英文翻译.GPS.

1、毕业设计（论文）外文翻译 题 目 学 院 专 业 学 生 学 号 指导教师 毕业论文外文翻译An integrated GPSaccelerometer data processing techniquefor structural deformation monitoringW. S. Chan Y. L. Xu X. L. Ding W. J. DaiReceived: 9 November 2005 / Accepted: 11 August 2006 / Published online: 7 September 2006 Springer-Verlag 2006Abstract Gl

2、obal Positioning System (GPS) is being actively applied tomeasure static and dynamic displacement responses of large civil engineering structures under winds. However, multipath effects and low sampling frequencies affect the accuracy of GPS for displacement measurement.On the other hand, accelerome

3、ters cannot reliably measure static and low-frequency structural responses, but can accurately measure high frequency structural responses. Therefore, this paper explores the possibility of integrating GPS-measured signals with accelerometer-measured signals to enhance the measurement accuracy of to

4、tal (static plus dynamic) displacement response of a structure. Integrated data processing techniques using both empirical mode decomposition (EMD) and an adaptive filter are presented. A series of motion simulation table tests are then performed at a site using three GPS receivers, one acceleromete

5、r, and one motion simulation table that can simulate various types of motion defined by input wave time histories around a pre-defined static position.The proposed data processing techniques are applied to the recorded GPS and accelerometer data to find both static and dynamic displacements. These r

6、esults are compared with the actual displacement motions generated by the motion simulation table. The comparative results demonstrate that the proposed technique can significantly enhance the measurement accuracy of the total displacement of a structure.Keywords：GPS structural deformation monitorin

7、g Accelerometer Integrated data processing Static and dynamic displacements Empirical mode decomposition (EMD) Adaptive filter1 IntroductionStructural displacement is a key parameter to assess the integrity and safety of a large civil engineering structure,such as a tall building or a long cable-sup

8、ported bridge, under winds. Wind-induced responses of such a large structure are mainly monitored by accelerometers,and dynamic displacement responses are then obtained often through a double integration of the measured acceleration responses. An accelerometer is able to extract acceleration respons

9、es of a structure with natural frequency up to 1,000 Hz because of the high sampling frequency (Roberts et al. 2004).However, an accelerometer is insensitive to acceleration changes. The velocity and displacement integrated from the uncompensated acceleration signals will drift over time due to unkn

10、own integration constants, and a high-pass filter should be used to cope with low-frequency drift introduced during the integration process. It is therefore recognized that an accelerometer is incapable of measuring static and low-frequency dynamic displacement responses of a structure.After the Sov

11、iet union launched the first man-made satellite, the United States John Hobbes Jin Daxue applied physics laboratory researchers put forward now that can be known to the location of the observatory know satellite position, so when the satellite position is known, should also can measure the location

12、of the receiver. This is the basic idea of navigation satellite.The basic principle of GPS navigation system is to measure the known position of satellite to the distance between the user receiver, and then integrated satellite data can know the location of the receiver. To achieve this purpose, the

13、 position of the satellite can be recorded by spaceborne clock time to find out in the satellite ephemeris. While the user is the distance to the satellite by record time experienced by the satellite signal transmission to the user, then its multiplied by the speed of light is (because of the atmosp

14、here, the ionosphere disturbance, the distance is not the real distance between the user and satellite, but the pseudorange (PR) : when the normal work of the GPS satellites, will continue to use the binary 1 s and 0 s element consisting of pseudo-random code (pn code) launch navigation message.GPS

15、system using the pseudo code of A total of two kinds, respectively is civil C/A code and military P (Y) code. C/A code frequency 1.023 MHz, repeat cycle A millisecond, code spacing 1 millisecond, equivalent to 300 m; P code frequency 10.23 MHz, 266.4 days, repeat cycle code spacing 0.1 microseconds,

16、 equivalent to 30 m. And Y code is on the basis of P code, secrecy performance is better. Navigation message includes satellite ephemeris, working conditions, and clock correction, ionospheric delay correction, correction of atmospheric refraction, etc. It from the satellite signal - | A useful - cn

17、: demodulation; Useful - tw: demodulation -, 50 b/s - | A useful - cn: modulation; Useful - tw: modulation - launched on the carrier frequency. Navigation message contains five child frame each main frame of the long frame 6 s.The first three frames each 10 word; Repeat every 30 seconds, updated eve

