本文選題：移動(dòng)計(jì)算　切入點(diǎn)：室內(nèi)定位　出處：《中國(guó)科學(xué)技術(shù)大學(xué)》2017年博士論文　論文類型：學(xué)位論文

【摘要】：移動(dòng)計(jì)算的蓬勃發(fā)展和智能設(shè)備的更新?lián)Q代,顛覆性地變革了現(xiàn)代人類的生活方式。用戶隨身攜帶的智能設(shè)備和日益普及的物聯(lián)網(wǎng)設(shè)施不僅僅可以隨時(shí)訪問(wèn)和處理信息,還可以實(shí)時(shí)感知用戶行為和周圍環(huán)境的變化。這些智能設(shè)備在知曉1)用戶的位置信息以及2)行為信息之后,可以協(xié)助拓展單個(gè)人類個(gè)體有限的感知范圍。為了實(shí)現(xiàn)這個(gè)目標(biāo),學(xué)術(shù)界和工業(yè)界提出了大量的1)定位系統(tǒng)與2)行為感知系統(tǒng)來(lái)滿足日益增長(zhǎng)的需求。但是,在定位系統(tǒng)方面,當(dāng)前主流的基于WiFi信號(hào)的室內(nèi)定位系統(tǒng)易受到來(lái)自環(huán)境變化的嚴(yán)重影響,而信源數(shù)目的不足也會(huì)嚴(yán)重影響其精度和覆蓋范圍。與此同時(shí),在感知系統(tǒng)方面,主流的基于計(jì)算機(jī)視覺(jué)的行為感知與識(shí)別系統(tǒng)面臨著較高的部署開銷和高精度圖像帶來(lái)的隱私問(wèn)題�？梢姽馐侨搜酆椭悄茉O(shè)備均可感知的電磁波譜片段,是最為普遍的,無(wú)處不在的電磁波�？梢姽饩哂休^強(qiáng)的方向性,不易受到環(huán)境變化的影響,且在室內(nèi)場(chǎng)景中密集部署的照明用光源直接可用作信源,降低了系統(tǒng)部署的開銷和復(fù)雜性�？梢姽獾膬�(yōu)良特性使其有望成為感知用戶位置和行為的下一個(gè)主要媒介。然而,設(shè)計(jì)基于可見光的定位和感知技術(shù)存在若干難點(diǎn)。首先,有別于WiFi信號(hào),智能設(shè)備采集到的接收光照強(qiáng)度(RLS,received light strength)僅僅是一個(gè)標(biāo)量,缺乏用于標(biāo)識(shí)信源身份的標(biāo)志(光源的編號(hào));這導(dǎo)致了一個(gè)相似的RLS可以在多個(gè)室內(nèi)物理位置被捕捉到。其次,有別于WiFi信號(hào),RLS對(duì)智能設(shè)備朝向,高度極度敏感;這使得影響RLS的變量空間具有較高維度,從而難以通過(guò)傳統(tǒng)的非測(cè)距方法來(lái)建立RLS和室內(nèi)物理位置的關(guān)聯(lián)。再次,若干用戶行為的高自由度(例如,手掌有23個(gè)自由度)使得借由粗粒度的接收光照強(qiáng)度信息恢復(fù)出細(xì)粒度的用戶行為成為一個(gè)困難的任務(wù)。面臨這些挑戰(zhàn)和問(wèn)題,本研究的主要研究和創(chuàng)新成果如下:·設(shè)計(jì)了一個(gè)基于可見光的室內(nèi)定位原型系統(tǒng),Lightitude。本系統(tǒng)的核心觀察在于,不同室內(nèi)物理位置的可見光信源的光照強(qiáng)度有差別,并且這個(gè)差別對(duì)智能設(shè)備上搭載的光傳感器來(lái)說(shuō)是非常明顯的。鑒于此,智能設(shè)備采集到的信號(hào)強(qiáng)度可以對(duì)應(yīng)特定的室內(nèi)物理位置。本研究首先提出了一個(gè)適用于實(shí)際場(chǎng)景的可見光傳播模型來(lái)描述RLS和設(shè)備當(dāng)前狀態(tài)的關(guān)聯(lián),并基于此設(shè)計(jì)了一個(gè)以粒子濾波器為核心的定位方案。真實(shí)環(huán)境中的實(shí)驗(yàn)證實(shí)了 Lightitude系統(tǒng)能夠精確地確定用戶在實(shí)驗(yàn)場(chǎng)景中的位置。與此同時(shí),Lightitude系統(tǒng)在面對(duì)障礙物的遮擋,用戶的意外行為以及日光的影響之下依然具有較強(qiáng)的魯棒性。·設(shè)計(jì)了一個(gè)基于可見光的室內(nèi)推薦原型系統(tǒng),LiLoc。本系統(tǒng)的核心觀察在于,特定的通路具有獨(dú)特的光強(qiáng)特性。這樣,服務(wù)提供商可以通過(guò)簡(jiǎn)單的一次性場(chǎng)景遍歷,使用微小的人力代價(jià)建立場(chǎng)景信息數(shù)據(jù)庫(kù)。借助用戶在大型室內(nèi)場(chǎng)景中的移動(dòng)性,LiLoc系統(tǒng)首先確定用戶在場(chǎng)景信息數(shù)據(jù)庫(kù)中的相對(duì)位置,從而在線下向用戶推送當(dāng)前位置所對(duì)應(yīng)的推薦服務(wù)信息。進(jìn)一步地,LiLoc系統(tǒng)可以以高精度識(shí)別三種用戶的典型行為(行走,駐足,伸手查看),從而可以進(jìn)一步幫助用戶離開室內(nèi)場(chǎng)景后的輔助線上推薦。真實(shí)環(huán)境中的實(shí)驗(yàn)驗(yàn)證了 LiLoc系統(tǒng)具有較高的推薦精度�！ぴO(shè)計(jì)了一個(gè)基于可見光的細(xì)粒度手掌輪廓恢復(fù)及移動(dòng)監(jiān)測(cè)技術(shù),HandSense。本系統(tǒng)的核心觀察在于,作為一個(gè)實(shí)心的障礙物,人的手掌既可以阻礙從光源(例如,日光,LED)到光傳感器的可見光通路,也可以反射微弱的反向散射信號(hào)。這兩種效應(yīng)均可被預(yù)先部署的光傳感器陣列所感知。這樣,特定的手掌狀態(tài)對(duì)應(yīng)著一組特定的接受光照強(qiáng)度集合。實(shí)驗(yàn)者在服務(wù)器上實(shí)現(xiàn)了可見光遮擋監(jiān)測(cè)和可見光反向散射監(jiān)測(cè),結(jié)合解剖學(xué)模型所描述的手掌固有限制,設(shè)計(jì)了一個(gè)啟發(fā)式的優(yōu)化算法,用于實(shí)現(xiàn)手掌的輪廓恢復(fù)和姿態(tài)監(jiān)測(cè),為進(jìn)一步的高精度室內(nèi)推薦提供客觀依據(jù)。真實(shí)環(huán)境中的實(shí)驗(yàn)證實(shí)了 HandSense系統(tǒng)能夠精確地感知用戶手掌的輪廓,移動(dòng),以及姿態(tài)。
[Abstract]:The vigorous development of mobile computing and intelligent equipment upgrading, subversive to the revolution of modern human lifestyle. Intelligent equipment carried by the client and the increasing popularity of networking facilities not only can access and process information at any time, you can also change the real-time perception of user behavior and the environment. These smart devices in the known position 1) the user information and behavior information, 2) can assist the development of a single individual limited sensing range. In order to achieve this goal, academia and industry put forward a lot of 1) 2) positioning system and behavior perception system to meet the growing demand. However, in the positioning system, the current mainstream indoor positioning the system based on the signal of WiFi susceptible to serious impact from changes in the environment, rather than the number of source will seriously affect the precision and coverage. At the same time, in the The perception system, mainstream behavior perception and recognition system of computer vision facing privacy issues high deployment overhead and high precision image based on visible light is electromagnetic spectrum fragments and smart devices can sense the human eye, is the most common, the ubiquity of electromagnetic waves. The visible light has strong directivity and influence not susceptible to changes in the environment, and in the