Dome A is the highest ice feature in Antarctica, at over 4000 m a.s.l., and overlies the Gamburtsev mountains. It is believed that deep ice-core drilling in this area may reveal the oldest ice in Antarctica, providing an unparalleled paleoclimate record in excess of 1 Ma, and perhaps going back as far as 1.2 Ma (Xiao and others, 2008). However, little is known about this area because its height and distance from the coast and scientific stations makes access difficult.Surface elevation information for the Dome A area is available only from the RADARSAT-1 Antarctic Mapping Project (RAMP) digital elevation model (DEM) compiled from altimeter data (Liu and others, 1999) and from data covering a small area of 64 km 2 centered on the observed summit point (80822 0 01.6 00 S, 77822 0 22.9 00 E, 4092.75 m a.s.l.) (Zhang and others, 2007). This small area was surveyed using realtime kinematic (RTK) GPS in early 2005, and 480 global positioning system (GPS) points were used to build the topography. The results show that the lowest surface height within the grid is 4090.20 m, giving an elevation range of 2.7 m (surface slope < 0.08%) over the entire 64 km 2 . Groundbased ice-penetrating radar (GPR) measurements were also made at that time. The main purpose of the fieldwork was to aid future selection of the best site for deep ice-core drilling in the region. However, the survey and GPR results indicated that a larger area needed to be studied before the site selection could be finalized. For the 2007/08 Dome A traverse, therefore, the primary task was to increase the survey area.We present measurements of surface topography of the summit area of Dome A, based on post-processing of differential GPS data. Fast-static differential GPS is a useful tool in measuring surface topography in the Antarctic interior, because it allows high-precision measurements to be made relatively quickly with minimal logistical support. The post-processing fast-static differential technique was chosen, as the distance maximum (14 km) between the rover and the base station exceeds the communication limit of the radio of the GPS system.
KEY WORDS: Time Synchronization, GPS Common-View, GPSABSTRACT:In recent years, with the development of satellite orbit and clock parameters accurately determining technology and the popularity of geodetic GPS receivers, Common-View (CV) which proposed in 1980 by Allan has gained widespread application and achieved higher accuracy time synchronization results. GPS Common View (GPS CV) is the technology that based on multi-channel geodetic GPS receivers located in different place and under the same common-view schedule to receiving same GPS satellite signal at the same time,and then calculating the time difference between respective local receiver time and GPST by weighted theory, we will obtain the difference between above local time of receivers that installed in different station with external atomic clock。 Multi-channel geodetic GPS receivers have significant advantages such as higher stability、higher accuracy and more common-view satellites in long baseline time synchronization application over the single-channel geodetic GPS receivers. At present, receiver hardware delay and surrounding environment influence are main error factors that affect the accuracy of GPS common-view result. But most error factors will be suppressed by observation data smoothing and using of observation data from different satellites in multi-channel geodetic GPS receiver. After the SA(Selective Availability)cancellation, Using a combination of precise satellite ephemeris ,ionospheric-free dual-frequency P-code observations and accurately measuring of receiver hardware delay, we can achieve time synchronization result on the order of nanoseconds (ns). In this paper, 6 days observation data of two IGS core stations with external atomic clock (PTB, USNO distance of two stations about 6000 km) were used to verify the GPS common-view theory. Through GPS observation data analysis, there are at least 2-4 common-view satellites and 5 satellites in a few tracking periods between two stations when the elevation angle is 15 °,even there will be at least 2 common-view satellites for each tracking period when the elevation angle is 30°. Data processing used precise GPS satellite ephemeris, double-frequency P-code combination observations without ionosphere effects and the correction of the Black troposphere Delay Model. the weighted average of all common-viewed GPS satellites in the same tracking period is taken by weighting the root-mean-square error of each satellite, finally a time comparison data between two stations is obtained, and then the time synchronization result between the two stations (PTB and USNO) is obtained. It can be seen from the analysis of time synchronization result that the root mean square error of REFSV (the difference between the local frequency standard at the mid-point of the actual tracking length and the tracked satellite time in unit of 0.1 ns) shows a linear change within one day, However the jump occurs when jumping over the day which is mainly caused by satellites position being changed due to the interpolation ...
Abstract. Time series analysis uses constant amplitude models to estimate seasonal changes, while the actual seasonal changes of station coordinates have varying degrees of modulation. The difference between the real modulation amplitude and the estimated constant amplitude enters the residual sequence. We analysed the contribution of the modulation amplitude to the regional CME characteristics based on the 410 GPS stations which located in China. The PCA method is used to carry out regional common-mode error analysis on the obtained residuals time series which is after deduction of deformation signals such as tectonic movements. The spectral analysis shows that the CME considering the amplitude modulation significantly weakens the characteristics of the annual cycle. The annual spectral peaks of the north components are reduced by 50%, the east components with a reduction of 80% and a reduction of 60% in the elevation component. The results of noise analysis show that the FN in CME that considers amplitude modulation is significantly lower than that of constant amplitude. This indicate that in time series analysis, the ‘signal’ that has not been estimated due to the oversimplification of the parameters is filtered in the area time will be evolved into CME, which means that CME not only contains errors, but also ‘signals’, that is, ‘signals’ that are not correctly modelled will affect the regional filtering effect.
Abstract. At present, ITRS series reference frameworks are widely used in the world. The results of GNSS are mostly based on the ITRF framework. Transform from ITRF to CGCS2000 is not easy, which restricts the promotion and use of CGCS2000. The conversion relationship between CGCS2000 and ITRF framework has imminent practical significance. This paper constructs the epoch reduction and frame conversion two-steps model which estimated the nonlinear model to solve the appeal problem. Effective test show that the nonlinear model accesses an improvement in not only precession but also accuracy relative to the tradition model.
Commission VI, WG VI/4 KEY WORDS: GPS, OCEAN TIDE MODEL, TIME SERIES, SPECTRAL INVERSION, PPP ABSTRACT:Due to lack of regional data constraints, all global ocean tide models are not accuracy enough in offshore areas around China, also the displacements predicted by different models are not consistency. The ocean tide loading effects have become a major source of error in the high precision GPS positioning. It is important for high precision GPS applications to build an appropriate regional ocean tide model. We first process the four offshore GPS tracking station's observation data which located in Guangdong province of China by using PPP aproach to get the time series. Then use the spectral inversion method to acquire eigenvalues of the Ocean Tidal Loading. We get the estimated value of not only ~12hour period tide wave (M2, S2, N2, K2) but also ~24hour period tide wave (O1, K1, P1, Q1) which has not been got in presious studies. The contrast test shows that GPS estimation value of M2, K1 is consistent with the result of five famous glocal ocean load tide models, but S2, N2, K2, O1, P1, Q1 is obviously larger.
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