18、ry hour. Two frames after 15000 b. The contents of the navigation message includes telemetry code, transform code, 1, 2, 3 data blocks, one of the most important is the ephemeris data. When users receive the navigation message, extract the satellite time and compare with their own clock can be learn

19、ed that the distance between the satellite and the user, using the navigation message of satellite ephemeris data show the location at the time of the satellite launch cables, users in the WGS - 84 - | A useful - cn: geodetic coordinate system; Useful - tw: geodetic coordinate system - the location

20、information such as speed can be learned.Visible GPS satellite navigation system part of the role of the navigation message is continuously launch. However, due to the user receiver using the clock with satellite spaceborne clock cant always be synchronized, so in addition to the users 3 d - | A use

21、ful - cn: coordinates; Useful - tw: coordinates - x, y, z, will also introduce a t is the time difference between the satellite and receiver as unknowns, and then use four equations to solve the four unknown number. So if you want to know the receivers position, can receive at least four of the sate

22、llite signal.In order to promote the accuracy of the civilian, the scientific development of another technology, called Differential global positioning system (Differential GPS), hereinafter referred to as DGPS. I.e. using near known reference coordinate point (measured by other methods), to correct

23、 the error of GPS. Then add the instant (real time) error value to itself coordinate operation consideration, can obtain more accurate values.GPS navigation with 2 d and 3 d navigation points, when the satellite signal is not enough to provide 3 d navigation services, and the elevation accuracy obvi

24、ously not enough, sometimes up to 10 times the error 7. But the improvement in terms of latitude and longitude error is very small. Satellite positioning receiver in high-rise buildings is taking longer to catch the satellite signal.Global Positioning System (GPS) is now actively applied to measure

25、static and dynamic displacement responses of a large civil engineering structure under winds due to its global coverage and continuous operation under all meteorological conditions. However, the accuracy of GPS for displacement measurement depends on many factors such as satellite coverage,atmospher

26、ic effects, multipath, and the GPS data processing method. The Nyquist frequency of a modern dual-frequency GPS receiver of 20 Hz sampling rate is 10 Hz, which is good enough to detect natural frequencies of a civil engineering structure.However, when concerning structural dynamic displacement monit

27、oring, the accuracy of quantization of the structural dynamic displacement is important. This requires the sampling rate to be much higher than the frequency components of interest in the continuous signal of structural deformation. For instance, when considering a 10 cycles per second sinusoidal wa

28、ve being sampled at 20 samples per second, only 2 samples can be obtained for each sine wave cycle, which is definitelynot enough to reconstruct this sine wave.In order to assess the best performance of GPS (Leica GX1230 GPS receiver) in dynamic displacement measurements, calibration tests using a m

29、otion simulation table were carried out in an open area in Hong Kong (Chan et al. 2005). The results showed that the GPS could measure dynamic displacements properly if the motion frequency was1Hz. This result may change slightly if the measurement site is changed.Clearly, the measurement performanc

30、e of GPS is complementary to that of an accelerometer. This paper thus explores the possibility of integrating GPS-measured signals with accelerometer-measured signals to enhance the measurement accuracy of total (static plus dynamic) displacement response of large civil engineering structures. The

31、concept of integrating signals from GPS and accelerometer for structural deformation monitoring was presented by Roberts et al. (2004). and Liet al. (2005).In the integration algorithms proposed by Roberts et al. (2004), the measurement signals from an accelerometer were filtered by a conventional f

32、ilter to remove high-frequency noise, and the measurement signals from a GPS were filtered using an adaptive filter to reduce multipath. The single integration of acceleration signals from the accelerometer was then performed to find velocity signals. The velocity signals from the accelerometer were

33、 reset using the velocity constant calculated from the GPS data. These calibrated velocity signals were integrated to obtain displacement signals, and the displacement signals were finally reset with the GPS coordinates to obtain the actual displacement of a structure. Their results revealed that, w

34、ith the proposed integration scheme, millimeter-accurate positioning could be maintained within several tens of seconds. The displacement obtained by the earlier method was actually dynamic displacement only. Li et al. (2005) further isolated the static and quasi-static displacement components from

35、the GPS data and added them to the dynamic displacement to obtain the total displacement of a structure under winds.Large civil engineering structures are typically very slender and accordingly their low-frequency responses to winds are very difficult to accurately measure with accelerometers. Furth

