本文選題：節(jié)點(diǎn)定位 + 凹凸節(jié)點(diǎn)�。� 參考：《電子科技大學(xué)》2014年碩士論文

【摘要】：隨著近年來(lái)無(wú)線傳感器網(wǎng)絡(luò)在軍事及民用的應(yīng)用越來(lái)越廣泛,人們?cè)絹?lái)越關(guān)注無(wú)線傳感器網(wǎng)絡(luò)在各方面的研究。其中節(jié)點(diǎn)定位技術(shù)是傳感器網(wǎng)絡(luò)應(yīng)用的關(guān)鍵支撐技術(shù)之一,針對(duì)節(jié)點(diǎn)定位技術(shù)的研究面也越來(lái)越廣,從二維平面定位到三維表面定位,從固定錨節(jié)點(diǎn)到移動(dòng)錨節(jié)點(diǎn)的定位研究。其中,三維表面定位最接近無(wú)線傳感器網(wǎng)絡(luò)的實(shí)際應(yīng)用,然而國(guó)內(nèi)外對(duì)其的研究相對(duì)比較少,并且缺乏考慮到實(shí)際的復(fù)雜地形如凹凸表面對(duì)其定位誤差和節(jié)點(diǎn)定位率的影響。本文在二維定位算法的基礎(chǔ)上提出了三維表面定位的復(fù)雜地形對(duì)節(jié)點(diǎn)定位的影響,主要有凹凸地形對(duì)節(jié)點(diǎn)定位精度和節(jié)點(diǎn)定位率的影響,以及錨節(jié)點(diǎn)的分布不均勻?qū)?jié)點(diǎn)定位和節(jié)點(diǎn)能耗的影響。針對(duì)這些問(wèn)題,本文首先提出了三維表面凹凸分解的分層定位算法,該算法首先將網(wǎng)絡(luò)基于高度分層,從而減小在應(yīng)用場(chǎng)景比較大時(shí)減小節(jié)點(diǎn)定位誤差的迭代,然后在每層內(nèi)根據(jù)凹凸節(jié)點(diǎn)劃分子網(wǎng),將凹凸度相近并相鄰的節(jié)點(diǎn)劃分到一個(gè)子網(wǎng)內(nèi),在每個(gè)子網(wǎng)內(nèi)定位出節(jié)點(diǎn)的坐標(biāo),最后合并。該算法在定位誤差和定位率方面都比其余的算法有所改進(jìn),不過(guò)計(jì)算復(fù)雜度和能耗方面提高很小。所以本文又提出了基于關(guān)鍵節(jié)點(diǎn)的移動(dòng)路徑規(guī)劃定位算法,該算法是在三維表面凹凸分解定位算法的基礎(chǔ)上進(jìn)行了改進(jìn),主要包含以下幾方面:(1)該算法將網(wǎng)絡(luò)中的節(jié)點(diǎn)映射到一個(gè)平面上,通過(guò)分辨是否有部分區(qū)域重合來(lái)判斷網(wǎng)絡(luò)是否需要分割,如果有重合將網(wǎng)絡(luò)劃分成多個(gè)子網(wǎng),從而提高節(jié)點(diǎn)的定位率。(2)該算法根據(jù)凹凸節(jié)點(diǎn)的定義在子網(wǎng)內(nèi)找出所有凹凸節(jié)點(diǎn)定義為關(guān)鍵節(jié)點(diǎn),并使用移動(dòng)錨節(jié)點(diǎn)定位出關(guān)鍵節(jié)點(diǎn)并作為已知節(jié)點(diǎn),然后利用這些已知節(jié)點(diǎn)定位其余的未知節(jié)點(diǎn),避免凹凸節(jié)點(diǎn)對(duì)定位誤差的影響。(3)算法采用移動(dòng)錨節(jié)點(diǎn)替換固定錨節(jié)點(diǎn),可以適應(yīng)各種復(fù)雜的地形,避免了錨節(jié)點(diǎn)密度不夠或者分布不均勻?qū)е碌墓?jié)點(diǎn)不可被定位和定位誤差迭代較大的情況。本文在最后通過(guò)實(shí)驗(yàn)證明兩個(gè)算法在定位誤差,定位率和節(jié)點(diǎn)能耗方面都有較大的改進(jìn),并且后者比前者在各方面都有明顯的提升。
[Abstract]:With the application of wireless sensor networks in military and civilian applications, more and more attention has been paid to the research of wireless sensor networks. The node location technology is one of the key supporting technologies in sensor network application. The research area of node location technology is more and more extensive, from two-dimensional plane positioning to three-dimensional surface positioning, from fixed anchor node to mobile anchor node location research. Among them, 3D surface localization is most close to the practical application of wireless sensor networks, but the research on it is relatively few at home and abroad, and lack of consideration of the actual complex terrain such as concave and convex surface on its positioning error and node localization rate. In this paper, based on the two-dimensional localization algorithm, the influence of the complex terrain of 3D surface location on node location is proposed, including the effect of concave and convex terrain on node location accuracy and node localization rate. And the influence of uneven distribution of anchor nodes on node location and node energy consumption. To solve these problems, this paper first proposes a layered localization algorithm based on three dimensional surface concavity and convex decomposition. Firstly, the network is based on high stratification, which reduces the iteration of node localization error when the application scene is large. Then the subnets are divided into subnets according to the concave and convex nodes in each layer, and the adjacent nodes with similar concave and convex degrees are divided into a subnet, and the coordinates of the nodes are located in each subnet, and finally the nodes are merged. The algorithm improves the localization error and localization rate compared with the other algorithms, but the computational complexity and energy consumption are little improved. Therefore, this paper proposes a mobile path planning and location algorithm based on key nodes, which is improved on the basis of 3D surface concavity and convex decomposition localization algorithm. It mainly includes the following aspects: (1) the algorithm maps the nodes in the network to a plane, and determines whether the network needs to be divided by distinguishing whether there is a partial area overlap. If there is overlap, the network is divided into several subnets. In order to improve the localization rate of nodes. (2) according to the definition of concave and convex nodes, the algorithm finds out that all concave and convex nodes are defined as key nodes in the subnet, and uses mobile anchor nodes to locate the key nodes and take them as known nodes. Then using these known nodes to locate the remaining unknown nodes to avoid the impact of concave and convex nodes on the positioning error. (3) the algorithm uses mobile anchor nodes to replace fixed anchor nodes, which can adapt to various complex terrain. It avoids the problem that the node can not be located and the error iteration is large due to the lack of anchor node density or the uneven distribution. At the end of this paper, it is proved by experiments that the two algorithms have great improvement in location error, localization rate and node energy consumption, and the latter has obvious improvement over the former in all aspects.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN929.5;TP212.9

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 李娟;王珂;盧長(zhǎng)剛;;Bounding Cube:一種無(wú)線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)三維定位算法[J];中國(guó)海洋大學(xué)學(xué)報(bào)(自然科學(xué)版);2009年06期

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本文編號(hào)：2056835