摘要
智能空间中的上下文感知为用户提供其所在环境的上下文相关信息,其中80%的信息和位置有关,因此定位问题在上下文感知中占据举足轻重的地位。智能空间中设备的许多行为都与其所在的位置相关联,如实时跟踪用户所处的位置、自动打开用户附近的灯或将来电转接到离用户最近的电话等,所有这些应用都需要判断用户在室内的位置,以及与其它设备之间的相对位置关系。定位信息的准确获取是完成定位服务的一个关键问题所在,那么如何简单、及时有效、准确地获取移动用户的定位信息,以便主动向用户提供所需定位服务是目前智能空间中需要研究的基础课题之一
在智能环境未知节点进行定位的过程中,信号传播延迟、参考点之间的相对位置等都会对未知节点的定位误差产生影响。对于参考点位置所引起的定位误差,由于智能环境中未知节点定位需要通过多个定位参考点来计算其位置,那么如何在这些参考点中选择最优的参考点使定位误差最小是本文要研究问题。
在二维空间定位服务中,在不存在定位误差情况下,提出了关于二维空间定位算子的两个定理,定位算子定理为未知节点的位置计算提供一种快捷的方法。对于定位过程存在误差情况下,通过对定位过程中产生的误差区域进行分析,提出了二维空间参考点优化选择定理,参考点优化选择定理表明在室内定位过程中有针对性选择参考点能使定位误差最小,为室内环境中布置和选择定位参考点提供了相应的理论基础。在此基础上,研究了未知节点被多次定位后定位误差极限问题,提出了定位误差极限定理,定位误差极限定理揭示了当有无限多个参考点参与对未知节点定位时,定位误差不会持续减小下去,而是最后趋于恒定值。基于参考点优化选择定理,通过对传统的定位算法进行改进,提出参考点优化选择算法(OSRN), OSRN算法以参考点与未知节点之间位置关系为基础,通过选择出合适的参考点来计算未知节点的位置,可以提供更准确的定位信息,并保证该算法具有较强的定位实时性,从而满足智能空间中移动用户定位服务的需求。以上这些定理为移动设备在二维空间定位过程中有针对减少由参考点引起的定位误差提供了依据。
定位过程中不可避免地存在着误差,通过分析三维空间定位过程中产生的误差区域,提出了空间参考点优化选择第一定理(SOSRN1)和空间参考点优化选择第二定理(SOSRN2), SOSRN1定理和SOSRN2定理从理论上证明三维空间定位过程中当未知节点与定位参考点满足某种分布时,定位误差最小。在此基础上,对空间未知节点多次定位后的误差区域研究发现,随着定位单元数目增加,定位误差不断减小,但不会无限制减小,而是定位误差最后趋于一个常量。在智能空间中,由于设备的资源有限,并且它们所面临的任务一般都是时间敏感性较强的应用空间,传统的定位算法,无法在资源受限的普适设备上实现,同时又不能很好的保证时间约束,基于SOSRN定理,提出了空间参考点优化选择算法。空间参考点优化选择(SOSRN)算法为未知节点在空间定位提供更准确的位置信息,并且改进定位实时性,从而满足定位服务的需求。
对于参考点位置所引起的定位误差进行定量分析,结果表明采用参考点优化选择算法定位能较大幅度提高定位精度,并且通过有限的几次定位就能使定位误差迅速趋于最小值,由此提出了二维空间快速参考点优化选择算法(FOSRN)和三维空间快速参考点优化选择算法(FSOSRN), FOSRN和FSOSRN在保证定位精度情况下实时性较好,特别适合应用于有较多参考点的智能空间定位中。
利用仿真实验对本文提出的OSRN和SOSRN算法进行了仿真验证,通过对得到的实验数据进行的分析,并与传统的算法相比较,结果表明OSRN算法SOSRN算法能够在资源有限环境下的改进未知节点定位实时性,并使得在一定的范围内未知节点在定位过程中产生的误差较小,有效解决了智能空间中的移动用户的定位需求。
Context awareness can provide the user with important context information in smart space, which is about 80 percent mainly related to position. Consequently the problem of position is playing an important role in context awareness. Many behaviors of the device is related to its position, for example, track the user's position in real-time, turning on the light near the user automatically, or transferring the phone to the nearest user, and so on. All the application should be capable to determine the user's position in a room, and the relative position with other devices. To accurately obtain the position information is the key to finish the positioning service, therefore how to simply, efficiently, accurately acquire the user's position information, and being able to provide the positioning service to user, is one of the basis problems in smart space.
