Anthony Mannucci, George Hajj, Byron Iijima, Attila Komjathy, Thomas Meehan, Xiao Qing Pi, Jeff Srinivasan, Bruce Tsurutani, Brian Wilson, Liwei Zhang, Mark Moldwin
KEYWORDS: Global Positioning System, Satellites, Plasma, Receivers, Antennas, Data modeling, Remote sensing, Solar radiation models, Solar processes, Tongue
Transmissions of the Global Positioning System (GPS) satellites can be used to measure the total electron content (TEC) between a receiver and several GPS satellites in view. This simple observable is yielding a wealth of new scientific information about ionosphere and plasmasphere dynamics. Data available from thousands of ground-based GPS receivers are used to image the large-scale and mesoscale ionospheric response to geospace forcings at high-precision covering all local times and latitudes. Complementary measurements from space-borne GPS receivers in low-Earth orbit provide information on both vertical and horizontal structure of the ionosphere/plasmasphere system. New flight hardware designs are being developed that permit simultaneous measurement of integrated electron content along new raypath orientations, including zenith, cross-track and nadir antenna orientations (the latter via bistatic reflection of the GPS signal off ocean surfaces). We will discuss a new data assimilation model of ionosphere, the Global Assimilative Ionosphere Model (GAIM), capable of integrating measurements from GPS and other sensors with a physics-based ionospheric model, to provide detailed global nowcasts of ionospheric structure, useful for science and applications. Finally, we discuss efforts underway to combine GPS space-based observations of plasmaspheric TEC, with ground-based magnetometer measurements, and satellite-based images from NASA's IMAGE satellite, to produce new dynamic models of the plasmasphere.
Global astrometry is the measurement of stellar positions and motions. These are typically characterized by five parameters, including two position parameters, two proper motion parameters, and parallax. The Space Interferometry Mission (SIM) will derive these parameters for a grid of approximately 1300 stars covering the celestial sphere to an accuracy of approximately 4uas, representing a two orders of magnitude improvemnt over the most precise current star catalogues. Narrow angle astrometry will be performed to a 1uas accuracy. A wealth of scientific information will be obtained from these accurate measurements encompassing many aspects of both galactic and extragalactic science. SIM will be subject to a number of instrument errors that can potentially degrade performance. Many of these errors are systematic in that they are relatively static and repeatable with respect to the time frame and direction of the observation. This paper and its companion define the modeling of the contributing factors to these errors and the analysis of how they impact SIM's ability to perform astrometric science.
The current design of the Space Interferometry Mission (SIM) employs a 19 laser-metrology-beam system (also called L19 external metrology truss) to monitor changes of distances between the fiducials of the flight system's multiple baselines. The function of the external metrology truss is to aid in the determination of the time-variations of the interferometer baseline. The largest contributor to truss error occurs in SIM wide-angle observations when the articulation of the siderostat mirrors (in order to gather starlight from different sky coordinates) brings to light systematic errors due to offsets at levels of instrument components (which include corner cube retro-reflectors, etc.). This is the external metrology wide-angle field-dependent error. Physics-based model of field-dependent error at single metrology gauge level is developed and linearly propagated to errors in interferometer delay. General formulation of delay error sensitivity to various error parameters is developed. The essence of the linear error model is contained in an errormapping matrix. A corresponding Zernike component matrix approach is developed in parallel with its advantages discussed. As a first example, dihedral error model is developed for the corner cubes (CC) attached to the siderostat mirrors. Average and worst case residual errors are computed when various orders of field-dependent terms are removed from the delay error. These serve as guidelines for arriving at system requirements given the error budget allocation. Highlights of the non-common vertex error (NCVE) model are shown as a second example followed by discussions.
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