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1、河北建筑工程学院毕业设计（论文）外文资料翻译 系别： 电气系 专业： 电子信息工程 班级： 电子092班 姓名： 学号： 2009315213 外文出处： Wireless.Sensor.Networks： A.Networking.Perspective 附 件：1、外文原文；2、外文资料翻译译文。指导教师评语：签字： 年 月 日1、 外文原文（复印件）8.3 RANGING TECHNIQUES FOR WIRELESS SENSOR NETWORKSThe RF location sensors operating in different environments can measur
2、e the RSS, AOA, phase of arrival (POA), TOA, and signature of the delay - power profile as location metrics to estimate the ranging distance 4,7 . The deployment environment (i.e., wireless RF channel) will constrain the accuracy and the performance of each technique. In outdoor open areas, these ra
3、nging techniques perform very well. However, as the wireless medium becomes more complex, for example, dense urban or indoor environments, the channel suffers from severe multipath propagation and heavy shadow fading conditions. This finding in turn impacts the accuracy and performance in estimating
4、 the range between a pair of nodes. For this reason, this chapter will focus its ranging and localization discussion on indoor environments. This is important because many of the WSN applications are envisioned for deployment in rough terrain and cluttered environments and understanding of the impac
5、t of the channel on the performance of ranging and localization is important. In addition, range measurements using POA and AOA in indoor and urban areas are unreliable. Therefore, we will focus our discussion on two practical techniques,TOA and RSS.These two ranging techniques, which have been used
6、 traditionally in wireless networks, have a great potential for use in WSN localization. The TOA based ranging is suitable for accurate indoor localization because it only needs a few references and no prior training. By using this technique, however, the hardware is complex and the accuracy is sens
7、itive to the multipath condition and the system bandwidth. This technique has been implemented in GPS, PinPoint, WearNet, IEEE 802.15.3, and IEEE 802.15.4 systems. The RSS based ranging, on the other hand, is simple to implement and is insensitive to the multipath condition and the bandwidth of the
8、system. In addition, it does not need any synchronization and can work with any existing wireless system that can measure the RSS. For accurate ranging, however, a high density of anchors or reference points is needed and extensive training and computationally expensive algorithms are required.The R
9、SS ranging has been used for WiFi positioning in systems, for example, Ekahau, Newbury Networks, PanGo, and Skyhook. This section first introduces TOA based ranging and the limitations imposed by the wireless channel. Then it will be compared with the RSS counterpart focusing on the performance as a
10、 function of the channel behavior. What is introduced here is important to the understanding of the underlying issues in distance estimation, which is an important fundamental building block in WSN localization.8.3.1 TOA Based Ranging In TOA based ranging, a sensor node measures the distance to anot
11、her node by estimating the signal propagation delay in free space, where radio signals travel at the constant speed of light. Figure 8.3 shows an example of TOA based ranging between two sensors. The performance of TOA based ranging depends on the availability of the direct path (DP) signal 4,14 . I
12、n its presence, for example, short distance line - of - sight (LOS) conditions, accurate estimates are feasible 14 . The challenge, however, is ranging in non - LOS (NLOS) conditions, which can be characterized as site - specific and dense multipath environments 14,22 . These environments introduce
