【摘要】：無線傳感器網(wǎng)絡(luò)(Wireless Sensor Networks,WSN)是一種集數(shù)據(jù)收集、融合、處理、傳輸?shù)裙δ苡谝惑w的網(wǎng)絡(luò)系統(tǒng)。作為物聯(lián)網(wǎng)的基礎(chǔ)和重要組成部分,他觸及到了軟硬件技術(shù)、計(jì)算機(jī)網(wǎng)絡(luò)及通信技術(shù)等多門學(xué)科領(lǐng)域。在軍事、醫(yī)療、環(huán)境監(jiān)測(cè)、森林火災(zāi)、空間探測(cè)等無線傳感器的網(wǎng)絡(luò)應(yīng)用中,不僅需要采集數(shù)據(jù),往往還需要精確確定數(shù)據(jù)的位置信息。因此,節(jié)點(diǎn)定位技術(shù)在無線傳感器中占據(jù)著十分重要、不可或缺的地位。在實(shí)際的環(huán)境中,常常會(huì)遇到不規(guī)則的網(wǎng)絡(luò)拓?fù)洹?fù)雜的傳播環(huán)境、不均勻的節(jié)點(diǎn)部署等問題,這對(duì)定位算法的性能提出了更高的要求。本文對(duì)已有定位算法進(jìn)行了研究分析,甄別已有算法的不足,對(duì)研究的凸規(guī)劃定位算法做了詳細(xì)的分析,并提出了改進(jìn)算法。本文的主要工作如下:(1)分析了目前國(guó)內(nèi)外凸規(guī)劃定位算法的研究現(xiàn)狀,指出了凸規(guī)劃定位算法中研究的不足。針對(duì)經(jīng)典的RSSI-Convex算法,分析了該算法的基本原理、算法過程、以及存在的問題。(2)在對(duì)RSSI-Convex算法的分析中發(fā)現(xiàn)其對(duì)RSSI的條件利用不夠充分,經(jīng)過論證后,提出了基于RSSI所成圓的改進(jìn)算法。該算法對(duì)原始算法的改進(jìn)如下:針對(duì)未知節(jié)點(diǎn)通信半徑內(nèi)僅有一個(gè)信標(biāo)節(jié)點(diǎn)的情況,不在一味地用信標(biāo)節(jié)點(diǎn)坐標(biāo)代替未知節(jié)點(diǎn)坐標(biāo)。改進(jìn)算法利用了物理中轉(zhuǎn)變參考系的思想,達(dá)到了縮減未知節(jié)點(diǎn)未知區(qū)域的目的;針對(duì)未知節(jié)點(diǎn)通信半徑內(nèi)有一個(gè)以上信標(biāo)節(jié)點(diǎn)的情況,利用RSSI所成的圓來進(jìn)一步縮小由RSSI-Convex所確定的未知節(jié)點(diǎn)的未知區(qū)域,達(dá)到了提高定位精度的目的。實(shí)驗(yàn)結(jié)果表明,在對(duì)RSSI充分利用的條件下就可以提高節(jié)點(diǎn)的定位精度。(3)在RSSI-Convex凸規(guī)劃的算法基礎(chǔ)上,結(jié)合查閱的大量文獻(xiàn),提出了改進(jìn)算法。算法通過引入變角的概念,對(duì)RSSI-Convex算法進(jìn)行了大膽的改進(jìn):用扇形取代圓,用變角來進(jìn)一步縮小未知節(jié)點(diǎn)的未知區(qū)域,達(dá)到提高定位精度的目的;通過概率均分的思想將未知節(jié)點(diǎn)合理的限定在角平分線上,使得未知節(jié)點(diǎn)的求解過程進(jìn)一步簡(jiǎn)化。實(shí)驗(yàn)結(jié)果表明,改進(jìn)算法比原算法具有更高的定位精度,并可以較好的改善所存在的問題。對(duì)比兩個(gè)改進(jìn)算法可以看出,基于動(dòng)態(tài)角度劃分的改進(jìn)算法,其算法曲線較為平緩,可以滿足信標(biāo)節(jié)點(diǎn)密度低而對(duì)精度要求高的領(lǐng)域,如軍事、醫(yī)療等。而基于接收信號(hào)強(qiáng)度的改進(jìn)算法可以在不增加成本的前提下,提供更高的節(jié)點(diǎn)精度,使得在環(huán)境監(jiān)測(cè)、森林火災(zāi)等領(lǐng)域得到的信息來源的準(zhǔn)確性更高。
[Abstract]:Wireless sensor network (Wireless Sensor Networks,WSN) is a data collection, fusion, processing, transmission and other functions in one network system. As the foundation and important part of the Internet of things, he touched on many subject fields such as hardware and software technology, computer network and communication technology. In the application of wireless sensors, such as military, medical, environmental monitoring, forest fire, space detection and other wireless sensor applications, it is necessary not only to collect data, but also to accurately determine the location information of the data. Therefore, node positioning technology plays a very important and indispensable role in wireless sensors. In the actual environment, irregular network topology, complex propagation environment, uneven node deployment and other problems are often encountered, which put forward higher requirements for the performance of the localization algorithm. In this paper, the existing localization algorithms are studied and analyzed, the shortcomings of the existing algorithms are identified, and the convex programming localization algorithm is analyzed in detail, and an improved algorithm is proposed. The main work of this paper is as follows: (1) the present research status of convex programming localization algorithm at home and abroad is analyzed, and the deficiency of the research on convex programming localization algorithm is pointed out. In view of the classical RSSI-Convex algorithm, the basic principle, algorithm process and existing problems of the algorithm are analyzed. (2) in the analysis of the RSSI-Convex algorithm, it is found that the condition of RSSI is not sufficiently utilized. An improved algorithm for circle formation based on RSSI is proposed. The improvement of the original algorithm is as follows: for the case that there is only one beacon node in the communication radius of the unknown node, the beacon node coordinates are not always used to replace the unknown node coordinates. The improved algorithm makes use of the idea of changing reference system in physics and achieves the purpose of reducing the unknown region of unknown nodes. Aiming at the case that there is more than one beacon node in the communication radius of the unknown node, the unknown area of the unknown node determined by the RSSI-Convex is further reduced by using the circle formed by the RSSI, and the accuracy of the location is improved. The experimental results show that the localization accuracy of nodes can be improved by fully utilizing RSSI. (3) based on the algorithm of RSSI-Convex convex programming, an improved algorithm is proposed based on a large number of references. By introducing the concept of variable angle, the RSSI-Convex algorithm is improved boldly: the sector is used to replace the circle, and the variable angle is used to further reduce the unknown region of the unknown node so as to improve the positioning accuracy; The unknown node is reasonably limited to the angular bisection line by the idea of equal probability, which further simplifies the solving process of the unknown node. The experimental results show that the improved algorithm has higher positioning accuracy than the original algorithm and can improve the existing problems. Compared with the two improved algorithms, it can be seen that the improved algorithm based on dynamic angle partition has a smooth curve, which can meet the requirements of low density of beacon nodes and high precision, such as military and medical treatment. The improved algorithm based on the received signal strength can provide higher node accuracy without increasing the cost, which makes the accuracy of information sources in environmental monitoring, forest fire and other fields more accurate.
【學(xué)位授予單位】：廣西師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP212.9;TN929.5

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