發(fā)布時(shí)間：2018-01-11 18:02

  本文關(guān)鍵詞：錨節(jié)點(diǎn)位置不確定情況下的魯棒室內(nèi)定位方法研究　出處：《哈爾濱工業(yè)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： 室內(nèi)定位 錨節(jié)點(diǎn)不確定 非貝葉斯估計(jì) 貝葉斯估計(jì) 置信度傳遞

【摘要】：室內(nèi)定位的需求在未來(lái)將會(huì)不斷增加,而對(duì)于定位精度的提高一直是研究的重要目標(biāo)。影響定位精度的因素有很多,不管是考慮環(huán)境因素的非視距傳播、多徑傳播,還是由噪聲引起的測(cè)量距離誤差,都會(huì)導(dǎo)致定位出現(xiàn)誤差。針對(duì)室內(nèi)定位,在考慮錨節(jié)點(diǎn)位置的不確定所導(dǎo)致的定位誤差方面的問(wèn)題,同樣需要得到足夠的重視。本文在常見(jiàn)的定位模型上,考慮了錨節(jié)點(diǎn)位置不確定問(wèn)題,重新建立了本文所用到的定位模型,并對(duì)其數(shù)學(xué)建模,以便用于文中的仿真和分析。通常情況下,我們常常在仿真和應(yīng)用中認(rèn)為得到的錨節(jié)點(diǎn)位置就是其真實(shí)位置,而實(shí)際情況并非如此,在錨節(jié)點(diǎn)位置不確定的模型中,我們需要先獲得錨節(jié)點(diǎn)的位置坐標(biāo),然而通過(guò)眾多方式所獲得的錨節(jié)點(diǎn)位置,會(huì)因?yàn)楦鞣N原因,使得所謂已知的錨節(jié)點(diǎn)位置相對(duì)于真實(shí)位置是帶有誤差的。借鑒測(cè)量距離的誤差對(duì)定位產(chǎn)生影響的分析方式,先從測(cè)量距離的誤差服從高斯分布的分析入手,逐漸向?qū)嶋H的測(cè)量結(jié)果靠攏;以及眾多文獻(xiàn)對(duì)存在定位誤差作了詳細(xì)的研究和分析。我們便借鑒了其中一些能夠適用于分析本文所需要解決的問(wèn)題的方法,可以分為兩大部分:非貝葉斯估計(jì)方法和貝葉斯估計(jì)方法。采用這兩種方法是因?yàn)?非貝葉斯方法中有很多算法可以用于分析錨節(jié)點(diǎn)位置不確定所帶來(lái)的定位誤差,算法常見(jiàn),而且簡(jiǎn)單易行,假定的誤差分布也是常見(jiàn)的高斯形式。如果需要考慮實(shí)際情況所得到的錨節(jié)點(diǎn)誤差,我們便可以從貝葉斯的方法入手,這種方法更加具有一般性,而且以便于后續(xù)的研究。本文一方面通過(guò)非貝葉斯估計(jì)方法,考慮了四種線性的算法,仿真和分析了錨節(jié)點(diǎn)位置不確定對(duì)定位精度的影響,考慮了錨節(jié)點(diǎn)誤差大小以及定位區(qū)域大小,得出了不同算法之間在不同的條件下定位性能的差異性,直觀的反映了錨節(jié)點(diǎn)位置不確定所帶來(lái)的定位誤差大小和利用不同算法的特性來(lái)指導(dǎo)實(shí)際情況的應(yīng)用。解決了錨節(jié)點(diǎn)誤差導(dǎo)致的奇異解問(wèn)題,提高了定位精度和定位性能,保證了定位算法的魯棒性。另一方面通過(guò)貝葉斯估計(jì)方法,引入置信度傳遞的算法,由錨節(jié)點(diǎn)的先驗(yàn)知識(shí)求得定位的邊緣后驗(yàn)概率分布,從參數(shù)形式轉(zhuǎn)向非參數(shù)形式,用基于粒子的信息傳遞和分布的高斯近似,從而能夠解決錨節(jié)點(diǎn)誤差服從實(shí)際分布情況的問(wèn)題,相對(duì)于非貝葉斯方法更加通用,也可應(yīng)用置信度傳遞于錨節(jié)點(diǎn)自我迭代的精度提升和后續(xù)進(jìn)行協(xié)作定位方面的研究。
[Abstract]:The demand for indoor positioning will continue to increase in the future, and the improvement of positioning accuracy has been an important goal of the study. There are many factors that affect the positioning accuracy, whether it is non-line-of-sight propagation considering environmental factors. Multipath propagation, or measurement distance error caused by noise, will lead to positioning errors. For indoor positioning, the positioning error caused by the uncertainty of anchor node location is considered. In this paper, considering the uncertainty of anchor node location, the location model used in this paper is re-established, and its mathematical model is established. In order to be used for simulation and analysis in this paper. In general, we often think that the anchor node position is the real position in simulation and application, but the actual situation is not. In the model of uncertain anchor node position, we need to obtain the anchor node position coordinates first. However, the anchor node position obtained by many ways will be due to a variety of reasons. So that the so-called known anchor node position relative to the real position is with errors. For reference to the measurement distance error impact on the