In the process of the positioning of the unknown node in the smart space, time error and relative position of reference nodes are the main causes of affecting the unknown nodes' position error. With regards to the position error caused by the position of reference node, the position of unknown node in the smart space is decided by reference to several position reference nodes. Therefore the problem that how to choose the most optimum reference node among all the reference nodes in order to reduce the position error to the great extend becomes the main topic of this paper.
In the positioning service of two dimensional space, two arithmetic operators theorems on two dimensional space are put forward on the basis of non-existence of position error. Arithmetic operators theorems provide a fast way of computing the position of unknown node. In the existence of position error in the process of positioning, reference nodes optimizing selection theorem in two dimensional space is proposed on the basis of analyzing the position error areas. This theorem shows that optimization selection of reference nodes will minimize the position error in the process of indoor positioning. Meanwhile this theorem builds up theoretical foundation for the layout and selection of reference nodes in indoor environment. Based on this, the research on the problem of position error limit caused by positioning the unknown nodes several times is conducted. Correspondingly the position error limit theorem is put forward, which reflects the fact that the position error can not be reduced gradually to zero when the positioning of unknown nodes involves limitless reference nodes, instead the position error will be reduced to a constant quantity. On the basis of reference nodes optimizing selection theorem and the improvement of the traditional positioning algorithm, optimization selection algorithm of reference nodes (OSRN) is produced. This algorithm is based on the relationship of the position of reference nodes and the position of unknown node. By the way of selecting optimum reference nodes in the process of calculating the unknown nodes'position, the more accurate position information can be delivered and the real-time sensitivity can be fulfilled. As a result, the requirements of positioning service from mobile users in the smart space are satisfied. All the above mentioned theorems are the basis for the mobile devices'specially reducing the position error caused by reference nodes in the process of positioning in two dimensional space.
It is impossible to avoid any error in the process of positioning. On the basis of the research of positioning problem in three dimensional space, Arithmetic operators theorems are brought forward in three dimensional space, which are the theoretical foundation for the layout of position reference nodes. In the existence of position error, the study on the position error in the process of three dimensional space is conducted. According to the study results, the two theorems are produced:the first theorem of space reference nodes optimizing selection (SOSRN1) and the second theorem of space reference nodes optimizing selection (SOSRN2). These two theorems, in the respect of theory, prove that the position error is the least when the unknown nodes and position reference nodes are in certain layout in three dimensional space. Based on this, the research on the error areas caused by positioning the unknown codes several times is made and the fact is discovered that the position error gradually decreases with the number of position units increases, but the position error can not decrease unlimitedly while it will reach a constant quantity. In the smart space, due to limited resources of a ubiquitous device, the device is usually facing the application with real-time sensitivity. The traditional positioning algorithm can not be implemented for a ubiquitous device with limited resources. Meanwhile, it can not satisfy the time constrains. Therefore based on the SOSRN theorem, the position reference nodes algorithm is proposed. The space position reference nodes optimization selection (SOSRN) algorithm can promise more accurate information with positioning of unknown nodes and meet the requirement of real-time, which will make the requirements from positioning service fulfilled.
Concerning the position error caused by the position reference nodes, it is mainly reduced by the optimization selection of position reference nodes. According to the results of analysing the position error caused by the relative position of reference nodes, the conclusion is made that the accuracy of position can be greatly improved by the adoption of reference nodes optimizing selection and the position error can be reduced to the least through only several times positioning. On the basis of this, the fast reference nodes optimization selection (FOSRN) algorithm and the fast space reference nodes optimization selection (FSOSRN) algorithm are brought forward. FOSRN and FSOSRN can guarantee the position accuracy and meet the requirement of real-time simultaneously, the two algorithms are especially suitable in the smart space positioning with the existence of many reference nodes.
The simulation is used to verify OSRN and SOSRN algorithm in this paper. After the analysis of the data acquired and the comparison with the traditional algorithm, the conclusion is drawn that OSRN and SOSRN algorithm can meet the requirement of real-time positioning of unknown nodes in the environment with limited resources, and make position error less than the traditional algorithm, therefore the algorithm can effectively solve the positioning problem for mobile users in the smart space.
引文
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