【摘要】：位置信息對(duì)傳感器網(wǎng)絡(luò)的檢測(cè)活動(dòng)至關(guān)重要。在實(shí)際應(yīng)用中,傳感器節(jié)點(diǎn)往往分布在三維區(qū)域中,如山區(qū)、森林、海洋等,且節(jié)點(diǎn)往往具有不可忽略的移動(dòng)性。因此,這就要求定位算法能夠?qū)崿F(xiàn)移動(dòng)節(jié)點(diǎn)在三維空間中的定位。 本文針對(duì)移動(dòng)節(jié)點(diǎn)在三維空間中的特性,設(shè)計(jì)了一種基于蒙特卡洛的無線傳感器網(wǎng)絡(luò)移動(dòng)節(jié)點(diǎn)非測(cè)距分布式錨箱三維定位算法。算法利用外接正方體來表示節(jié)點(diǎn)的通信范圍和移動(dòng)范圍,根據(jù)未知節(jié)點(diǎn)每時(shí)隙最大移動(dòng)范圍和錨節(jié)點(diǎn)通信范圍形成采樣區(qū)域,依據(jù)錨箱體積確定采樣數(shù)量,隨機(jī)采集的樣點(diǎn)取均值作為未知節(jié)點(diǎn)的估計(jì)位置。仿真表明,通過不同采樣數(shù)量、時(shí)隙、錨節(jié)點(diǎn)比例、節(jié)點(diǎn)數(shù)量、節(jié)點(diǎn)移動(dòng)速度、通信半徑以及通信范圍的不規(guī)則度對(duì)定位誤差影響的分析,在一定節(jié)點(diǎn)移動(dòng)速度、較小的通信半徑和錨節(jié)點(diǎn)比例下算法取得了較理想的定位精度,且優(yōu)于質(zhì)心算法,有效實(shí)現(xiàn)了三維環(huán)境中移動(dòng)節(jié)點(diǎn)的定位。 通過引進(jìn)鄰居節(jié)點(diǎn)有效樣點(diǎn)投票機(jī)制,本文還研究了一種加權(quán)蒙特卡洛移動(dòng)節(jié)點(diǎn)的三維定位算法。算法充分利用鄰居節(jié)點(diǎn)的位置信息,給篩選之后的有效樣點(diǎn)進(jìn)行投票,給更接近真實(shí)位置的樣本分配更大的權(quán)值,通過權(quán)值來反映鄰居節(jié)點(diǎn)對(duì)估計(jì)位置的影響提高定位精度。仿真顯示,通過不同時(shí)隙、錨節(jié)點(diǎn)比例、節(jié)點(diǎn)數(shù)量、節(jié)點(diǎn)移動(dòng)速度和通信半徑對(duì)定位誤差影響的分析,算法定位精度高于錨箱三維算法和質(zhì)心算法。該算法具有較高的魯棒性、可擴(kuò)展性和定位精度,且是一種無需測(cè)距的分布式三維定位算法,可在移動(dòng)無線傳感器網(wǎng)絡(luò)中大規(guī)模的實(shí)際應(yīng)用。
[Abstract]:Location information is very important for sensor network detection. In practical applications, sensor nodes are often distributed in three-dimensional regions, such as mountains, forests, oceans and so on, and the nodes often have the mobility that can not be ignored. Therefore, the localization algorithm is required to realize the location of mobile nodes in three-dimensional space. In view of the characteristics of mobile nodes in 3D space, this paper designs a distributed 3D location algorithm for mobile nodes in wireless sensor networks based on Monte Carlo. The algorithm uses the external cube to express the communication range and moving range of the node, forms the sampling area according to the maximum moving range of each slot of unknown node and the communication range of anchor node, and determines the sampling number according to the volume of anchor box. The random sampling points take the mean value as the estimated position of unknown nodes. The simulation results show that the influence of sampling number, time slot, anchor node ratio, node number, node moving speed, communication radius and the irregularity of communication range on the location error is analyzed. With small communication radius and anchor node ratio, the algorithm achieves ideal positioning accuracy and is superior to centroid algorithm, which effectively realizes the location of mobile nodes in three-dimensional environment. By introducing the effective sampling voting mechanism of neighbor nodes, this paper also studies a weighted Monte Carlo mobile node 3D location algorithm. The algorithm makes full use of the location information of neighbor nodes to vote the valid samples after screening and assigns larger weights to the samples closer to the real location. The weight value is used to reflect the influence of neighbor nodes on the estimated location to improve the location accuracy. The simulation results show that the localization accuracy of the algorithm is higher than that of the anchor box 3D algorithm and centroid algorithm through the analysis of the effects of different time slots, the proportion of anchor nodes, the number of nodes, the speed of node movement and the communication radius on the positioning error. The algorithm is robust, scalable and accurate. It is a distributed 3D localization algorithm without ranging. It can be used in mobile wireless sensor networks on a large scale.
【學(xué)位授予單位】：中南大學(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

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 劉云浩;楊錚;王小平;簡(jiǎn)麗榮;;Location,Localization,and Localizability[J];Journal of Computer Science & Technology;2010年02期

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本文編號(hào)：2271820