發(fā)布時間：2018-08-15 12:24

【摘要】： 現(xiàn)代室內(nèi)空間可以容納大量的移動對象。例如,人們在日常生活中通常會花費大量的時間活動在諸如辦公樓、購物中心、會展中心、機場及地鐵等交通基礎(chǔ)設(shè)施在內(nèi)的各種室內(nèi)空間。隨著各種室內(nèi)定位技術(shù)的發(fā)展,這些室內(nèi)移動對象的位置可以被確定和記錄下來。對室內(nèi)移動對象的數(shù)據(jù)管理,可以作為一系列室內(nèi)位置服務(wù)的基礎(chǔ),例如室內(nèi)導(dǎo)航,員工安全,室內(nèi)空間規(guī)劃,商鋪促銷,廣告競價等。因此,有效的管理室內(nèi)移動對象,具有重要的應(yīng)用價值。 雖然當前對室外移動對象的數(shù)據(jù)管理問題已經(jīng)有了較充分的研究,然而,這些技術(shù)并不能直接應(yīng)用于室內(nèi)移動對象的管理,主要原因有如下兩點：首先,復(fù)雜的室內(nèi)拓撲結(jié)構(gòu)使得廣泛應(yīng)用于室外空間的距離模型,軌跡表達等都不再適用于室內(nèi)空間。其次,室內(nèi)的定位技術(shù)通常不能像廣泛應(yīng)用于室外空間的GPS定位技術(shù)那樣,連續(xù)不斷的報告室內(nèi)移動對象的位置,從而帶來較大程度的位置不確定性。 本文首先對室外移動對象的管理技術(shù)進行了綜述,指出其直接應(yīng)用在室內(nèi)環(huán)境下的不足。針對室內(nèi)空間的特點,提出了基于圖的室內(nèi)空間建模方法、室內(nèi)移動對象的跟蹤方法,以及室內(nèi)時空范圍查詢、連續(xù)范圍查詢和概率閾值k近鄰查詢等多類查詢處理的新算法及相關(guān)索引結(jié)構(gòu)。 本文的主要貢獻如下： 1.提出了基于圖模型的室內(nèi)空間建模方法�；A(chǔ)圖用于對室內(nèi)空間拓撲信息建模,而部署圖則可以有效的管理符號化定位設(shè)備,并做為室內(nèi)移動對象數(shù)據(jù)管理的基礎(chǔ)。根據(jù)部署圖,對室內(nèi)移動對象的狀態(tài)進行了劃分。 2.基于部署圖模型,分別提出了室內(nèi)移動對象的離線跟蹤方法和在線跟蹤方法。 3.提出了一種基于符號空間的室內(nèi)移動對象歷史軌跡表示方法,并提出了新型索引結(jié)構(gòu)RTR-tree和TP2R-tree對該類型歷史軌跡進行索引,以支持室內(nèi)時空范圍查詢和室內(nèi)邏輯查詢。 4.根據(jù)室內(nèi)移動對象所處的狀態(tài),提出了基于哈希的索引結(jié)構(gòu)用于索引室內(nèi)移動對象的當前位置。并在此基礎(chǔ)上提出一種查詢感知的、增量的連續(xù)范圍查找算法。 5.形式化的分析了室內(nèi)移動對象的不確定性。提出了一種有效的概率閾值k最近鄰查詢處理算法。 本文對室內(nèi)移動對象的數(shù)據(jù)管理進行了系統(tǒng)研究。針對室內(nèi)空間和符號化定位技術(shù)的特點,提出了基于圖模型的室內(nèi)移動對象管理基礎(chǔ);并且基于該圖模型,對室內(nèi)時空范圍查詢,連續(xù)范圍查詢和概率閾值k最近鄰查詢的處理方法做了充分研究。這些技術(shù)可以作為今后室內(nèi)移動對象管理研究的基礎(chǔ),并且可以為實際應(yīng)用中的室內(nèi)位置服務(wù)提供技術(shù)保障。
[Abstract]:Modern indoor space can accommodate a large number of moving objects. For example, people usually spend a lot of time in indoor space such as office building, shopping center, convention and exhibition center, airport and subway and so on. With the development of various indoor positioning technologies, the location of these indoor moving objects can be determined and recorded. The data management of indoor moving objects can be used as the basis of a series of indoor location services, such as indoor navigation, employee safety, indoor space planning, shop promotion, advertising bidding and so on. Therefore, the effective management of indoor moving objects, has an important application value. Although the current data management of outdoor moving objects has been fully studied, these technologies can not be directly applied to the management of indoor moving objects. The main reasons are as follows: first of all, Because of the complex indoor topology, the distance model, trajectory representation and so on, which are widely used in outdoor space, are no longer suitable for indoor space. Secondly, indoor positioning technology usually can not report the location of moving objects continuously as the GPS positioning technology is widely used in outdoor space, which brings a large degree of location uncertainty. In this paper, the management technology of outdoor moving objects is reviewed, and the shortcomings of its direct application in indoor environment are pointed out. According to the characteristics of indoor space, the paper puts forward the modeling method of indoor space based on graph, the tracking method of indoor moving object, and the query of indoor space-time range. A new algorithm for multi-class query processing, such as continuous range query and probabilistic threshold k-nearest neighbor query, and related index structure. The main contributions of this paper are as follows: 1. A method of indoor space modeling based on graph model is proposed. The basic map is used to model the topological information of indoor space, and the deployment plan can effectively manage the symbolic positioning equipment and serve as the basis for the data management of indoor moving objects. According to the deployment diagram, the state of indoor moving objects is divided. 2. 2. Based on the deployment diagram model, an off-line tracking method and an on-line tracking method for indoor moving objects are proposed, respectively. In this paper, a method of representing the historical track of indoor moving object based on symbol space is proposed, and a new index structure, RTR-tree and TP2R-tree, is proposed to index the historical track of this type. To support indoor space-time range query and indoor logic query. 4. According to the state of indoor moving objects, a hash-based index structure is proposed to index the current position of indoor moving objects. On this basis, a query aware, incremental continuous range lookup algorithm is proposed. 5. The uncertainty of indoor moving object is analyzed formally. An effective probability threshold k nearest neighbor query processing algorithm is proposed. In this paper, the data management of indoor moving objects is studied systematically. According to the characteristics of indoor space and symbolic positioning technology, the paper puts forward the management foundation of indoor moving objects based on graph model, and queries the scope of indoor space and time based on the graph model. The processing methods of continuous range query and probability threshold k nearest neighbor query are studied. These technologies can be used as the basis of the research on indoor moving object management in the future, and can provide technical support for indoor location service in practical application.
【學(xué)位授予單位】：復(fù)旦大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2010
【分類號】：TP274

【引證文獻】

相關(guān)會議論文 前1條

1 何鳳成;劉奎恩;許佳捷;徐懷野;丁治明;;Hestus:一種海量異構(gòu)物聯(lián)網(wǎng)數(shù)據(jù)存儲模型及其實現(xiàn)[A];第29屆中國數(shù)據(jù)庫學(xué)術(shù)會議論文集（B輯）（NDBC2012）[C];2012年

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本文編號：2184187