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Douglas Freesland

Publications and source records attributed to Douglas Freesland.

Autonomous Maneuver Planning and Execution for GeoXO Station Keeping and Momentum Management

GOES-16 was launched in 2016 using GPS at GEO, a first for civil space. With the subsequent launch of GOES-17 in 2018, followed by GOES-18 in 2022, we have accumulated over a decade of error free GPS navigation experience at GEO. Confident in GPS performance at GEO, the next generation/NASA geosynchronous weather satellite program GeoXO will require the spacecraft flight software to automate station keeping and momentum management maneuver planning and execution. Coupled with low thrust propulsion, it gives us assurance that on-board maneuver planning and execution can be implemented at a very low risk, allowing instruments to operate through maneuvers while maintaining a more accurate orbital slot and reducing operational costs. In this paper, we discuss how GOES-R maneuver planning is currently performed on the ground and contrast this with our vision of how it might be automated on-board.

GeoXO↗

On-Board Deployment Event Verification for GOES-R Spacecraft

As is common with many spacecraft designs, the GOES-R vehicles require a series of deployment events to transition from the launch configuration to the operational configuration. Rather than implementing additional sensors to verify various deployments, the GOES-R program developed an alternate approach that uses existing gyro rate sensing. The approach includes two pieces: the first is a new onboard shock detection capability to confirm initiation of individual deployment events, and the second is a ground-based dynamics verification step to confirm completion of deployment events. We first present the algorithm that detects shock events for various deployment devices along with the parameter tuning performed during ground tests. We then show inflight performance of the shock detection algorithm. While shock detection is useful for observing initiation of deployment events, completion of some deployment events cannot be determined by shock detection alone. For these events, such as solar panel latch-up and deployable boom extension, the program developed dynamics models for the deployment transient responses. High-rate gyro data were recorded for these events, which allow the ground team to verify that the appendages were fully deployed. We show the predictive models for these events and corresponding flight results.

GeoXO↗

Global Positioning System Constellation Modernization Impact on Sidelobe Capable GPS Receivers in Geostationary Orbit

This paper provides on-orbit insight into Global Positioning System Receiver (GPSR) performance at a geostationary orbit (GEO) and contrasts that performance regarding the modernized and heritage GPS constellation currently operational. The subject matter of this paper falls under the following topics a) heritage and modern GPS transmit pattern comparison, b) GOES-R GPSR acquisition and tracking characterization regarding the first four operational GPS III vehicles, and c)relevant signal requirements as it pertains to GEO GPSR facilitation. The GPSR described herein is onboard the GOES-R series satellites. GOES-R (Geostationary Operational Environmental Satellite-R Series) is the first in a 4-part series of new weather satellites set to replace and upgrade the older GOES constellation. Two GOES-R have been launched to date, GOES-16 and GOES-17, the data presented in this paper are from both vehicles over common time spans. The GPSR on board this geostationary weather satellite is a mission critical, enabling technology which has been both tested on the ground and evaluated on-orbit to verify its effectivity[1]. This is a completely new system design consisting of a unique L1 GEO antenna, low-noise amplifier (LNA) assembly and a 12-channel GPSR capable of tracking the edge of the main beam and the sidelobes of the GPS L1 signal. Any satellite intending to maximize GPS navigation performance at GEO will need to implement a GPSR system that tracks sidelobes. GOES-R is the first civilian operational satellite to utilize GPS sidelobes for navigation at GEO, which is the key factor in the systems highly accurate, robust and continuous navigation solution. However, this also renders a distinct sensitivity to changes in the GPS transmit signal pattern in the sidelobe regime as a result of the new GPS III constellation modernization. This paper presents results showing that the GOES-RGPSR solution, given GPS constellation modernization to GPS III, although impacted slightly in received C/N0 at certain geometries, will continue to meet all performance requirements tracking up to 12 satellites and achieving excellent carrier-to-noise spectral density (C/N0).

GPS↗

GOES-R GN&C Capabilities Used to Support Instrument Anomaly Investigations

The Geostationary Operational Environmental Satellite-R program (GOES-R) has launched three of the latest generation geostationary weather satellites, of which all three are now fully operational. In this paper we discuss how the robust capabilities inherent in the design have been used to address off-nominal instrument performance observed in flight, and to subsequently provide acceptable data return from two of the instruments exhibiting off-nominal performance. The primary science instrument, the Advanced Baseline Imager (ABI), performed well on GOES-16, but on GOES-17 ABI exhibited anomalous IR-channel imaging early in the mission. Unfortunately, lower than expected thermal control capability did not cool the IR detectors to the expected temperatures. This paper presents spacecraft operations undertaken to calibrate the off-nominal performance of the instrument thermal control, and to develop spacecraft operational mitigation steps to recover near-nominal instrument performance. On GOES-16, the magnetometer (MAG) instrument experienced performance that was less than expected. As part of the MAG performance investigation, an improved calibration procedure was developed that required use of the entire GOES-R performance envelope. This paper presents an overview of the performance issues and provides details on the specific accommodations implemented to help maximize science return.

Jim Chapel↗