【作者】 史伟光；

【导师】 刘开华；

【作者基本信息】 天津大学 ， 电路与系统， 2012， 博士

【摘要】 在情境感知服务技术领域,服务对象的位置信息是最重要的环境参数之一,决定着情境服务能否有效、准确的施行。业已成熟的GPS系统能够为情景感知服务提供精度小于5m的室外位置信息,然而建筑物的屏蔽作用令其室内定位精度大打折扣,过高的系统成本使其直接应用于室内环境也存在困难。近年来,基于无线传感器网络、超宽带、红外线、射频识别等技术的室内定位研究开展得如火如荼,尤其是射频识别技术,凭借非接触、非视距、短时延、高精度、传输范围大和成本低等优点已成为室内定位技术的主要选择。目前,基于射频识别技术的室内定位算法的定位依据主要是阅读器检测到的信号收信场强。典型代表是LANDMARC算法,通过引入参考标签动态捕捉环境信息替代阅读器的离线数据,比较参考标签和待定位标签在多个阅读器上的收信场强差异,基于场强欧式距离选取近邻参考标签,利用残差加权算法确定待定位标签的物理位置,LANDMARC算法不仅降低了系统成本,提高了系统的环境适应能力,而且具有比较理想的室内定位精度。尽管如此,LANDMARC系统仍存在一些缺陷和不足:如非测距算法使得算法精度有限、定位精度受制于参考标签布设密度等。本文在详细分析LANDMARC算法特性及室内环境中的时间延迟信道模型的基础上,对射频识别定位算法进行了深入研究,主要内容包括以下几个方面:(1)针对LANDMARC算法中TTBDA的定位精度较低的问题,提出了一种基于加权欧式算子的改进定位算法,引入基于待定位标签及参考标签收信场强值的加权欧式算子调整各个阅读器的定位信息可靠性,算法在几乎不影响TTCDA (Tracking Tags Covered by Detection Area,处于监测区域内并被有效覆盖定位标签)的定位精度前提下,对TTBDA的定位精度有了较大的提升。(2)针对LANDMARC算法的定位精度受制于参考标签部署密度的问题,提出了基于子区域动态二次回归插值的VIRE改进定位算法。算法首先提出一种子区域选取机制以实现虚拟参考标签的动态引入,然后提出一种基于二次曲线回归的插值算法估计虚拟参考标签的收信场强值,并利用历史校正机制进一步客服偶然误差。相比于VIRE算法,改进算法对于AGVs系统及多个定位目标位置集中的情形,能够有效降低插值计算量,并且具备更好的定位精度。(3)对于室内环境中各区域特性(如目标出现概率、障碍物分布等)差异较大的情况,针对LANDMARC算法中采用网格状均匀部署有源参考标签难以保证全局定位精度的问题,基于联合高斯分布的目标概率模型和Keenan-Motley模型确定优化函数,提出了一种基于改进粒子群算法的寻优策略,实现对有源参考标签的优化部署。(4)考虑到LANDMARC系统中的非测距定位机制使得算法定位精度难以进一步提高的问题。以收发信号的相位差作为定位依据,提出了一种适用于ISO/IEC 18000-6C标准的UHF RFID室内定位机制,引入双频副载波克服整周期模糊度并降低采样率要求,并提出欠采样条件下的相位差估计方法及测距机制,结合全相位FFT谱分析的“相位不变性”获取接收端信号相位信息并测距。更多还原

【Abstract】 As an environmental factor in context-aware system, the target location information plays an important role in governing the effectiveness and accuracy of situation-dependent services. However, typical positioning system GPS is not available for the indoor localization due to its high costs and shielding effect caused by the buildings, though a fully-fledged solution to the outside localization. Hence,the research of the indoor location sensing systems based on WSN, UWB, IF attract lots of attention in the past decade. Among others, RFID provide an excellent approach with its advantages of non line of sight, the non-contacting and low cost.Currently, most indoor location systems based on RFID technology utilize received signal strength indicator to locate objects. LANDMARC algorithm, a common example, reduces system cost and improves the environmental suitability by introducing the active reference tags to replace the reader. After calculating the Euclidian distance in signal strength between a tracking tag and each reference tag, the algorithm chooses k nearest reference tags and uses their coordinates to locate the tracking tag. Compared with other location algorithms, LANDMARC achieves a better overall accuracy of position. However , LANDMARC still faces some drawbacks and disadvantages. On the basis of the analysis of LANDMARC algorithm and building the channel model toward time delay, the major research of this dissertation specifically stated as follows:(1) To investigate the location accuracy of TTBDA (Tracking Tags near the Boundary of Detection Area) is not as good as that of TTCDA (Tracking Tags Covered by Detection Area), an optimized ranging location algorithm was proposed. By introducing the weighted factor, the algorithm rectifies the received signal strength indication values’credibility on each reader. Simulation results showed that the proposed algorithm achieves a higher accuracy and better environmental suitability towards TTBDA compared with LANDMARC.(2) In order to solve the location accuracy of LANDMARC being restricted by the number of reference tags, an enhanced VIRE location algorithm based on Subregion Dynamic Quadratic Regression Interpolation (SDQRI) was proposed. The enhanced algprothm suggests a subregion selcetion mechanism to introduce vitual reference tags dynamically, and puts forward an interpolation algorithm on the basis of quadratic regression to compute the RSSI values of VRTual reference tags. The historical information of localization is utilized to rectify the accidental error as well. Compared with VIRE algprithm, the enhanced algorithms enjoy the less amount of interpolation calculation in the AGVs system and in the case of the tracking tags highly centralized. Simulation results also demonstrated that the location accuracy of optimized algorithm is better.(3) Since the uniform arrangement of the reference tags is not applicabale in rhe case that the probability occurrence of each area differs greatly, or obstacles like wall and partition exist, an event-based occurrence probability based on the multi-gaussian distribution model and Keenan-Motley model was proposed to establish the optimization problem.An improved PSO optimizing mechanism was suggested to solve the optimization problem. Simulation results showed that the proposed algorithm outperforms the arrangement and layout adopted by genetic algorithm(4) Considering the accuracy of LANDMARC system being restricted by the range free mechanism, a location algorithm using 915MHZ UHF signal was proposed. Dual frequency subcarriers were introduced to overcome the ambiguity of whole cycles and reduce the demands of sample rate. On the basis of spectrum analysis of All-Phase FFT, a mechanism was put forward to estimate the phase difference so as to achieve the ranging information with under-sampling.Simulation results showed that the proposed algorithm possesses a higher accuracy and stability.更多还原