英文翻譯.GPS.

1、畢業(yè)設(shè)計（論文）外文翻譯 題 目 學(xué) 院 專 業(yè) 學(xué) 生 學(xué) 號 指導(dǎo)教師 畢業(yè)論文·外文翻譯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©

2、; Springer-Verlag 2006Abstract Global 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 measurem

3、ent.On the other hand, accelerometers 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 enhan

4、ce the measurement accuracy of total (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 thre

5、e GPS receivers, one accelerometer, 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 a

6、nd dynamic displacements. These results 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

7、 structural deformation monitoring 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

8、tall building or a long cable-supported 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 abl

9、e to extract acceleration responses 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

10、 will drift over time due to unknown 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 respo

11、nses of a structure.After the Soviet 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, shou

12、ld also can measure the location 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 recei

13、ver. To achieve this purpose, the 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 o

14、f light is (because of the atmosphere, 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 cod

15、e) launch navigation message.GPS 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 cyc

16、le code spacing 0.1 microseconds, 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 s

17、atellite signal - | A useful - cn: 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; Rep

18、eat every 30 seconds, updated every 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

19、with their own clock can be learned 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

20、coordinate system - the location 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 can't always be synchronized, so

21、in addition to the user's 3 d - | A useful - 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 receiver's

22、 position, can receive at least four of the satellite 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 coordina

23、te point (measured by other methods), to correct 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 navi

24、gation services, and the elevation accuracy obviously 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

25、System (GPS) is now actively applied to measure 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 m

26、any factors such as satellite coverage,atmospheric 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

27、concerning structural dynamic displacement monitoring, 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

28、considering a 10 cycles per second sinusoidal wave 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 displa

29、cement measurements, calibration tests using a motion 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 sit

30、e is changed.Clearly, the measurement performance 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 resp

31、onse of large civil engineering structures. The 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

32、 accelerometer were filtered by a conventional filter 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.

33、The velocity signals from the accelerometer were 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 displacemen

34、t of a structure. Their results revealed that, with 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 stati

35、c and quasi-static displacement components from 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

36、to accurately measure with accelerometers. Furthermore, 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 resp

37、onse of large civil engineering structures.In this 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 re

38、sponse of a large civil engineering structure under 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 tim

39、e-varying mean wind speed from typhoon induced non-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-correlat

40、ion between reference and primary time series (Ge 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 integra

41、ted data processing techniques, a series of motion 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 perf

42、ormed at the test site to estimate the amount of 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

43、 but on the next sidereal day. The proposed data 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

44、original motions generated by the motion simulation 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

45、 et al. 1998):x(t) =cj(t) + r(t)NeWhere Ne is the 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 conce

46、pt of this decomposition is based on the direct 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 separ

47、ate the waves of different periods into different 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 c

48、omponents greater than the cutoff frequency.An adaptive 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 referenc

49、e measurement r(k) of noise signal n_(k). In order 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; (

50、2) the noise n_(k) in the reference measurement 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 a

51、t our test site (Chan et al. 2005), the adaptive 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 s

52、ignal measured by GPS with a stationary antenna 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 refere

53、nce measurement is uncorrelated with the structural 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 r

54、esponse from the GPS-measured data by using high-frequency dynamic displacement response from the accelerometer as a reference measurement.GPS數(shù)據(jù)的處理方法在結(jié)構(gòu)變形監(jiān)測的應(yīng)用W. S. Chan · Y. L. Xu · X. L. Ding · W. J. DaiReceived: 9 November 2005 / Accepted: 11 August 2006 / Published online: 7 Septe

55、mber 2006 摘要：全球定位系統(tǒng)(GPS)現(xiàn)在正積極應(yīng)用靜態(tài)和動態(tài)位移法在有風(fēng)的情況下對大型土木工程結(jié)構(gòu)進行監(jiān)測。然而,多路徑效應(yīng)和低采樣頻率的精度影響GPS位移測量。另一方面,加速度計靜態(tài)和低頻不能有效的措施結(jié)構(gòu)反應(yīng),但可以精確測量高頻結(jié)構(gòu)的反應(yīng)。因此,本文僅探討GPS與測量結(jié)合的可能性，信號提高對測量準確度的(靜態(tài)加上動態(tài))一個結(jié)構(gòu)的位移響應(yīng)。集成數(shù)據(jù)處理技巧,利用兩個經(jīng)驗?zāi)Ｊ椒纸?EMD)和自適應(yīng)濾波的方法。一系列的運動模擬臺試驗，然后根據(jù)站點使用三個GPS接收器,一個加速度、“桌子”和一個運動仿真可以模擬各種類型的運動定義為輸入，在波時間歷程一個預(yù)先定義的靜態(tài)的位置。該數(shù)據(jù)處理技

