本文選題：無(wú)線定位　切入點(diǎn)：無(wú)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(wú)設(shè)備定位(Device-Free Localization,DFL)是一種目標(biāo)無(wú)需攜帶任何電子設(shè)備的無(wú)線定位技術(shù),已被廣泛地應(yīng)用于各個(gè)領(lǐng)域,如入侵檢測(cè)、緊急救援、老人看護(hù)等。該無(wú)線定位技術(shù)通過(guò)分析目標(biāo)所帶來(lái)的監(jiān)測(cè)區(qū)域內(nèi)無(wú)線射頻信號(hào)的變化得以實(shí)現(xiàn)。但由于受環(huán)境時(shí)變、非視距、多路徑信號(hào)傳播等不確定性因素的影響,實(shí)現(xiàn)高精度、抗干擾能力強(qiáng)的DFL仍是亟待解決的、挑戰(zhàn)性的問(wèn)題。構(gòu)建合理的無(wú)線信號(hào)傳播模型是提高DFL精度的有效途徑,為此本文對(duì)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(gè)方面:(1)通過(guò)分析影響鏈路信號(hào)強(qiáng)度波動(dòng)的因素,提出聯(lián)合鏈路檢測(cè)方法,實(shí)現(xiàn)監(jiān)測(cè)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(cè)模型,對(duì)DFL進(jìn)行優(yōu)化方法研究。采用鏈路直線檢測(cè)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(cè)模型,提出了基于凸可行并行投影的DFL方法;通過(guò)實(shí)驗(yàn)驗(yàn)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(wèn)題,通過(guò)分析目標(biāo)對(duì)鏈路信號(hào)強(qiáng)度的影響,構(gòu)建了基于高斯過(guò)程的無(wú)線射頻信號(hào)傳播模型,并通過(guò)實(shí)驗(yàn)測(cè)試該模型的性能。(4)基于高斯過(guò)程無(wú)線射頻信號(hào)傳播模型,結(jié)合聯(lián)合鏈路檢測(cè)方法,將DFL問(wèn)題轉(zhuǎn)化為極大似然概率優(yōu)化問(wèn)題,并提出了相應(yīng)的改進(jìn)果蠅優(yōu)化求解方法;針對(duì)目標(biāo)跟蹤問(wèn)題,提出了基于高斯過(guò)程無(wú)線射頻信號(hào)傳播模型的粒子濾波方法,結(jié)合目標(biāo)運(yùn)動(dòng)模型對(duì)粒子進(jìn)行預(yù)測(cè)和更新,實(shí)現(xiàn)對(duì)目標(biāo)的跟蹤;分別在空曠的室外場(chǎng)景、及復(fù)雜的室內(nèi)場(chǎng)景搭建實(shí)驗(yàn)平臺(tái)對(duì)所提方法進(jìn)行測(cè)試,驗(yàn)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(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP212.9;TN929.5

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