13、several challenges. The first corrupts the TOA estimates due to the multipath components (MPCs), which are delayed and attenuated replicas of the original signal, arriving and combining at the receiver shifting the estimate. The second is the propagation delay caused by the signal traveling through
14、obstacles, which adds a positive bias to the TOA estimates. The third is the absence of the DP due to blockage, also known as undetected direct path (UDP) 14 . The bias imposed by this type of error is usually much larger than the first two and has a significant probability of occurrence due to cabi
15、nets, elevator shafts, or doors that are usually cluttering the indoor environment. In order to analyze the behavior of the TOA based ranging, it is best to resort to a popular model used to describe the wireless channel. In a typical indoor environment, the transmitted signal will be scattered and
16、the receiver node will receive replicas of the original signal with different amplitudes, phases, and delays. At the receiver, the signals from all these paths combine and this phenomenon is known as multipath. In order to understand the impact of the channel on the TOA accuracy, we resort to a mode
17、l typically used to characterize multipath arrivals. For multipath channels, the impulse respons characterizes the arrival paths, their respective amplitudes, and delays. Mathematically, it can be represented as a summation of all the arriving multipath components or ，（8.1）where Lp is the number of
18、MPCs, and , , and are amplitude, phase, and propagation delay of the kth path, respectively 7,23 . Let and denote the DP amplitude and propagation delay, respectively. The distance between the sensor node and the RP or anchor is , where v is the speed of signal propagation. In the absence of the DP,
19、 ranging can be achieved using the amplitude and propagation delay of the non - direct path (NDP) component given by and, respectively; resulting in a longer distance, where. For the receiver to identify the DP, the ratio of the strongest MPC to that of the DP given by ，（8.2）must be less than the re
20、ceiver dynamic range k and the power of the DP must be greater than the receiver sensitivity . These constraints are given by ，（8.3a）, （8.3b）where. In general, ranging and localization accuracy is constrained by the ranging error, which is defined as the difference between the estimated and the actu
21、al distance; that is, .（8.4） In an indoor environment, the node/MT will experience a varying error behavior depending on the availability of the DP and in the case of its absence on the characteristics of the DP blockage. It is possible to categorize the error based on the following ranging states 2
22、4 . In the presence of the DP, both (8.3a) and (8.3b) are met and the distance estimate is very accurate, yielding ,（8.5a）where the random bias induced by the multipath, is the bias corresponding to the propagation delay caused by NLOS conditions, and z is a zero - mean additive measurement noise. I
23、t has been shown that is indeed a function of the bandwidth and the signal to noise ratio (SNR) 14 , while bpd is dependant on the medium of the obstacles.When the node experiences sudden blockage of the DP, Eq. (8.3a) is not met and the DP is shadowed by some obstacle, burying its power under the d
24、ynamic range of the receiver. In this situation, the ranging estimate experiences a larger error compared to Eq. (8.5a) . Emphasizing that ranging is achieved through the NDP component, the estimate is then given by ,（8.6a）,（8.6b）where is a deterministic additive bias representing the nature of the