56、術(shù)應(yīng)用：記錄的GPS和加速度計數(shù)據(jù)，發(fā)現(xiàn)兩者都有靜態(tài)和動態(tài)位移。這些結(jié)果通過實測位移運動產(chǎn)生運動仿真的“桌子”。比較結(jié)果表明,該技術(shù)能顯著提高測量準確度。關(guān)鍵詞：GPS變形監(jiān)測、結(jié)構(gòu)、加速度計；綜合數(shù)據(jù)處理、靜態(tài)和動態(tài)位移法、EDM的經(jīng)典分解模式；自適應(yīng)濾波器。1、介紹：結(jié)構(gòu)位移是評估一個大型土木工程結(jié)構(gòu)的完整和安全關(guān)鍵參數(shù)。如高樓大廈或一個長橋在風(fēng)力影響下的情況。風(fēng)影響這樣一個大型結(jié)構(gòu)主要是由加速度計監(jiān)測,然后采用動態(tài)位移響應(yīng)表達式，用雙重整合的測量加速度響應(yīng)。一個加速度計是可以做到提取加速度響應(yīng)，自然頻率達1000赫茲,因為它具有極高的取樣頻率。(羅伯茨丁曉萍.2004)然而,加速度計不敏

57、感加速度的變化。速度和位移集成加速度隨著時間的推移,信號將漂移，由于未知集成常量,以及一個高通濾波器，用于處理中引入低頻漂移一體化進程。因此,認識到一個加速度計是無法測量靜態(tài)和低頻動態(tài)位移。 當(dāng)蘇聯(lián)發(fā)射了第一顆人造衛(wèi)星后，美國約翰·霍布斯金大學(xué)應(yīng)用物理實驗室的研究人員提出既然可以已知觀測站的位置知道衛(wèi)星位置，那么如果已知衛(wèi)星位置，應(yīng)該也能測量出接收者的所在位置。這是導(dǎo)航衛(wèi)星的基本設(shè)想。GPS導(dǎo)航系統(tǒng)的基本原理是測量出已知位置的衛(wèi)星到用戶接收機之間的距離，然后綜合多顆衛(wèi)星的數(shù)據(jù)就可知道接收機的具體位置。要達到這一目的，衛(wèi)星的位置可以根據(jù)星載時鐘所記錄的時間在衛(wèi)星星歷中查出。而用戶到衛(wèi)星

58、的距離則通過紀錄衛(wèi)星信號傳播到用戶所經(jīng)歷的時間，再將其乘以光速得到(由于大氣層電離層的干擾，這一距離并不是用戶與衛(wèi)星之間的真實距離，而是偽距（PR）：當(dāng)GPS衛(wèi)星正常工作時，會不斷地用1和0二進制碼元組成的偽隨機碼（簡稱偽碼）發(fā)射導(dǎo)航電文。GPS系統(tǒng)使用的偽碼一共有兩種，分別是民用的C/A碼和軍用的P(Y)碼。C/A碼頻率1.023MHz,重復(fù)周期一毫秒，碼間距1微秒，相當(dāng)于300m；P碼頻率10.23MHz，重復(fù)周期266.4天，碼間距0.1微秒，相當(dāng)于30m。而Y碼是在P碼的基礎(chǔ)上形成的，保密性能更佳。導(dǎo)航電文包括衛(wèi)星星歷、工作狀況、時鐘改正、電離層時延修正、大氣折射修正等信息。它是從衛(wèi)星

59、信號中-A|zh-cn:解調(diào)制;zh-tw:解調(diào)變-出來，以50b/s-A|zh-cn:調(diào)制;zh-tw:調(diào)變-在載頻上發(fā)射的。導(dǎo)航電文每個主幀中包含5個子幀每幀長6s。前三幀各10個字碼；每三十秒重復(fù)一次，每小時更新一次。后兩幀共15000b。導(dǎo)航電文中的內(nèi)容主要有遙測碼、轉(zhuǎn)換碼、第1、2、3數(shù)據(jù)塊，其中最重要的則為星歷數(shù)據(jù)。當(dāng)用戶接受到導(dǎo)航電文時，提取出衛(wèi)星時間并將其與自己的時鐘做對比便可得知衛(wèi)星與用戶的距離，再利用導(dǎo)航電文中的衛(wèi)星星歷數(shù)據(jù)推算出衛(wèi)星發(fā)射電文時所處位置，用戶在WGS-84-A|zh-cn:大地坐標系;zh-tw:大地坐標系-中的位置速度等信息便可得知。可見GPS導(dǎo)航系統(tǒng)衛(wèi)星部分的作用就是不斷地發(fā)射導(dǎo)航電文。然而，由于用戶接受機使用的時鐘與衛(wèi)星星載時鐘不可能總是同步，所以除了用戶的三維-A|zh-cn:坐標;zh-tw:坐標-x