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基于UWB的定位方法研究

发布时间:2018-07-15 13:32
【摘要】:近年来,位置服务产业发展迅猛,并在物联网、智慧城市建设、救灾减灾等诸多领域有着广阔的市场空间。当前,全球定位系统(Global Positioning System, GPS)已解决了室外定位问题,而对于GPS无法覆盖的室内环境,实现高精度定位依然面临着极大挑战。超宽带(Ultra-Wideband, UWB)技术具有穿透能力强、测距精度高、抗多径能力强等优点,是实现高精度定位的关键技术。本文研究了基于超宽带的定位方法,讨论了超宽带定位技术的研究现状及仍需解决的问题,针对室内多径信道提出了两种改进的时延估计(Time of Arrival,TOA)算法,并给出了仿真分析,从理论上证明了算法的有效性。另外,本论文针对无线传感网中参考节点覆盖率不足的场景,提出了两种高效的协作定位方法,所提方法改善定位性能的同时实现了网络中能量、信息的有效管理。其主要贡献如下: 首先,本论文针对适于UWB测距的TOA估计算法,分析了现有TOA估计算法的不足以及制约TOA估计精度的关键因素,探讨了接收信号的特征,提出了基于校验窗的TOA估计算法和基于误差特征的TOA估计算法。不同于传统TOA估计算法,各个能量样本独立判决,基于校验窗的TOA估计算法充分利用了信号样本在时间维度上的相关性,通过多个能量样本联合检测提高了估计精度,因此该算法可以用于改善其它TOA估计算法,是一种通用的TOA改进技术。基于误差特征的TOA估计算法则从另外一个角度考虑,分析了阈值和检测误差之间的关系,建立了误差类型函数,通过误差类型函数自适应调整阈值,与传统TOA估计算法不同的是,该算法不需要先验信道状态信息(Channel State Information, CSI),采用了基于判决反馈的自适应阈值,有良好的抗干扰性能。 此外,本论文针对网络定位的实施问题做了进一步讨论,重点研究了协作定位技术。众所周知,协作定位很好的解决了参考节点覆盖率不足的问题,但当前协作定位由于复杂度过高、节点能耗大等问题受到应用限制。本论文将协作定位分解为定位估计和信息控制两个子模块,提出了基于引导渗流控制信息传播的协作定位方案,在引导渗流的控制作用下,只有满足激活条件的节点可以实施位置估计和位置信息广播,因此,所提方案实现了能量管理和信息管理。同时,由于所提方案减少了误差信息的传播,提高了定位性能。 最后,本论文将引导渗流的思路扩展至贝叶斯网络定位,提出了基于分层的非参数置信度传播(Nonparametric Belief Propagation, NBP)定位算法。论文重新构架了基于引导渗流定位问题的图模型,形成了分层的图模型,设计了基于分层图模型的消息传播准则,给出了相应的用于实现的基于分层的NBP定位算法。仿真结果验证了所提算法的有效性。传统的协作定位算法中,由于各个节点都广播位置信息,且消息不受控制的传播,导致各节点位置估计收敛速度很慢甚至无法收敛,所提算法通过控制节点状态以及消息传播,形成了有序的流动状态,使得消息总是从置信度高的节点流向置信度低的节点,因此,有效实现了能量管理,抑制了误差传播现象。
[Abstract]:In recent years, the position service industry has developed rapidly, and has broad market space in many fields, such as the Internet of things, intelligent city construction, disaster relief, disaster relief and so on. At present, the Global Positioning System (GPS) has solved the problem of outdoor location, and still faces the extremely high precision positioning for the indoor environment which can not be covered by GPS. Great challenge. Ultra-Wideband (UWB) technology has the advantages of strong penetration ability, high precision and strong anti multipath ability. It is the key technology to realize high precision positioning. This paper studies the localization method based on ultra wideband, discusses the research status of UWB positioning technology and the problems still need to be solved, and proposes the indoor multipath channel. Two improved Time of Arrival (TOA) algorithm and simulation analysis are given, and the effectiveness of the algorithm is proved theoretically. In addition, two efficient cooperative positioning methods are proposed for the scenario of insufficient coverage of reference nodes in wireless sensor networks. The proposed method improves the location performance and realizes the network at the same time. The main contributions are as follows:
First, this paper, aiming at the TOA estimation algorithm suitable for UWB ranging, analyzes the shortcomings of the existing TOA estimation algorithms and the key factors that restrict the accuracy of the TOA estimation. The characteristics of the received signals are discussed, and the TOA estimation algorithm based on the checkwindow and the TOA estimation method based on the error characteristics are proposed. Different from the traditional TOA estimation algorithms, each energy sample is different. In this independent decision, the TOA estimation algorithm based on the checkwindow makes full use of the correlation of the signal samples in the time dimension and improves the estimation accuracy through joint detection of multiple energy samples. Therefore, the algorithm can be used to improve the other TOA estimation algorithms and is a general TOA improvement technique. The TOA estimation algorithm based on the error features is from the other. On the other hand, the relationship between threshold and detection error is analyzed, and an error type function is established. The error type function adaptively adjusts the threshold value. Unlike the traditional TOA estimation algorithm, the algorithm does not need a priori channel state information (Channel State Information, CSI), and the adaptive threshold based on decision feedback is adopted. It has good anti-jamming performance.
In addition, this paper further discusses the implementation of network positioning, focusing on Collaborative positioning technology. It is well known that collaborative positioning is a good solution to the problem of insufficient coverage of reference nodes. However, the current collaborative positioning is restricted by the application because of high complexity and large energy consumption. It is solved as two sub modules of location estimation and information control. A collaborative positioning scheme based on guided percolation control information transmission is proposed. Under the control of guided percolation, only the nodes that satisfy the activation condition can implement position estimation and position information broadcasting. Therefore, the proposed scheme realizes energy management and information management. The proposed scheme reduces the propagation of error information and improves the positioning performance.
Finally, this paper extends the thought of percolation to Bayesian network positioning, and proposes a hierarchical non parametric Nonparametric Belief Propagation (NBP) location algorithm. The paper reconstructs a graph model based on the guidance percolation location problem, forms a hierarchical graph model, and designs a hierarchical graph model. The simulation results verify the effectiveness of the proposed algorithm. In the traditional cooperative location algorithm, because the location information of each node is broadcast and the message is not transmitted by the control, the convergence rate of the location estimation of each node is slow or even convergent, which is proposed in the traditional cooperative positioning algorithm. By controlling the state of the node and the message propagation, the algorithm forms an orderly flow state, which makes the message always flow from the high confidence node to the low confidence node. Therefore, the energy management is effectively realized and the error propagation is suppressed.
【学位授予单位】:北京邮电大学
【学位级别】:硕士
【学位授予年份】:2015
【分类号】:TN925

【共引文献】

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相关硕士学位论文 前2条

1 陈明;基于混合部件模型的姿态估计方法研究[D];南京航空航天大学;2014年

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