Satellite Attitude Error Research Articles

GRACE-FO attitude determination: Star camera installation matrix calibration and incremental quaternion integrator

The satellite attitude error is transmitted to the gravity field through KBR antenna phase center correction and non-conservative force conversion, which affects the accuracy of gravity field inversion. Therefore, obtaining high-precision satellite attitude is one of the important research contents of gravity field inversion. Each satellite of GRACE-FO is equipped with three SCs and an IMU for satellite attitude measurement, and fusion of these two types of data can obtain high-precision satellite attitude. In this paper, we use kalman filter to fuse the original GRACE-FO 1A observation data, and take into account the calibration of the installation matrix of the SCs during the fusion process. Meanwhile, a quaternion integrator that takes angle increments as inputs is derived from the equivalent rotation vector differential equation to address the computational inefficiency of first-order quaternion integrator, the accuracy and computational efficiency are verified using measured data. The experimental results show that after the calibration of the installation matrix of the SCs, the system bias of 20′′ caused by switching from three SCs observations to two SCs observations can be eliminated. The standard deviation of the attitude difference between the obtained attitude in this paper and the attitude calculated by JPL is at most 6′′ and the proposed incremental quaternion integrator has the same accuracy as the first-order quaternion integrator but with computational efficiency improved by at least 35%.

Characteristics of phase bias from CNES and its application in multi-frequency and multi-GNSS precise point positioning with ambiguity resolution

While precise point positioning ambiguity resolution (PPP AR) is a valuable tool of the multi-constellation global navigation satellite system (multi-GNSS), phase biases are critical to implement PPP AR. Multi-frequency phase biases and satellite attitude files are provided freely by Centre National d’Etudes Spatiales (CNES), which are estimated based on GeoForschungs Zentrum (GFZ) satellite rapid orbit and clock products. However, the temporal characteristics of these phase biases and their positioning performance in the multi-frequency and multi-GNSS PPP AR have not been investigated yet, especially in the low sun elevation and satellite maneuver period. We introduce the transformation between multi-frequency phase biases and integer recovery clock model. In this transformation, inter-frequency clock biases (IFCBs) and inconsistencies in satellite attitude model errors between GFZ and CNES products are well considered. Experiments with GPS/Galileo/BeiDou observations from 34 stations were performed in static and kinematic modes, and the multi-frequency phase residuals were analyzed in the low sun elevation. Our results show that the impact of IFCBs and inconsistencies in satellite attitude errors could be mitigated at the user ends by using phase biases and satellite attitude files. Under the condition of satellite reverse yaw maneuvers, the performance of kinematic PPP without phase biases or deleting maneuvering satellites would be degraded significantly until the end of satellite observation arc or the next reverse yaw maneuver occurs. By applying phase biases with PPP AR, the positioning accuracy could be improved by 34.4%, 23.1%, and 37.4% in the east (E), north (N), and up (U) directions, respectively. Therefore, we suggested that PPP users should apply phase biases and satellite attitude files when using the GFZ rapid orbit and clock products, especially for satellite maneuvers and low sun elevation.

Geometric Accuracy Improvement Method for High-Resolution Optical Satellite Remote Sensing Imagery Combining Multi-Temporal SAR Imagery and GLAS Data

