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Alexander Krimchansky

Publications and source records attributed to Alexander Krimchansky.

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↗

Reflective Solar Band Striping Mitigation Method for the GOES-R Series Advanced Baseline Imager Using Special Scans

The large focal plane arrays used in the new generation of the Geostationary Operational Environmental Satellites (GOES) advanced baseline imager (ABI) introduce new calibration challenges compared with the heritage GOES imagers. The increased number of detectors allows for increased spatial, spectral, and temporal performance, but as a trade-off, it has an increased risk of image striping. We detail the development of a new postlaunch relative calibration capability for ABI reflective solar bands that utilizes ABI special scans to generate a set of relative gains that can be applied to improve image quality and reduce image striping. Results demonstrate that the method reduces image striping in the ABI solar reflective bands over varying scene content and time, both diurnally and over an extended period. This methodology ensures a calibration strategy that is consistent with heritage approaches yet adapts to the new postlaunch validation challenges presented by the new class of operational imagers in the GOES-R series. The developed approach is ready for operational use, as needed, and can be easily implemented into operations to support the operational production of geostationary imagery of the Earth.

Monica Cook↗

Validation of GOES-17 ABI Reflective Channels Performance: Salar De Uyuni 2018 Field Campaign Results

Validation results from a reflectance-based field campaign at the Salar de Uyuni in Bolivia (September 2018) are presented for GOES-17 and GOES-16 Advanced Baseline Imagers (ABI) reflective channels. The in situ measurements were used to characterize the surface reflectance and the atmosphere in order to constrain a radiative transfer model and predict the reflectance at the top of the atmosphere (TOA), which was then compared to the ABI measurements. The field campaign provides TOA reflectance estimates over several days, allowing assessment of the calibration accuracy and stability of channels 1, 2, 3, 5 and 6 for GOES-17 andGOES-16 ABI. Channel 1 of GOES-17 ABI shows -5.5% bias in comparison to the ground-based predicted TOA. Over 6% bias in GOES-17 B2 was confirmed. A comparison to NOAA-20 VIIRS was also carried on during a near nadir overpass.

validation↗

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↗

Compact Coronagraph (CCOR) Accommodation on GOES-U

The CCOR-1 will monitor our Sun’s Coronal Mass Ejections (CMEs). It will reside on the Sun-Pointing Platform (SPP) of the Geostationary Operational Environmental Satellite (GOES) -U in a geostationary orbit. As a member of the GOES-R Series of satellites, GOES-U will pro-vide advanced imagery and atmospheric measurements of Earth’s weather, oceans and envi-ronment, real-time mapping of total lightning activity, and as well as monitoring of solar ac-tivity and space weather. GOES-U is the final satellite in the GOES-R Series, with an expected launch date in April of 2024. The Compact Coronagraph (CCOR) instrument was designed, built, and tested by the Unit-ed States Naval Research Laboratory. CCOR-1, the first in a series of coronagraphs, is funded by the National Oceanic and Atmospheric Administration (NOAA), is managed by the National Aeronautics and Space Administration (NASA), and will ultimately be operated by NOAA. Us-ing a series of images of the Sun’s coronal white-light, scientists at NOAA’s Space Weather Prediction Center (SWPC) and National Centers for Environmental Information (NCEI) can de-termine the size, velocity, and density of these CMEs. This information can then be used to assess and prepare for potential impacts of these solar storms on infrastructure here on Earth, as well as assets in space. CCOR-1 has completed instrument-level Integration and Testing (I&T), delivered to the GOES-U satellite vendor and is now mechanically integrated with the spacecraft. The GOES-U satellite has completed spacecraft-level integration and test activities. This poster presents the details on the CCOR-1 instrument, its integration onto the GOES-U satellite bus, ground system, and operations, as well as the expected performance.

White Light Coronagraph↗

From the Solar Limb and Out: Results from the Wide-Field EUV Image Campaigns with GOES/SUVI

Traditional approaches to tracking solar outflows for space weather forecasting rely primarily on coronagraph images, which generally observe the solar corona above a minimum height of about 2.5 solar radii. EUV images have been widely used to characterize features on the solar disk, but the limited fields of view of most current EUV imagers have prevented their use for tracking outflows through the inner and middle coronae. A series of off-point campaigns with the GOES 16-18 Solar Ultraviolet Imager (SUVI) between 2018 and 2022 from three Flight Models have provided an opportunity to assess the value of extended EUV images for space weather forecasting applications. These new results demonstrate that wide field-of-view EUV images are useful for characterizing the early onset of eruptive events and tracking smaller outflow into the solar wind. They also reveal the origins of shocks that are known to accelerate particles and drive solar energetic particle (SEP) events. Because CMEs generally experience the bulk of their acceleration below the height of white light coronagraphic observations, these images provide information about the origins of these events that has not been available traditionally. Together with coronagraphic measurements, EUV images provide the continuous views needed to connect CMEs back to their source regions. Here, we present these new SUVI observations and discuss their potential use in space weather operations.

SUVI↗