36、ermore, besides wind-induced dynamic displacement, wind-induced static displacement of a structure measured by GPS is likely to be contaminated by multipath. Hence, it is difficult to apply the existing integration scheme to the total displacement response of large civil engineering structures.In th

37、is regard, this paper presents different integrated GPS/accelerometer data processing techniques, based on the empirical mode decomposition (EMD) and an adaptive filter, to enhance the measurement accuracy of total (static plus dynamic) displacement response of a large civil engineering structure un

38、der winds. The EMD developed by Huang et al. (1998) is a data-processing tool that can decompose any complicated data set into a small number of intrinsic mode functions (IMF) and afinal residual.The EMD method has been successfully used to extract time-varying mean wind speed from typhoon induced n

39、on-stationary wind records for long cable supported bridges (Xu and Chen 2004) and tall buildings (Chen and Xu 2004). The adaptive filter is a signal decomposer that extracts information of interest from the contaminated signal using the cross-correlation between reference and primary time series (G

40、e et al. 2000, Roberts et al. 2002). In recognition that the multipath is repeatable on every sidereal day, Ge et al. (2000) successfully applied adaptive filtering to GPS data to reduce the multipath.To assess the effectiveness of the proposed integrated data processing techniques, a series of moti

41、on simulation table tests are performed at a site using three GPS receivers, one accelerometer, and one motion simulation table. Static tests, with the GPS antenna installed on the motion simulation table that is in stationary condition, are first performed at the test site to estimate the amount of

42、 multipath. The motion simulation table is then used to generate various types of dynamic displacement response around a pre-defined static position.The GPS and accelerometer measurement data are recorded within the same time period as the static tests but on the next sidereal day. The proposed data

43、 processing techniques are then applied to the recorded GPS and accelerometer data to find both static and dynamic displacements. The effectiveness of the integrated methods is finally assessed through the comparison of the integrated results with the original motions generated by the motion simulat

44、ion table.2 Empirical Mode Decomposition and Adaptive FilterThe EMD used in this study is to decompose GPS measured structural displacement response time history x(t) into a number of IMF components and a final residual through a sifting process (Huang et al. 1998):x(t) =cj(t) + r(t)NeWhere Ne is th

45、e number of IMF components; and r(t)Ne is the final residual. This final residual of the structural displacement response time history, measured by GPS, is a monotonic function that can be defined as the mean displacement of the structure. As the concept of this decomposition is based on the direct

46、extraction of the energy associated with various intrinsic time scales of the time history itself, mode mixing during the sifting process would be possible. A criterion, termed the intermittency check, was thus suggested by Huang et al. (1999) to separate the waves of different periods into differen

47、t modes based on the period length. In this study, the EMD with an intermittency check and a cutoff frequency _c are used to process acceleration time history measured by an accelerometer so as to obtain a high-frequency dynamic response of frequency components greater than the cutoff frequency.An a

48、daptive filter, used as a signal decomposer, operates on the information from two measurement inputs with the same length: (1) a primary measurement p(k) that contains the desired signal of interest s(k) contaminated by noise n(k), and (2) the reference measurement r(k) of noise signal n_(k). In ord

49、er to extract the desired signal s(k) from the polluted primary measurement p(k) by using the adaptive filter, two conditions have to be satisfied: (1) the desired signal s(k) and noise n(k) in thePrimary measurement are uncorrelated with each other; (2) the noise n_(k) in the reference measurement

50、is uncorrelated with the desired signal s(k) but correlated in some way with the noise component n(k) of the primary signal. As the multipath measured by the moving receiver is similar to that measured by the stationary receiver between sidereal days at our test site (Chan et al. 2005), the adaptive

51、 filter can actually be applied to mitigate the multipath. The displacement measured by the GPS with a moving antenna is taken as the primary measurement p(k), which includes the desired structural displacement s(k) and the multipath effect n(k). The signal measured by GPS with a stationary antenna

52、during the same timeperiod as the dynamic measurement, but on the next or previous sidereal day, is taken as the reference measurement r(k) = n_(k).By assuming that the desired structural displacement is uncorrelated with the multipath while the reference measurement is uncorrelated with the structu

53、ral displacement, but correlated in some way with the multipath effect, the adaptive filter can thus be applied in this study. Apart from the multipath mitigation, this study also uses the adaptive filter to extract low-frequency dynamic displacement response from the GPS-measured data by using high