25、blockage. Unlike the multipath biases, but similar to the biases induced by the propagation delay, the dependence of on the system bandwidth and SNR has its own limitations as reported in Ref. 14 . Formally, these ranging states can be defi ned as,（8.7a）,（8.7b）Figures 8.4 and 8.5 provide sample chan
26、nel profiles of these two ranging situations 24 . The performance of TOA based ranging can be determined by the Cramer-Rao lower bound (CRLB), which has been studied extensively for existing systems. The variance of TOA estimation is bounded by the CRLB 25 ,（8.8）where T is the signal observation tim
27、e, is the SNR, is the frequency of operation, and w is the system bandwidth. In practice, TOA can be obtained by measuring the arrival time of a wide-band narrow pulse, which can be obtained either by using spread spectrum technology or directly. 8.3.1.1 Direct Spread Spectrum. One TOA estimation te
28、chnique based on the direct spread spectrum (DSS) wideband signal has been used in GPS and other ranging systems for many years. In such a system, a signal coded by a known pseudorandom (PN) sequence is transmitted and a receiver cross - correlates the received signal with a locally generated PN seq
29、uence using a sliding correlator or a matched filter. The distance between the transmitter and the receiver is determined from the arrival time of the first correlation peak. Because of the processing gain of the correlation at the receiver, DSS ranging systems perform much better than competing sys
30、tems in suppressing interference from other radio systems operating in the same frequency band. In these band - limited systems, super- resolution techniques for TOA estimation have been applied successfully. Results have shown that these high - resolution algorithms can provide improved accuracy 25
31、 . 8.3.1.2 Ultra - Wideband Ranging.A promising alternative to DSS systems is ultra - wideband (UWB) ranging 26 . According to Eq. (8.8) , it is clear that in multipath propagation environments, the performance of TOA estimation is inversely related to the system bandwidth. Increasing the system ban
32、dwidth (i.e., narrower time - domain pulse) results in higher time resolution and thus better ranging accuracy. As a result, these systems have attracted considerable attention in recent years 16,22,26 . For UWB applications, the FCC regulation allocated an unlicensed flat frequency band 3.1 10.6 GH
33、z for which there are two proposals: direct sequence (DS) UWB and multiband orthogonal frequency division multiplexing (MB OFDM). The former is pulse based, which utilizes large bandwidths, for example, 3 GHz, while the latter occupies a bandwidth of 528 MHz. The accuracy of these systems can be eva
34、luated by examining their behaviors in the multipath channel. Sample measurements in indoor office environments are provided in Fig. 8.6 a for 500 - MHz systems, resembling the MB OFDM channels and Fig. 8.6 b for 3 - GHz bandwidth, resembling the wider channel of the DS UWB.The expected TOA between
35、the transmitter and the receiver is 40.5 ns and the estimated arrival with 500 - MHz and 3 - GHz bands are 45.5 and 40.7 ns, respectively. The 5 - and 0.2 - ns errors in TOA estimation results in 1.67 - m and 7 - cm errors, respectively, clearly illustrating the impact of a higher system bandwidth o
36、n accuracy. One important observation from these measurement results is that higher bandwidths improve time - domain resolution, which resolves the pulse into respective components, resulting in improved accuracy. The trade - off, however, is that higher resolution implies lower energy per MPC, whic
