本文關(guān)鍵詞：無線傳感器網(wǎng)絡(luò)高性能定位算法研究　出處：《大連理工大學(xué)》2014年博士論文　論文類型：學(xué)位論文

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【摘要】：近些年來,隨著無線技術(shù)的快速發(fā)展和傳感器軟、硬件技術(shù)的成熟,無線傳感器網(wǎng)絡(luò)(WSNs, Wireless Sensor Networks)引起了越來越多的國內(nèi)外研究學(xué)者的關(guān)注。WSNs是一種新型的信息獲取技術(shù),因為其自身所具有的自組織性、動態(tài)性和數(shù)據(jù)為中心等眾多特點,在軍事和民用領(lǐng)域具有廣闊的應(yīng)用前景,例如,在工作人員無法到達的地震災(zāi)區(qū)進行人員搜救、災(zāi)后環(huán)境監(jiān)控和余震檢測。其中,數(shù)據(jù)為中心的特點決定了在其上進行的任何算法設(shè)計、應(yīng)用開發(fā)都需要基于可靠而且高效的節(jié)點自身或者從周圍自然環(huán)境中獲取的各種類型的數(shù)據(jù)。節(jié)點的位置信息作為節(jié)點自身所具有的一種主要數(shù)據(jù),對于很多基于位置的應(yīng)用和服務(wù),是相當重要的。 本文針對高性能數(shù)據(jù)收集問題和利用高性能數(shù)據(jù)收集進行高精度定位問題,使用理論分析和實驗評估相結(jié)合的方法路線,研究了無線傳感器網(wǎng)絡(luò)中數(shù)據(jù)高吞吐量、公平收集問題,提出了比例公平的高性能數(shù)據(jù)收集算法；研究了各種動態(tài)網(wǎng)絡(luò)參數(shù)對定位精度的影響,發(fā)現(xiàn)節(jié)點的定位精度與定位計算時使用的數(shù)據(jù)(基于各種動態(tài)網(wǎng)絡(luò)參數(shù)的不同取值,收集得到的用于定位的數(shù)據(jù)并不相同)之間存在關(guān)系。通過優(yōu)化各種動態(tài)網(wǎng)絡(luò)參數(shù),提高數(shù)據(jù)收集的性能和所收集數(shù)據(jù)的針對性,提出了高精度的定位算法。主要工作概括如下： (1)在無線傳感器網(wǎng)絡(luò)中,網(wǎng)絡(luò)數(shù)據(jù)收集的效率和數(shù)據(jù)收集的公平性問題是兩個重要的研究課題,本文通過分析數(shù)據(jù)收集中“漏斗效應(yīng)”問題以及挖掘?qū)α栴}：數(shù)據(jù)收集效率和數(shù)據(jù)收集公平性之間的相互關(guān)系,提出了一種高性能的比例公平的數(shù)據(jù)收集算法,在提高數(shù)據(jù)收集吞吐量的同時,達到了數(shù)據(jù)比例公平收集的目的。 (2)本文對周期性睡眠調(diào)度網(wǎng)絡(luò)中的定位問題進行了詳細的分析、研究,利用優(yōu)化動態(tài)網(wǎng)絡(luò)參數(shù)的方法,提高定位數(shù)據(jù)收集的針對性和有效性,提出一種高性能的周期性參數(shù)優(yōu)化的動態(tài)定位算法。通過與當前已有的高精度定位算法的比較,發(fā)現(xiàn)利用參數(shù)優(yōu)化確實能提高數(shù)據(jù)收集的針對性和有效性,從而提高定位算法的定位精確度。 (3)本文對基于移動數(shù)據(jù)收集的定位問題進行研究。通過深入分析各種移動參數(shù)對移動數(shù)據(jù)協(xié)助的定位算法的影響,以無線測距為手段,根據(jù)移動節(jié)點的觀察模型,將節(jié)點的定位問題轉(zhuǎn)化為基于某一移動節(jié)點位置坐標數(shù)據(jù)的后驗概率坐標估計問題來處理。根據(jù)與其它幾種經(jīng)典的或最新的定位算法的比較實驗和結(jié)果分析,本文提出的定位算法在多種參數(shù)配置下,在動態(tài)環(huán)境中,表現(xiàn)出了很好的定位性能,是一種高性能的定位算法。 (4)基于移動參數(shù)對定位性能影響的分析,本文提出了一種高性能的基于先驗數(shù)據(jù)收集的室內(nèi)定位算法LuPI,此算法利用了易于獲得的RSS (Received Signal Strength)信息,以各個采樣點之間的RSS差值作為先驗信息,構(gòu)建先驗信息數(shù)據(jù)庫,然后利用RSS差值數(shù)據(jù)庫對移動節(jié)點進行定位,獲得移動節(jié)點的相對位置坐標。本文利用移動智能設(shè)備和WiFi路由器實現(xiàn)了LuPI算法,搭建了原型系統(tǒng),進行了真實環(huán)境的實驗,通過與最新的LiFS算法的比較,LuPI確實提高了動態(tài)環(huán)境中移動節(jié)點的定位精度,并且能在環(huán)境復(fù)雜、多徑干擾強烈的室內(nèi)進行高精度的定位。
[Abstract]:In recent years, with the rapid development of wireless technology and soft sensor, hardware technology, wireless sensor network (WSNs Wireless, Sensor Networks) attracted more and more researchers focus on.WSNs is a new technology of information acquisition, because of its self-organization, dynamic and data the center and many other features, has broad application prospect, in military and civil fields such as earthquake can not arrive in the staff of the search and rescue personnel, environmental monitoring and detection of aftershocks after the earthquake. Among them, any number of algorithm design according to the characteristics of as the center of the decision on the need, application development based on node reliability but efficient or acquired from its surrounding natural environment in various types of data. One of the main data of the location information of the nodes as the node itself has, for it Location based applications and services are very important.