54、-frequency dynamic displacement response from the accelerometer as a reference measurement.GPS数据的处理方法在结构变形监测的应用W. S. Chan Y. L. Xu X. L. Ding W. J. DaiReceived: 9 November 2005 / Accepted: 11 August 2006 / Published online: 7 September 2006 摘要：全球定位系统(GPS)现在正积极应用静态和动态位移法在有风的情况下对大型土木工程结构进行监测。然而,多路径效应和

55、低采样频率的精度影响GPS位移测量。另一方面,加速度计静态和低频不能有效的措施结构反应,但可以精确测量高频结构的反应。因此,本文仅探讨GPS与测量结合的可能性，信号提高对测量准确度的(静态加上动态)一个结构的位移响应。集成数据处理技巧,利用两个经验模式分解(EMD)和自适应滤波的方法。一系列的运动模拟台试验，然后根据站点使用三个GPS接收器,一个加速度、“桌子”和一个运动仿真可以模拟各种类型的运动定义为输入，在波时间历程一个预先定义的静态的位置。该数据处理技术应用：记录的GPS和加速度计数据，发现两者都有静态和动态位移。这些结果通过实测位移运动产生运动仿真的“桌子”。比较结果表明,该技术能显著

56、提高测量准确度。关键词：GPS变形监测、结构、加速度计；综合数据处理、静态和动态位移法、EDM的经典分解模式；自适应滤波器。1、介绍：结构位移是评估一个大型土木工程结构的完整和安全关键参数。如高楼大厦或一个长桥在风力影响下的情况。风影响这样一个大型结构主要是由加速度计监测,然后采用动态位移响应表达式，用双重整合的测量加速度响应。一个加速度计是可以做到提取加速度响应，自然频率达1000赫兹,因为它具有极高的取样频率。(罗伯茨丁晓萍.2004)然而,加速度计不敏感加速度的变化。速度和位移集成加速度随着时间的推移,信号将漂移，由于未知集成常量,以及一个高通滤波器，用于处理中引入低频漂移一体化进程。因

57、此,认识到一个加速度计是无法测量静态和低频动态位移。 当苏联发射了第一颗人造卫星后，美国约翰霍布斯金大学应用物理实验室的研究人员提出既然可以已知观测站的位置知道卫星位置，那么如果已知卫星位置，应该也能测量出接收者的所在位置。这是导航卫星的基本设想。GPS导航系统的基本原理是测量出已知位置的卫星到用户接收机之间的距离，然后综合多颗卫星的数据就可知道接收机的具体位置。要达到这一目的，卫星的位置可以根据星载时钟所记录的时间在卫星星历中查出。而用户到卫星的距离则通过纪录卫星信号传播到用户所经历的时间，再将其乘以光速得到(由于大气层电离层的干扰，这一距离并不是用户与卫星之间的真实距离，而是伪距（PR）：

58、当GPS卫星正常工作时，会不断地用1和0二进制码元组成的伪随机码（简称伪码）发射导航电文。GPS系统使用的伪码一共有两种，分别是民用的C/A码和军用的P(Y)码。C/A码频率1.023MHz,重复周期一毫秒，码间距1微秒，相当于300m；P码频率10.23MHz，重复周期266.4天，码间距0.1微秒，相当于30m。而Y码是在P码的基础上形成的，保密性能更佳。导航电文包括卫星星历、工作状况、时钟改正、电离层时延修正、大气折射修正等信息。它是从卫星信号中-A|zh-cn:解调制;zh-tw:解调变-出来，以50b/s-A|zh-cn:调制;zh-tw:调变-在载频上发射的。导航电文每个主帧中包含

59、5个子帧每帧长6s。前三帧各10个字码；每三十秒重复一次，每小时更新一次。后两帧共15000b。导航电文中的内容主要有遥测码、转换码、第1、2、3数据块，其中最重要的则为星历数据。当用户接受到导航电文时，提取出卫星时间并将其与自己的时钟做对比便可得知卫星与用户的距离，再利用导航电文中的卫星星历数据推算出卫星发射电文时所处位置，用户在WGS-84-A|zh-cn:大地坐标系;zh-tw:大地坐标系-中的位置速度等信息便可得知。可见GPS导航系统卫星部分的作用就是不断地发射导航电文。然而，由于用户接受机使用的时钟与卫星星载时钟不可能总是同步，所以除了用户的三维-A|zh-cn:坐标;zh-tw:坐标-x、y、z外，还要