The Geostationary Operational Environmental Satellite (GOES) 13 is the first in a new series of weather satellites. Compared to previous GOES satellites, GOES-13 has improved Image Navigation and Registration (INR) accuracy and can continue imaging during eclipse periods. Post launch testing showed that GOES-13 met all INR requirements, but systematic patterns appeared in differences between actual landmark and range measurements and 24-hour measurement predictions based on estimated orbit and attitude parameters. Presence of these residual patterns implied that the models used in Orbit and Attitude Determination (OAD) did not accurately match reality. Thorough investigations were conducted to determine the modeling error source. It was concluded that an angular bias between star and landmark observations was the most likely modeling error, although small uncompensated range biases could also be present. Further analysis of on-orbit and test data eliminated numerous potential instrument, spacecraft and ground processing error sources. Although the cause of the landmark-star bias is still unknown, the bias causes no operational problems because OAD solution of a range bias compensates for the error. Even without range bias adjustment, GOES-13 met all INR requirements with margin.
The Geostationary Operational Environmental Satellite (GOES) 13 is the first in a new series of weather satellites. Compared to previous GOES satellites, GOES-13 has improved Image Navigation and Registration (INR) accuracy, can continue imaging during eclipse periods, periodically yaw-flips to provide better instrument cooling, and uses daily momentum dumping maneuvers to offset solar torque generated by the single solar array. Post launch testing showed that GOES-13 met all INR requirements, but post-maneuver orbit predictions, particularly longitude drift, were not nearly as accurate as desired. Ground software computes the maneuver velocity change ( v) for the predictions using firing data (telemetry if available, or predicted firing if not) and a propulsion model for the twelve 9.25 N bi-propellant thrusters. Investigations verified that the propulsion model met flowdown requirements on maneuver v accuracy, but several problems were uncovered. In particular, the effect of plume impingement on the solar array was not modeled, the propulsion model was not accurate for pulsed firing with short off-times, and prelaunch calibrations of jet thrust and direction were slightly in error. A plume impingement model was developed using detailed models of plume momentum flux and plate reflection. Corrections to calibrations of jet thrust and direction were computed using a thruster calibration algorithm that fits maneuver v estimates (obtained from orbit determination), angular momentum change ( h) telemetry data, and prior information. Thruster mass and energy flow was analyzed to understand factors affecting pulsed firing. Problems in modeling short off-time pulsed firing were eventually traced to the effects of liquid propellant remaining between the jet valves and thrust chamber after valve closure. A new propulsion model was developed and validated using data for hundreds of test firings. With these changes, the ground system can accurately predict GOES-13 maneuver performance for all maneuver types.
The Geostationary Operational Environmental Satellite "GOES-13" is the first of a new generation of United States weather satellites. Launched in May 2006, it incorporates new features designed to improve Image Navigation & Registration (INR) performance. The objectives of this paper are to present GOES-13 on-orbit INR performance, make comparisons against the previous GOES satellite series (GOES-8 through -12), and to explore the associated improvements to spacecraft operations. INR system performance was evaluated during operational scenarios including normal daily operations (which included momentum unloads), station keeping maneuvers, yaw flips, eclipse operations, and station change maneuvers. The PreObs Residual Plotter software was used to evaluate trends in observation residuals, and the Performance Analysis System software was used to calculate the percentage of residuals that met performance specifications. For each scenario, postlaunch tests showed that the INR system successfully passed all specification requirements and provided significant improvement versus the previous GOES series.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.