indoor scene in densely deployed light sources can be used as a direct source, reduce the cost and complexity of the deployment of the system. The excellent characteristics of visible light which is expected to become the next major media user position and behavior with perception. However, the design positioning of visible light and sensing technology there are a number of difficulties. Based on the first, is different from the WiFi signal, receiving intelligent equipment to collect light intensity (RLS, received light strength) is just a scalar, for lack of identification Mark the identity of the source (source code); this leads to a similar RLS can be captured in a plurality of indoor physical location. Secondly, different from the WiFi signal, RLS of smart devices to highly sensitive; this makes the variable space effect of RLS has high correlation dimension, and it is difficult to through the distance the traditional method to build RLS and indoor physical location. Again, a high degree of freedom some user behavior (for example, the palm has 23 degrees of freedom) made by receiving coarse-grained light intensity information to restore the fine-grained user behavior becomes a difficult task. Facing these challenges and problems, the main research and the innovation results of this study are as follows: the design of a prototype system based on indoor positioning of visible light, is to observe Lightitude. the core of this system, the physical location of the different indoor visible light source light intensity difference, And the difference is very obvious in the light sensor mounted on the intelligent equipment. In view of this, the signal intensity of intelligent equipment collected can correspond to the specific indoor physical location. The visible light propagation model, this paper puts forward a suitable for the actual scene to describe the association between RLS and the current state of equipment, and based on this the design of a particle filter core positioning scheme. The real environment experiment proved that Lightitude system can accurately determine the location of the user in the scene. At the same time, the Lightitude system in the face of occlusion avoidance obstacle, under the unexpected behavior of users as well as the effect of sunlight still has strong robustness and design. A recommendation system based on the indoor visible light is observed, LiLoc. the core of this system, the specific pathway has unique characteristics of light intensity. This service Service providers can one-time scene traversal simple, use the tiny human cost to build the scene information database. With the user in a large indoor scene in LiLoc mobility, the system first determines the relative position of the user in the scene information in the database, so online users push to the position corresponding to the information recommendation service. Further, typical the behavior of LiLoc system with high precision can identify three kinds of users (walk, stop, hand, view) so it can help online help users leave the indoor scene after further recommended. In real environment experiment verifies the accuracy of recommendation LiLoc system has high. Design a fine-grained palm contour recovery and visible light mobile monitoring technology based on the observation of HandSense. is the core of this system, as a solid obstacle, the palm can hinder from light source (for example, sun, LED) to the visible light channel light sensor, also can be reflected back scattering signal. The weak light perception sensor array of these two effects can be pre deployment. In this way, the specific state corresponds to a specific set of palm received light intensity collection. Experimenters in the server implementation the visible light shielding monitoring and visible light backscatter monitoring, combined with the anatomical model described by palm inherent limitations, a heuristic optimization algorithm design, for the realization of palm contour recovery and posture monitoring, provide objective basis for high precision indoor further recommended. The real environment experiment proved that HandSense system can accurately the perception of a user's palm contour, mobile, and attitude.

【學(xué)位授予單位】：中國(guó)科學(xué)技術(shù)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

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