37、h means a higher probability of DP blockage. This means that the ranging coverage of 500 - MHz systems is larger than that of the 3 - GHz counterpart. Although UWB can reduce multipath significantly, combating the excess propagation delay and UDP becomes challenging because the amount of delay and t
38、he type of blocking material are not known in advance and cannot be mitigated through large bandwidths alone. Understanding of the error behavior in light of these major error contributors is necessary to enable effective UWB ranging. Specifi cally, WSN localization algorithms must analyze the chann
39、el statistics and attempt to identify and mitigate DP blockage 27,28 . 2、外文资料翻译译文8.3无线传感器网络的测距技术射频位置传感器在不同的环境中运行可测量RSS，AOA，阶段的到来（POA），TOA，和作为位置的度量估计距离延迟功率谱 4,7。这种部署环境（例如，无线射频信道）将限制精度和每种技术的性能。在户外空旷地区，这些测距技术执行得很好。然而，随着无线介质而变得更加复杂，例如，密集的城市或室内环境中，信道存在严重的多径传播和严重的阴影衰落环境。这一发现反过来说明了在一对节点之间的距离估计对精度和性能的影响。为此，
40、本章将重点讨论在室内环境中的测距和定位。这点很重要，因为许多WSN应用程序设想在崎岖的地形和杂乱的环境中部署传感器，因此，对测距和定位性能的信道的影响的理解是很重要的。此外，采用POA和AOA在室内和城市地区进行测距是不可靠的。因此，我们将重点讨论两个实用技术，TOA和RSS。这两种测距技术，已经有在无线网络中使用的传统，它们对于在无线传感器网络定位有着很大的潜力。TOA测距适合于精确的室内定位是因为它只需要很少的文献并且不需要事先训练。但是，通过使用这种技术，硬件会变得复杂、精度的多径条件和系统带宽会敏感。这种技术已经被实施在GPS，PinPoint，wearnet，IEEE 802.15.
41、3，和IEEE 802.15.4系统应用上。另一方面，RSS测量实现简单，对多径条件和系统的带宽不敏感。此外，它不需要任何同步，可以与任何现有的无线系统协同工作，可以测量RSS。然而，对于准确的测量，锚或参考点的高密度是必要的，并且广泛的培训和昂贵的算法也是必需的。RSS测距已被用于在WiFi定位系统中，比如Ekahau，Newbury Networks，Pango和Skyhook。本章首先介绍了基于测距的TOA和所施加在无线通道的局限性。然后它与专注于信道行为函数的RSS的性能进行比较。这里所介绍的在测距基本问题上的认识很重要，这是研究无线传感器网络定位的重要基础。8.3.1 TOA测距在T
42、OA测距中，传感器节点到另一个节点间距离的测量是通过自由空间中的信号传播时延来估计的，信号传播在无线信号以光速为恒定速度。图8.3展示了两个节点间的TOA测距。 TOA测距的性能取决于直接路径的可用性（DP）信号 14 。例如，在DP信号中，短距离的线的视线（LOS）的条件下，准确的估计是可行的 14 。然而，我们面临的挑战是，在非LOS（NLOS）表现为网站的特异性和密集多径环境的条件下。这些环境提出了一些挑战。图8.3 传感器间的TOA测距第一个由于多径分量（MPC）所引起的腐化的TOA估计，这是原始信号延迟和衰减的复制品，到达和合并接收器的移动估计。第二个是由信号穿过障碍物引起的传播延迟
43、，这增加了一个正向偏置的TOA估计。第三是由于堵塞的DP的缺失，也被称为未发现的直接路径（UDP） 14 。这种类型的错误引起的偏压通常是比前两大得多，同时由于橱柜，电梯，或通常在室内门附近，也会引起更大出错的概率。为了分析基于TOA测距的行为,最好采取一个受欢迎的模型用来描述无线信道。在一个典型的室内环境中,传输信号将被分散，接收者节点将收到与原始信号不同振幅、阶段和延误的副本信号。在接收机,信号从所有这些路径结合,这种现象称为多径。为了了解影响精度的渠道,我们常常借助于一个用于描述多路径到达的模型。这个模型描述了多路径通道,脉冲响应特征路径,到达各自的振幅和延误。在数学上,它可以表示为一个
44、求和的多路径组件或到达，（8.1）其中，Lp代表MPCs的数量，分别是振幅，相位以及传播延迟的路径。让和分别表示DP振幅和传播延迟。传感器节点之间的距离和RP或锚是,v是信号传播的速度。在DP的缺席中,测距可以通过,分别由和给出的使用振幅和传播延迟的非直接的路径(NDP)组件来达到;这导致了长的距离,其中。为使接收机识别DP,最大的MPC与DP信号的比例如下，（8.2）它必须低于接收机动态范围k的能力并且DP必须大于接收机灵敏度。这些约束条件如下，（8.3a）,（8.3b）其中。待添加的隐藏文字内容2一般来说,测距和定位精度受到测距误差的限制,其被定义为估计和实际的距离的差异;那就是（8.4）
45、在室内环境中,节点/MT将会体验一种取决于可用性的DP不同的错误行为和具有DP堵塞特征对于的缺席。它可能是基于以下测距状态24 的错误分类。在DP下, (8.3a)和(8.3 b)得到满足和距离的估计是非常准确的。，（8.5a）其中，是在随机偏差引起的多路径, 是由NLOS引起的传播延时的偏置, z是一个零,意味着添加剂测量噪声。它已被证明的确是一个函数的带宽和信号噪声比(信噪比)14,而bpd是依赖于介质的障碍。当节点经历突然DP,Eq阻塞,(8.3 a)不满足和DP被一些障碍所阻挡,它将它的能量放在在动态范围的接收机。在这种情况下,同Eq(8.5 a)相比，测距估计将会有一个更大的误差范围
46、。其中值得强调的是，测距是通过NDP组件来实现的,然后由以下给出图8.4 宽带在200MHz范围的TOA估计，（8.6a），（8.6b）是一个堵塞性质的确定性偏置。与多路径偏置不同,但类似于由于传播延迟引起的偏置，取决于系统带宽的，并且信噪比都有自己的局限性上报信息14。一般来说，这些测距状态可以被定义为，（8.7a），（8.7b）图8.4和8.5提供样品通道配置文件的这两个测距情况24。基于TOA测距的性能范围可以由最大下界(CRLB)确定,它已广泛地用于研究现有系统。TOA测距中的估计由CRLB25确定，（8.8）图8.5 在宽带为200MHz范围内的NDP的TOA测距其中T是信号的观测时
47、间, 是信噪比、是运作的频率,w是系统带宽。在实践中,可以通过测量获得长远的到达时间一个宽带窄脉冲来获得TOA,也可以通过使用或直接扩频技术。8.3.1.1直接扩频一种基于直接扩频(DSS)宽带信号的TOA测距技术已经应用于GPS和其他测距系统许多年了。在这样一个系统,一个由已知的伪随机(PN)序列编码的信号是用来传播的和一个交叉关联的接收器接收信号的与本地PN序列生成使用滑动相关器或一个匹配滤波器。发射机和接收机之间的距离是由到达时间的第一个相关峰确定。因为处理增益的相关性在接收机、DSS测距系统在同一频带的性能远远好于竞争的系统抑制干扰其他无线电系统操作。在这些有限的系统中,超级分辨率技术已经成功应用于TOA测距。结果表明,这些高分辨率算法可以提供改善的准确性25。8.3.1.2超宽频带范围。一个有前途的可以用来替代DSS系统是超宽带(UWB)测距26系统。很明显,根据Eq. (8.8)，在多径传播环境,TOA测距的性能估计是逆相关系统带宽。通过增加系统带宽(即更窄的时间-域脉冲)导致更高的时间分辨率,从而有更好的测距精度。因此, 近年来这些系统已经引起了相当大的关注。对于超宽频应用,FCC规定分配一个无照平频带3.1 - 10.6 GHz,有两个建议:直接序列(DS)超宽频和