positioning analysis, first from the error of the measurement distance from the Gaussian distribution analysis. Gradually close to the actual measurement results; And many literatures have done a detailed study and analysis of the existence of positioning errors. We have used some of the methods that can be used to analyze the problems that need to be solved in this paper. It can be divided into two parts: the non-Bayesian estimation method and the Bayesian estimation method. There are many non-Bayesian methods can be used to analyze the location error caused by the uncertainty of anchor node location. The algorithm is common and easy to implement. The assumed error distribution is also a common Gaussian form. If we need to consider the actual situation of the anchor node error, we can start from the Bayesian method, this method is more general. On the one hand, four linear algorithms are considered through the non-Bayesian estimation method, and the influence of the location uncertainty of anchor nodes on the positioning accuracy is simulated and analyzed. Considering the error of anchor node and the size of location area, the difference of localization performance between different algorithms is obtained under different conditions. It intuitively reflects the location error caused by the uncertainty of anchor node location and uses the characteristics of different algorithms to guide the application of the actual situation and solves the singular solution problem caused by anchor node error. The location accuracy and performance are improved, and the robustness of the localization algorithm is guaranteed. On the other hand, the confidence transfer algorithm is introduced through Bayesian estimation. The edge posteriori probability distribution is obtained from the priori knowledge of anchor nodes, and the probability distribution is changed from parametric form to non-parametric form. The Gaussian approximation based on particle information transmission and distribution is used. Therefore, it can solve the problem of the actual distribution of the anchor node error, which is more general than the non-Bayesian method. It can also be used to improve the accuracy of self-iteration of anchor nodes and to carry out the research of cooperative localization.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TN92

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 鄧中亮;余彥培;袁協(xié);萬(wàn)能;楊磊;;室內(nèi)定位現(xiàn)狀與發(fā)展趨勢(shì)研究(英文)[J];中國(guó)通信;2013年03期

2 申鉉京;李成岳;王碩;千慶姬;;基于最優(yōu)錨節(jié)點(diǎn)的無(wú)線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位算法[J];吉林大學(xué)學(xué)報(bào)(工學(xué)版);2011年S1期

3 郭建全;趙偉;黃松嶺;;農(nóng)田環(huán)境無(wú)線傳感器網(wǎng)絡(luò)無(wú)錨節(jié)點(diǎn)定位算法[J];儀器儀表學(xué)報(bào);2009年08期

4 李洪峻;卜彥龍;薛晗;李迅;馬宏緒;;面向無(wú)線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位的移動(dòng)錨節(jié)點(diǎn)路徑規(guī)劃[J];計(jì)算機(jī)研究與發(fā)展;2009年01期

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本文編號(hào)：1410600