發(fā)布時間：2018-03-07 02:36

  本文選題：無線定位　切入點：無設(shè)備定位　出處：《北京科技大學(xué)》2017年博士論文　論文類型：學(xué)位論文

【摘要】：無設(shè)備定位(Device-Free Localization,DFL)是一種目標(biāo)無需攜帶任何電子設(shè)備的無線定位技術(shù),已被廣泛地應(yīng)用于各個領(lǐng)域,如入侵檢測、緊急救援、老人看護(hù)等。該無線定位技術(shù)通過分析目標(biāo)所帶來的監(jiān)測區(qū)域內(nèi)無線射頻信號的變化得以實現(xiàn)。但由于受環(huán)境時變、非視距、多路徑信號傳播等不確定性因素的影響,實現(xiàn)高精度、抗干擾能力強的DFL仍是亟待解決的、挑戰(zhàn)性的問題。構(gòu)建合理的無線信號傳播模型是提高DFL精度的有效途徑,為此本文對該模型及相應(yīng)的DFL優(yōu)化求解方法進(jìn)行了深入的研究。論文主要工作和研究成果包括以下幾個方面:(1)通過分析影響鏈路信號強度波動的因素,提出聯(lián)合鏈路檢測方法,實現(xiàn)監(jiān)測區(qū)域內(nèi)受影響鏈路的聯(lián)合選取及異常鏈路的剔除。(2)基于鏈路的幾何檢測模型,對DFL進(jìn)行優(yōu)化方法研究。采用鏈路直線檢測模型,提出了 DFL的非線性目標(biāo)函數(shù)優(yōu)化方法,并利用凸優(yōu)化理論進(jìn)行求解;為了進(jìn)一步提高定位精度,采用鏈路橢圓檢測模型,提出了基于凸可行并行投影的DFL方法;通過實驗驗證了所提方法具有較好的定位效果,并優(yōu)于已有定位方法。(3)為解決在復(fù)雜環(huán)境下DFL精度面臨惡化的問題,通過分析目標(biāo)對鏈路信號強度的影響,構(gòu)建了基于高斯過程的無線射頻信號傳播模型,并通過實驗測試該模型的性能。(4)基于高斯過程無線射頻信號傳播模型,結(jié)合聯(lián)合鏈路檢測方法,將DFL問題轉(zhuǎn)化為極大似然概率優(yōu)化問題,并提出了相應(yīng)的改進(jìn)果蠅優(yōu)化求解方法;針對目標(biāo)跟蹤問題,提出了基于高斯過程無線射頻信號傳播模型的粒子濾波方法,結(jié)合目標(biāo)運動模型對粒子進(jìn)行預(yù)測和更新,實現(xiàn)對目標(biāo)的跟蹤;分別在空曠的室外場景、及復(fù)雜的室內(nèi)場景搭建實驗平臺對所提方法進(jìn)行測試,驗證了所提方法的定位與跟蹤效果。
[Abstract]:Device-Free Localization #en0# (DFL) is a wireless location technology with no need to carry any electronic devices. It has been widely used in various fields, such as intrusion detection, emergency rescue. The wireless location technology is realized by analyzing the changes of radio frequency signals in the monitoring area brought about by the target. However, due to the influence of uncertain factors such as environmental time-varying, non-line-of-sight, multipath signal propagation, etc., this wireless location technology is realized by analyzing the changes of radio frequency signals in the monitoring area brought about by the target. It is still an urgent and challenging problem to realize DFL with high precision and strong anti-jamming ability. It is an effective way to improve the accuracy of DFL to build a reasonable wireless signal propagation model. In this paper, the model and the corresponding DFL optimization method are studied in depth. The main work and research results include the following aspects: 1) by analyzing the factors affecting the fluctuation of link signal intensity, a joint link detection method is proposed. To realize the joint selection of the affected links in the monitoring area and the elimination of the abnormal links. (2) based on the geometric detection model of the link, the optimization method of DFL is studied, and the link line detection model is adopted. The nonlinear objective function optimization method of DFL is proposed, and the convex optimization theory is used to solve the problem. In order to further improve the positioning accuracy, a DFL method based on convex feasible parallel projection is proposed by using the link ellipse detection model. The experimental results show that the proposed method has good localization effect, and is superior to the existing localization method. In order to solve the problem of deterioration of DFL precision in complex environment, the effect of target on link signal strength is analyzed. A radio frequency signal propagation model based on Gao Si process is constructed, and the performance of the model is tested experimentally. The DFL problem is transformed into the maximum likelihood probability optimization problem, and the corresponding improved optimization method for fruit fly is proposed, and a particle filter method based on Gao Si process radio frequency signal propagation model is proposed for target tracking. Combined with the target motion model to predict and update the particles to achieve the target tracking, respectively in the open outdoor scene, and complex indoor scene to build an experimental platform to test the proposed method, The localization and tracking effect of the proposed method is verified.
【學(xué)位授予單位】：北京科技大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TP212.9;TN929.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前7條

1 王滿意;丁恩杰;;基于WSNs的無線層析成像定位算法的改進(jìn)[J];傳感器與微系統(tǒng);2015年04期

2 張會新;陳德沅;彭晴晴;史磊;;一種改進(jìn)的TDOA無線傳感器網(wǎng)絡(luò)節(jié)點定位算法[J];傳感技術(shù)學(xué)報;2015年03期

3 劉凱;夏然;柴柯;;結(jié)合菲涅爾理論的免攜帶設(shè)備定位研究[J];傳感技術(shù)學(xué)報;2015年02期

4 何志昆;劉光斌;趙曦晶;王明昊;;高斯過程回歸方法綜述[J];控制與決策;2013年08期

5 史東亞;陸鍵;陸林軍;;基于RFID技術(shù)和FOA-GRNN理論的高速公路道路關(guān)閉交通事件對車輛影響的判斷模型[J];武漢理工大學(xué)學(xué)報;2012年03期

6 張華;宋正勛;石云;李娜;張福威;;基于超寬帶的TOA定位技術(shù)研究[J];吉林大學(xué)學(xué)報(信息科學(xué)版);2008年01期

7 莫以為,蕭德云;進(jìn)化粒子濾波算法及其應(yīng)用[J];控制理論與應(yīng)用;2005年02期

相關(guān)博士學(xué)位論文 前3條

1 賀建軍;基于高斯過程模型的機器學(xué)習(xí)算法研究及應(yīng)用[D];大連理工大學(xué);2012年

2 王潔;基于貝葉斯估計方法的無線定位跟蹤技術(shù)研究[D];大連理工大學(xué);2011年

3 寇曉麗;群智能算法及其應(yīng)用研究[D];西安電子科技大學(xué);2009年

相關(guān)碩士學(xué)位論文 前2條

1 傅童昌健;基于背景提取的無設(shè)備目標(biāo)定位（DFPL）技術(shù)研究[D];南京師范大學(xué);2014年

2 何平;基于ZigBee技術(shù)的定位技術(shù)研究與應(yīng)用[D];南京郵電大學(xué);2012年

，

本文編號：1577598