In-orbit assessment of laser retro-reflector efficiency onboard high orbiting satellites

The navigation and geodetic satellites that orbit the Earth at altitudes of approximately 20,000 km are tracked routinely by many of the Satellite Laser Ranging (SLR) stations of the International Laser Ranging Service (ILRS). In order to meet increasing demands on SLR stations for daytime and nighttime observations, any new mission needs to ensure a strong return signal so that the target is easily acquirable. The ILRS has therefore set a minimum effective cross-section of 100 million square metres for the on-board laser retro-reflector arrays (LRAs) and further recommends the use of ‘uncoated’ cubes in the arrays. Given the large number of GNSS satellites that are currently supported by SLR, it is informative to make an assessment of the relative efficiencies of the various LRAs employed. This paper uses the laser ranging observations themselves to deduce and then compare the efficiencies of the LRAs on the COMPASS-M1 navigation satellite, two satellites from the GPS and three from the GLONASS constellations, the two GIOVE test satellites from the upcoming Galileo constellation, the two Etalon geodetic spheres and the geosynchronous communications test satellite, ETS-8. All the LRAs on this set of satellites employ back-coated retro-reflector cubes, except those on the COMPASS-M1 and ETS-8 vehicles which are uncoated. A measure of return signal strength, and thus of LRA-efficiency, is calculated using the laser-range full-rate data archive from 2007 to 2010, scaled to remove the effects of variations in satellite range, atmospheric attenuation and retro-reflector target total surface area. Observations from five SLR stations are used in this study; they are Herstmonceux (UK), Yarragadee (Australia), Monument Peak and McDonald (USA) and Wettzell (Germany). Careful consideration is given to the treatment of the observations from each station in order to take account of local working practices and system upgrades. The results show that the uncoated retro-reflector cubes offer significant improvements in efficiency.     

The effect of geocenter motion on Jason-2 orbits and the mean sea level

We compute a series of Jason-2 GPS and SLR/DORIS-based orbits using ITRF2005 and the std0905 standards ( Lemoine et al., 2010). Our GPS and SLR/DORIS orbit data sets span a period of 2 years from cycle 3 (July 2008) to cycle 74 (July 2010). We extract the Jason-2 orbit frame translational parameters per cycle by the means of a Helmert transformation between a set of reference orbits and a set of test orbits. We compare the annual terms of these time-series to the annual terms of two different geocenter motion models where biases and trends have been removed. Subsequently, we include the annual terms of the modeled geocenter motion as a degree-1 loading displacement correction to the GPS and SLR/DORIS tracking network of the POD process. Although the annual geocenter motion correction would reflect a stationary signal in time, under ideal conditions, the whole geocenter motion is a non-stationary process that includes secular trends. Our results suggest that our GSFC Jason-2 GPS-based orbits are closely tied to the center of mass (CM) of the Earth consistent with our current force modeling, whereas GSFC’s SLR/DORIS-based orbits are tied to the origin of ITRF2005, which is the center of figure (CF) for sub-secular scales. We quantify the GPS and SLR/DORIS orbit centering and how this impacts the orbit radial error over the globe, which is assimilated into mean sea level (MSL) error, from the omission of the annual term of the geocenter correction. We find that for the SLR/DORIS std0905 orbits, currently used by the oceanographic community, only the negligence of the annual term of the geocenter motion correction results in a – 4.67 ± 3.40 mm error in the Z-component of the orbit frame which creates 1.06 ± 2.66 mm of systematic error in the MSL estimates, mainly due to the uneven distribution of the oceans between the North and South hemisphere.     

DORIS geodesy: A dynamic determination of geocentre location

Geoscience Australia contributed a multi-satellite, multi-year weekly time series to the International DORIS Service combined submission for the construction of International Terrestrial Reference Frame 2008 (ITRF2008). This contributing solution was extended to a study of the capability of DORIS to dynamically estimate the variation in the geocentre location. Two solutions, comprising different constraint configurations of the tracking network, were undertaken. The respective DORIS satellite orbit solutions (SPOT-2, SPOT-4, SPOT-5 and Envisat) were verified and validated by comparison with those produced at the Goddard Space Flight Center (GSFC), DORIS Analysis Centre, for computational consistency and standards. In addition, in the case of Envisat, the trajectories from the GA determined SLR and DORIS orbits were compared. The results for weekly dynamic geocentre estimates from the two constraint configurations were benchmarked against the geometric geocentre estimates from the IDS-2 combined solution. This established that DORIS is capable of determining the dynamic geocentre variation by estimating the degree one spherical harmonic coefficients of the Earth’s gravity potential. It was established that constrained configurations produced similar results for the geocentre location and consequently similar annual amplitudes. For the minimally constrained configuration Greenbelt–Kitab, the mean of the uncertainties of the geocentre location were 2.3, 2.3 and 7.6 mm and RMS of the mean uncertainties were 1.9, 1.2 and 3.5 mm for the X, Y and Z components, respectively. For GA_IDS-2_Datum constrained configuration, the mean of the uncertainties of the geocentre location were 1.7, 1.7 and 6.2 mm and RMS of the mean uncertainties were 0.9, 0.7 and 2.9 mm for the X, Y and Z components, respectively. The mean of the differences of the two DORIS dynamic geocentre solutions with respect to the IDS-2 combination were 1.6, 4.0 and 5.1 mm with an RMS of the mean 21.2, 14.0 and 31.5 mm for the Greenbelt–Kitab configuration and 4.1, 3.9 and 4.3 mm with an RMS 8.1, 9.0 and 28.6 mm for the GA_IDS-2_Datum constraint configuration. The annual amplitudes for each component were estimated to be 5.3, 10.8 and 11.0 mm for the Greenbelt–Kitab configuration and 5.3, 9.3 and 9.4 mm for the GA_IDS-2_Datum constraint configuration. The two DORIS determined dynamic geocentre solutions were compared to the SLR determined dynamic solution (which was determined from the same process of the GA contribution to the ITRF2008 ILRS combination) gave mean differences of 3.3, −4.7 and 2.5 mm with an RMS of 20.7, 17.5 and 28.0 mm for the X, Y and Z components, respectively for the Greenbelt–Kitab configuration and 1.1, −5.4 and 4.4 mm with an RMS of 9.7, 13.3 and 24.9 mm for the GA_IDS-2_Datum configuration. The larger variability is reflected in the respective amplitudes. As a comparison, the annual amplitudes of the SLR determined dynamic geocentre are 0.9, 1.0 and 6.8 mm in the X, Y and Z components. The results from this study indicate that there is potential to achieve precise dynamically determined geocentre from DORIS.     