For the high performance data collection and collection of high precision positioning using high performance data line method using theoretical analysis and experimental evaluation of combining the research data in wireless sensor networks with high throughput, fairness is proposed for high performance data collection, proportional fair collection algorithm was studied; various parameters of dynamic network the positioning accuracy, using to calculate the positioning accuracy and the positioning of the nodes when the data (different values of various parameters, dynamic network based on the collected data for positioning is not the same). The relationship between the various parameters through optimizing the dynamic network, improve the performance of data collection and the data collected of the proposed localization algorithm high precision. The main works are summarized as follows:
(1) in wireless sensor networks, the fairness of network data collection efficiency and data collection are two important research topic, this paper through the analysis of the data collected in the "funnel effect" and explore the opposite problem: the relationship between data collection efficiency and fairness of data collection, presents a high performance the fair share of the data collection method in improving data collection throughput at the same time, to achieve the data proportional fair collection purposes.
(2) the positioning problem of periodic sleep scheduling in the network are analyzed in detail. The study, using the method of dynamic optimization of network parameters, improve the pertinence and effectiveness of positioning data collection, this paper proposed a dynamic positioning periodic parameter optimization of high performance algorithm. By comparing the algorithm with high precision positioning the current findings, pertinence and effectiveness of using parameter optimization can improve the data collection, so as to improve the positioning accuracy of the positioning algorithm.
(3) this paper studies the location problem of mobile data collection based on impact localization algorithm for mobile data to assist through in-depth analysis of various parameters to the mobile, wireless ranging means, according to the observation model of the mobile node, the node localization problem is transformed into a mobile node position coordinate data of the posterior probability estimation of coordinates based on the problem to deal with. According to the classical and several other or new positioning algorithm comparison experiment and result analysis, the proposed localization algorithm in a variety of configurations, in a dynamic environment, showing good positioning performance, is a localization algorithm with high performance.
(4) analysis of the influence of parameters on the performance of mobile location based on the proposed LuPI indoor positioning algorithm based on a priori data collection of high performance, this algorithm makes use of the easy access to RSS (Received Signal Strength), with each RSS difference between sampling points as a priori information, and then construct a priori information database. The localization of mobile nodes using RSS difference database, relative position coordinates access to mobile nodes. Using smart mobile devices and WiFi routers to realize LuPI algorithm, built a prototype system of real experimental environment, through comparing with the new LiFS algorithm, LuPI can improve the accuracy of dynamic positioning of mobile nodes in the environment, and in the complex environment, strong multipath interference for indoor high accuracy position.

【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN929.5;TP212.9

【參考文獻】

相關(guān)博士學(xué)位論文 前1條

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本文編號：1427672