish a connection and estimate the distance from the nearby nodes (not the actual distance). The purpose of the paper is to only pass the node without relying on the coordinates of the nodes in the network. The connection between points and the distance between neighbor nodes to find edge nodes.
In this paper, an algorithm for finding network edge nodes is proposed and applied to distributed and centralized scenarios. The nodes in the network are distributed in a wireless sensor network with boundary, no coordinate, low density and random deployment. The key idea of this algorithm is put forward in the centralized scene and extends to the distributed field. The simulation experiments show that the distributed implementation is more effective than the real wireless sensor network, and the distributed algorithm can detect the higher quality of the network boundary relative to the centralized algorithm, especially in the sparse network, which can not collect the location information of all nodes because of the sparse connection between nodes. Based on the combination of geometric knowledge and topology knowledge, a new distributed algorithm for edge detection in wireless sensor networks is proposed, based on a polygon encircling detection algorithm based on directed tree expansion, and the algorithm has no restriction on the density of network nodes. The simulation results show that the algorithm has the advantages of the algorithm. This method avoids the wrong detection and missed detection, and the method is simple and accurate. It effectively improves the efficiency and accuracy of edge detection in wireless sensor networks.
This paper studies the edge detection technology of wireless sensor network, which aims to analyze the existing algorithms in detail and design a new optimization algorithm. It does not need the location information of any node, only relies on the connectivity between nodes to complete the required tasks, and on the basis of the implementation of the edge detection, the application of this paper to the wireless sensor network is made. In this paper, we summarize and introduce the related algorithms and applications of target tracking technology in wireless sensor networks.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：TP212.9;TN929.5

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