發(fā)布時間：2018-04-25 12:20

  本文選題：室內標簽定位 + 樓層定位��； 參考：《南京大學》2016年博士論文

【摘要】：隨著Internet的快速發(fā)展與移動智能設備的廣泛普及,基于位置的應用及服務已經與人們的日常生活息息相關,GPS無法滿足的室內位置需求出現(xiàn)了爆發(fā)式增長,迫切需要新的更有效的室內標簽定位技術。目前室內標簽定位場景下的應用,對定位的需求已經不僅僅滿足于精度,對可靠性、可用性及成本等方面也有較高的要求。但室內場景的普遍復雜化、定位設施的廣泛缺乏及定位需求的多樣化,導致傳統(tǒng)的室內定位技術難以滿足要求�；趥鹘y(tǒng)的室內標簽定位技術,本文的研究思路是充分利用定位場景下豐富的智能手機感知和計算資源,不依賴額外的基礎設施和技術維護人員,使定位系統(tǒng)在滿足標簽定位精度的同時提高可靠性、可用性和降低成本。本文提出了一個室內標簽定位技術框架,然后對室內樓層定位問題和地鐵定位問題進行了研究,還提出了一套通用的智能手機傳感器校準方案。最后在框架基礎上設計與實現(xiàn)了一個室內標簽定位技術平臺并開發(fā)了“位動校園”應用示例。具體而言,本文取得了以下創(chuàng)新性成果：·系統(tǒng)性的提出了一個基于智能手機、基礎設施低依賴的面向室內標簽定位的技術框架(SIFIS)。針對傳統(tǒng)室內標簽定位技術對基礎設施依賴性較高的不足,提出了一個融合行為識別、群智感知計算和模式識別技術的新型室內標簽定位技術框架。該框架的基礎設施依賴性較低,使得該技術在滿足精度的要求下有更好的可靠性、可用性和較低的成本�！せ赟IFIS技術框架,針對室內樓層定位需求,僅利用智能手機的加速度、氣壓、地磁等感知能力,提出了基于機器學習的上下樓行為識別算法、基于軌跡匹配的相遇算法、基于動態(tài)時間規(guī)整(DTW)的標簽定位等算法,實現(xiàn)了無基礎設施支撐條件下的室內樓層定位。模擬實驗和現(xiàn)場實驗均表明,該方案不僅能滿足定位精度,而且具有更好的可靠性、可用性和更低的成本�！せ赟IFIS技術框架,針對地鐵位置定位需求,僅利用智能手機的加速度、氣壓、地磁等感知能力,提出了基于狀態(tài)機的地鐵啟停判定和開關門判定算法、基于動態(tài)時間規(guī)整(DTW)的標簽定位等算法,實現(xiàn)了無基礎設施支撐條件下的地鐵位置定位�，F(xiàn)場實驗表明,該方案不僅能滿足定位精度,而且具有更好的可靠性、可用性和更低的成本�！め槍χ悄苁謾C傳感器誤差的自然存在以及必定影響定位準確性的特征,提出了一個相對通用的傳感器校準方案。該方案利用群智感知技術,提出了基于相遇識別的兩兩校準和基于最矮生成樹的全局校準方案,校準過程透明于用戶,為室內標簽定位奠定了數據準確性的基礎。氣壓傳感器校準實驗表明,該方案具有良好的實用性和通用性�！ぴO計并初步實現(xiàn)了室內標簽定位技術平臺,并基于此平臺實現(xiàn)了一個基于位置的社交應用示例。該應用基于定位平臺,通過用戶的位置描述用戶的特征,依據特征進行交友推薦。體現(xiàn)了室內標簽定位技術的可行性和廣泛的應用前景。
[Abstract]:With the rapid development of Internet and the widespread popularity of mobile intelligent equipment, location based applications and services have been closely related to people's daily life. GPS can not meet the explosive growth of the indoor location demand, and a new and more effective indoor label positioning technology is urgently needed. The demand for positioning has not only been satisfied with accuracy, but also has high requirements on reliability, availability and cost. However, the general complexity of the indoor scene, the wide lack of location facilities and the diversification of the location requirements lead to the difficulty of meeting the requirements of the traditional indoor positioning technology. The research idea is to make full use of the rich intelligent mobile phone perception and computing resources under the positioning scene, and do not rely on additional infrastructure and technical maintenance personnel, so that the positioning system can improve the reliability, availability and reduce the cost while satisfying the positioning accuracy of the label. The problem of floor location and subway positioning is studied, and a set of universal smart phone sensor calibration scheme is put forward. At last, an indoor label positioning technology platform is designed and implemented on the basis of the framework and the application example of "mobile campus" is developed. In particular, the following innovative results are obtained:. A technical framework based on smart phone and low dependency on infrastructure (SIFIS) is proposed. In view of the high dependence of traditional indoor label positioning technology on infrastructure, a new indoor tag positioning technology framework is proposed for fusion behavior recognition, swarm intelligence perception calculation and mode recognition technology. The dependency of the framework is low, which makes the technology have better reliability, availability and lower cost under the requirement of precision. Based on the SIFIS technical framework, the performance of the indoor floor positioning needs only by using the intelligent mobile phone acceleration, pressure, and geomagnetism ability, and puts forward the behavior of up and down building based on machine learning. Recognition algorithm, track matching based meeting algorithm, based on dynamic time warping (DTW) label location algorithm, implemented the indoor floor positioning without infrastructure support. Both simulation experiment and field experiment show that the scheme not only satisfies the positioning accuracy, but also has better reliability, availability and lower cost. Based on the SIFIS technology framework, based on the acceleration, air pressure and geomagnetism of the smart phone, the subway start stop decision and the switch gate determination algorithm based on the state machine are proposed. Based on the dynamic time regularization (DTW), the subway location is determined without infrastructure support. Field experiments show that the scheme not only satisfies the positioning accuracy, but also has better reliability, availability and lower cost. In view of the natural existence of the sensor error and the characteristics that must affect the accuracy of the location, a relative universal sensor calibration scheme is proposed. The scheme uses group intelligence sensing technology. The 22 calibration based on meeting recognition and the global calibration scheme based on the shortest generation tree are proposed. The calibration process is transparent to the user, which lays the foundation for the accuracy of the indoor label location. The pressure sensor calibration experiment shows that the scheme has good practicability and generality. Based on this platform, an example of a location based social application is implemented. The application is based on the location platform, describes the user's features through the user's position, and recommends friends according to the features. It embodies the feasibility and wide application prospect of the indoor label positioning technology.

【學位授予單位】：南京大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：TN929.5

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本文編號：1801283