With the widespread availability of satellite data, a single region can be described using multi-source and multi-temporal remote sensing data, such as high-resolution (HR) optical imagery, synthetic aperture radar (SAR) imagery, and space-borne laser altimetry data. These have become the main source of data for geopositioning. However, due to the limitation of the direct geometric accuracy of HR optical imagery and the effect of the small intersection angle of HR optical imagery in stereo pair orientation, the geometric accuracy of HR optical imagery cannot meet the requirements for geopositioning without ground control points (GCPs), especially in uninhabited areas, such as forests, plateaus, or deserts. Without satellite attitude error, SAR usually provides higher geometric accuracy than optical satellites. Space-borne laser altimetry technology can collect global laser footprints with high altitude accuracy. Therefore, this paper presents a geometric accuracy improvement method for HR optical satellite remote sensing imagery combining multi-temporal SAR Imagery and GLAS data without GCPs. Based on the imaging mechanism, the differences in the weight matrix determination of the HR optical imagery and SAR imagery were analyzed. The laser altimetry data with high altitude accuracy were selected and applied as height control point in combined geopositioning. To validate the combined geopositioning approach, GaoFen2 (GF2) optical imagery, GaoFen6 (GF6) optical imagery, GaoFen3 (GF3) SAR imagery, and the Geoscience Laser Altimeter System (GLAS) footprint were tested. The experimental results show that the proposed model can be effectively applied to combined geopositioning to improve the geometric accuracy of HR optical imagery. Moreover, we found that the distribution and weight matrix determination of SAR images and the distribution of GLAS footprints are the crucial factors influencing geometric accuracy. Combined geopositioning using multi-source remote sensing data can achieve a plane accuracy of 1.587 m and an altitude accuracy of 1.985 m, which is similar to the geometric accuracy of geopositioning of GF2 with GCPs.

Calibration and Estimation of Attitude Errors for a Rotating Fan-Beam Scatterometer Using Calibration Ground Stations

The rotating fan-beam scatterometer (RFSCAT) onboard Chinese-French Oceanic SATellite (CFOSAT) due to launch in 2018 is a new type of radar scatterometer system for ocean surface wind vector measurement. It can give observations with more azimuth and incidence angles for a single wind vector cell (WVC) than other available scatterometers. This has been proved effective in bettering the retrieved wind quality by the simulation approach. However, its innovative observing geometry is challenging for the coming in-orbit external calibration. In this paper, CFOSAT attitude errors are estimated, and its antenna gain pattern is monitored and verified based on the external calibration strategy of a Ku-band scatterometer employing calibration ground stations (CGSs). The effects of satellite attitude errors on the measurements are also analyzed, together with simulation results for the external calibration. It is shown that a gain pattern with accuracy of 0.08 dB and attitude errors within 0.025° are achieved.

Ray tracing in relativistic astrometry: the satellite attitude error and the comprehensive error budget

The general relativistic analysis of the astrometric data which will be soon provided by the satellite GAIA—ready to be launched in 2012—should include an accurate estimation of the errors which are due to the uncertainties of the boundary conditions. These uncertainties stem from the errors of the observables which can be intrinsic but also induced by the instabilities of the satellite attitude. Following previous work, we take these additional sources of uncertainties into account and provide semi-analytically, at the requested order of accuracy , the complete error equations for the line of sight and the stellar position at the emission event.

A parametric study on the impact of satellite attitude errors on GOCE gravity field recovery

In the recent design of the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite mission, the gravity gradients are defined in the gradiometer reference frame (GRF), which deviates from the actual flight direction (local orbit reference frame, LORF) by up to 3–4°. The main objective of this paper is to investigate the effect of uncertainties in the knowledge of the gradiometer orientation due to attitude reconstitution errors on the gravity field solution. In the framework of several numerical simulations, which are based on a realistic mission configuration, different scenarios are investigated, to provide the accuracy requirements of the orientation information. It turns out that orientation errors have to be seriously considered, because they may represent a significant error component of the gravity field solution. While in a realistic mission scenario (colored gradiometer noise) the gravity field solutions are quite insensitive to small orientation biases, random noise applied to the attitude information can have a considerable impact on the accuracy of the resolved gravity field models.

Ground control pointing and geometric transformation of satellite imagery

Abstract LANDSAT imagery has been corrected for Earth curvature and rotation, satellite attitude errors and sensor non-linearities, it still contains significant geometric distortions with the centre of the scene only located to an accuracy of a few kilometres. For some applications these errors are unimportant but an increasing number of users need geometrically transformed imagery either for direct comparison with maps or for multitemporal analysis. To determine the transformation the user must select a number of ground control points, i.e. features which are readily identifiable on both the image and a map. The transformation matrix between image and map co-ordinates is then determined and the scene resampled using interpolation techniques.