Estimation of the Love and Shida numbers: h2, l2 using SLR data for the low satellites

In this paper we present results for the global elastic parameters: Love number h₂ and Shida number l₂ derived from the analysis of Satellite Laser Ranging (SLR) data. SLR data for the two low satellites STELLA (H = 800 km) and STARLETTE (H = 810 km) observed during 2.5 years from January 3, 2005 until July 1, 2007 with 18 globally distributed ground stations were analyzed. The analysis was done separately for the two satellites. We do a sequential analysis and study the stability and convergence of the estimates as a function of length of the data set used.     

22 Years of AJISAI spin period determination from standard SLR and kHz SLR data

Satellite Laser Ranging (SLR) is a powerful and efficient technique to measure spin parameters of satellites equipped with corner cube reflectors. We obtained spin period determination of the satellite AJISAI from SLR data only: 17246 pass-by-pass estimates from standard 1–15 Hz SLR data (14/Aug/1986–30/Dec/2008) and 1444 pass-by-pass estimates (9/Oct/2003–30/Dec/2008) from data of the first 2 kHz SLR system from Graz, Austria. A continuous history of the slowing down of AJISAI spin is derived from frequency analysis, and corrected for the apparent effects. The apparent corrections, elaborated here, allowed very accurate determination of AJISAI initial spin period: 1.4855 ± 0.0007 [s]. The paper identifies also non-gravitational effects as a source of the periodical changes in the rate of slowing down of the satellite.     

ETALON spin period determination from kHz SLR data

Using kHz Satellite LASER Ranging (SLR) data of the SLR station Graz only, we determined the spin periods of the two ETALON satellites – launched into high orbits of about 20,000 km – and their spin period increase during 3 years. The determined spin period values and spin period increase rates at 2004-01-01 are: T_ET1 = 63 s + 0.484 s/year, and T_ET2 = 65.5 s + 0.401 s/year.     

空间飞行器综合定轨与参数分析软件COMPASS的研发——动力学统计定轨程序compass的编写及调试

介绍了空间飞行器综合定轨与参数分析软件COMPASS的开发过程。软件的初级阶段目标是可以利用SLR观测对多颗激光卫星进行同时定轨、可以利用非差GPS观测对GPS星座进行同时定轨，并估计有意叉的地学参数。COMPASS的开发采取了由简到繁、循序渐进的技术策略，软件开发经历了这样几个主要过程：多星多技术定轨框架的建立。利用SLR观测确定GPS卫星的轨道，利用IGS的SP3轨道确定GPS星座的轨道，利用非差GPS伪距观测确定GPS星座的轨道，利用非差GPS伪距和相位观测确定GPS星座的轨道。激光卫星的定轨精度已经达到国际水平，可以用于提供国际服务（如IERSEOP；ILRS快速分析）；GPS定轨内符精度达到国际先进水平，平均外符精度好于30cm。     

基于伪随机脉冲估计的简化动力学卫星定轨方法

采用简化动力学模型和星载GPS非差观测值,通过在确定性卫星运动方程中引入伪随机脉冲参数,将确定性参数和伪随机脉冲参数一起估计,对CHAMP卫星进行精密定轨.定轨软件采用自行研制的CASMORD精密定轨软件,定轨结果与GFZ事后定轨结果以及SLR结果进行了比较与分析.结果表明,采用简化动力学方法对CHAMP卫星定轨,在X、Y、Z三个方向的均方根误差(RMS)基本一致,轨道位置精度优于10cm,与SLR比较,测距精度优于5cm,定轨结果可靠,验证了算法的可行性和软件的定轨精度.     

Geocenter coordinates estimated from GNSS data as viewed by perturbation theory

Time series of geocenter coordinates were determined with data of two global navigation satellite systems (GNSSs), namely the U.S. GPS (Global Positioning System) and the Russian GLONASS (Global’naya Nawigatsionnaya Sputnikowaya Sistema). The data was recorded in the years 2008–2011 by a global network of 92 permanently observing GPS/GLONASS receivers. Two types of daily solutions were generated independently for each GNSS, one including the estimation of geocenter coordinates and one without these parameters.