Engineering topics
Publications and source records attributed to Wolff, Peter J..
The upcoming launch of the solar electric propulsion (SEP) mission New Millennium Deep Space 1 and proposed future SEP missions such as Pluto Express necessitates an analysis of the operational issues related to the navigation of low-thrust missions.
Elements of this experiment include the GPS satellite constellation, GPS Demonstration Receiver (GPSDR) on-board T/P, six ground GPS receivers, the GPS Data Handling Facility and the GPS Data Processing Facility.
Results of operational Orbit detemination, Performed as part of the TOPEX/Poseidon (T/P) Global Positionin Satellite (GPS) demonstration experiment, are presented in this paper. Elements of this experiment include the GPS satellite constellation, GPS Demonstration Receiver on-board T/P, six ground GPS receivers, the GPS Data Handling Facility and the GPS Data processing Facility (GDPF).
Two algorithms compute error covariance of difference between optimal estimates, based on data acquired during overlapping or disjoint intervals, of state of discrete linear system. Provides quantitative measure of mutual consistency or inconsistency of estimates of states. Relative-error-covariance concept applied, to determine degree of correlation between trajectories calculated from two overlapping sets of measurements and construct real-time test of consistency of state estimates based upon recently acquired data.
A state estimation problem where some of the measurements may be common to two or more data sets is considered. Two approaches for computing the error covariance of the difference between filtered estimates (for each data set) are discussed. The first algorithm is based on postprocessing of the Kalman gain profiles of two correlated estimators. It uses UD factors of the covariance of the relative error. The second algorithm uses a square root information filter applied to relative error analysis. In the absence of process noise, the square root information filter is computationally more efficient and more flexible than the Kalman gain (covariance update) method. Both the algorithms (covariance and information matrix based) are applied to a Venus orbiter simulation, and their performances are compared.
Orbit Analysis and Simulation Software, OASIS, is software system developed for covariance and simulation analyses of problems involving Earth satellites, especially Global Positioning System (GPS). Provides flexible, versatile, and efficient software tool for analysis of accuracy in Earth-satellite navigation and GPS-based geodetic studies.