本文關(guān)鍵詞：WSN中移動(dòng)節(jié)點(diǎn)定位及其在智慧校園中的應(yīng)用研究　出處：《河北師范大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 無線傳感器網(wǎng)絡(luò) 移動(dòng)節(jié)點(diǎn)定位算法 顏色定位 信號分解定位 應(yīng)用 智慧校園

【摘要】：移動(dòng)節(jié)點(diǎn)定位是無線傳感器網(wǎng)絡(luò)(WSN)的關(guān)鍵技術(shù)之一,本文通過對已有移動(dòng)節(jié)點(diǎn)定位算法的總結(jié)和分類,分別從定位算法兩大分類體系——基于距離和基于非距離兩方面提出了新的移動(dòng)節(jié)點(diǎn)定位算法。最后,對移動(dòng)節(jié)點(diǎn)定位在智慧校園中的建設(shè)進(jìn)行了理論闡述。提出的定位算法其中之一為顏色定位算法的改進(jìn)算法,該算法利用收集的信號,在與移動(dòng)節(jié)點(diǎn)能直接通信的信標(biāo)節(jié)點(diǎn)的信號交疊區(qū)域內(nèi)局部采樣;引入距離比例因子,對平均跳距權(quán)值化,優(yōu)化了CDL中跳距的計(jì)算公式;借助RGB差值序列對樣本點(diǎn)濾波并將差值序列絕對值作為加權(quán)標(biāo)準(zhǔn)計(jì)算移動(dòng)節(jié)點(diǎn)的坐標(biāo)。仿真結(jié)果表明與Efficient Color-theory based Dynamic Localization(E-CDL)、Monte Carlo Localization(MCL)等經(jīng)典的移動(dòng)節(jié)點(diǎn)定位算法比較,新算法定位誤差減少了33%以上,具有較好的定位效果。另一種算法是基于采樣濾波的信號矢量分解移動(dòng)定位算法。該算法是以接收信號強(qiáng)度(Received Signal Strength,簡稱RSS)的測距技術(shù)為基礎(chǔ),借助無線傳感器網(wǎng)絡(luò)中MCL類粒子濾波定位算法的采樣、過濾方法,并融入物理中力的分解和合成的思想。該算法通過建立直角坐標(biāo)系,分解合成移動(dòng)節(jié)點(diǎn)、樣本點(diǎn)與信標(biāo)節(jié)點(diǎn)間的信號矢量,利用誤差圓環(huán)采樣,比較移動(dòng)節(jié)點(diǎn)與樣本點(diǎn)的信號合矢量進(jìn)行濾波,將信號合矢量模差絕對值最小的樣本點(diǎn)坐標(biāo)的均值作為移動(dòng)節(jié)點(diǎn)的坐標(biāo)。仿真結(jié)果表明,在同樣的實(shí)驗(yàn)條件下,該算法的定位精度明顯高于相比較的其它算法,且該算法不需要添加任何硬件設(shè)備。WSN中的移動(dòng)節(jié)點(diǎn)定位應(yīng)用范圍廣泛,有軍事、醫(yī)療、家庭、教育等,其在教育上的應(yīng)用還屬于新型領(lǐng)域。本文主要論述了移動(dòng)節(jié)點(diǎn)定位在教育中的重要應(yīng)用——智慧校園的建設(shè)。簡要介紹了智慧校園的概念和核心特征,詳細(xì)的陳述了移動(dòng)節(jié)點(diǎn)定位在智慧校園中的作用,重點(diǎn)介紹了智慧校園的兩大應(yīng)用實(shí)例——校園生活和智慧教室。兩種移動(dòng)節(jié)點(diǎn)定位算法為智慧校園中移動(dòng)定位的應(yīng)用奠定了開發(fā)基礎(chǔ),移動(dòng)節(jié)點(diǎn)定位在智慧校園中應(yīng)用的理論陳述為其在智慧校園中的實(shí)踐奠定了理論基礎(chǔ)和科學(xué)指導(dǎo).
[Abstract]:Mobile node location is one of the key technologies in wireless sensor networks (WSNs). This paper summarizes and classifies the existing mobile node localization algorithms. A new location algorithm for mobile nodes is proposed from two major classification systems, distance based and non-distance based. Finally, a new location algorithm for mobile nodes is proposed. In this paper, the construction of mobile node location in intelligent campus is described theoretically. One of the proposed localization algorithms is the improved color location algorithm, which uses the collected signals. A local sampling is performed in a signal overlap region of a beacon node that can communicate directly with a mobile node; The distance ratio factor is introduced to optimize the calculation formula of the hopping distance in CDL. The RGB difference sequence is used to filter the sample points and the absolute value of the difference sequence is taken as the weighted standard to calculate the coordinates of the mobile node. The simulation results show that the difference sequence is similar to the Efficient Color-theory. Based Dynamic Localization (. E-CDL). Compared with the classical mobile node localization algorithms, such as Monte Carlo Localization, the new algorithm reduces the localization error by more than 33%. Another algorithm is the signal vector decomposition mobile location algorithm based on sampling filter. The algorithm is based on the received signal strength (. Received Signal Strength. Based on the distance measurement technology of rss, sampling and filtering method of MCL particle filtering algorithm in wireless sensor network is used. The algorithm combines the idea of decomposition and synthesis of forces in physics. By establishing a rectangular coordinate system, decomposing and synthesizing the signal vectors between moving nodes, sample points and beacon nodes, the algorithm takes advantage of the error circle sampling. The mean value of the sample point coordinate with the minimum absolute value of the signal combination vector mode difference is taken as the moving node coordinate. The simulation results show that under the same experimental conditions. The location accuracy of the algorithm is obviously higher than that of other algorithms, and the algorithm does not need to add any hardware devices. WSN mobile node location application range, including military, medical, family, education and so on. Its application in education is also a new field. This paper mainly discusses the construction of intelligent campus, which is an important application of mobile node orientation in education, and briefly introduces the concept and core characteristics of intelligent campus. The role of mobile node positioning in smart campus is described in detail. This paper mainly introduces two application examples of intelligent campus-campus life and wisdom classroom. The two mobile node localization algorithms lay a foundation for the application of mobile location in intelligent campus. The theoretical statement of mobile node positioning in the intelligent campus lays a theoretical foundation and scientific guidance for its practice in the intelligent campus.
【學(xué)位授予單位】：河北師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：G40-057

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