Data preparation and evaluation for Geos 1 tracking systems
Data evaluation from tracking systems abroad Geos 1
Solomon, L. H.↗
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Evolution and Reengineering of NASA's Flight Dynamics Facility (FDF)
The NASA Goddard Space Flight Center's Flight Dynamics Facility (FDF) is a multimission support facility that performs ground navigation and spacecraft trajectory design services for a wide range of scientific satellites. The FDF also supports the NASA Space Network by providing orbit determination and tracking data evaluation services for the Tracking Data Relay Satellite System (TDRSS). The FDF traces its history to early NASA missions in the 1960's, including navigation support to the Apollo lunar missions. Over its 40 year history, the FDF has undergone many changes in its architecture, services offered, missions supported, management approach, and business operation. As a fully reimbursable facility (users now pay 100% of all costs for FDF operations and sustaining engineering activities), the FDF has faced significant challenges in recent years in providing mission critical products and services at minimal cost while defining and implementing upgrades necessary to meet future mission demands. This paper traces the history of the FDF and discusses significant events in the past that impacted the FDF infrastructure and/or business model, and the events today that are shaping the plans for the FDF in the next decade. Today's drivers for change include new mission requirements, the availability of new technology for spacecraft navigation, and continued pressures for cost reduction from FDF users. Recently, the FDF completed an architecture study based on these drivers that defines significant changes planned for the facility. This paper discusses the results of this study and a proposed implementation plan. As a case study in how flight dynamics operations have evolved and will continue to evolve, this paper focuses on two periods of time (1992 and the present) in order to contrast the dramatic changes that have taken place in the FDF. This paper offers observations and plans for the evolution of the FDF over the next ten years. Finally, this paper defines the mission model of the future for the FDF based on NASA's current mission list and planning for the Constellation Program. As part of this discussion the following are addressed: the relevance and benefits of a multi-mission facility for NASA's navigation operations in the future; anticipated technologies affecting ground orbit determination; continued incorporation of Commercial Off-the-shelf (COTS) software into the FDF; challenges of a business model that relies entirely on user fees to fund facility upgrades; anticipated changes in flight dynamics services required; and considerations for defining architecture upgrades given a set of cost drivers.
Stengle, Thomas↗
TDRSS tracking data and orbit determination evaluation
TDRS-1 was launched on April 4, 1983. This paper presents preliminary results of TDRSS tracking data evaluation through September 1983. TDRSS tracking data evaluation is a summary of valid tracking data that characterizes data quality. TDRS-1 orbit accuracy is evaluated by using orbit consistency measured by comparing overlaps of TDRS-1 ephemerides produced from consecutive data arcs. TDRS-1 and user orbit accuracies and consistencies are also estimated. Orbit accuracy is estimated by comparing user orbits based on tracking data obtained both through the TDRSS and from ground-based tracking.
Campion, R. E.↗
Joint JSC/GSFC two-TDRS navigation certification results for STS-29, STS-30, and STS-32
The procedures used and the results obtained in the joint Johnson Space Center (JSC)/Goddard Space Flight Center (GSFC) navigation certification of the two-Tracking and Data Relay Satellite (TDRS) S-band tracking configuration for support of low- to medium-inclination (28.5 to 62 degrees) Shuttle missions (STS-29 and STS-30) and Shuttle rendezvous missions (STS-32) are described. The objective of this certification effort was to certify the two-TDRS configuration for nominal Space Transportation System (STS) on-orbit navigation support, thereby making it possible to significantly reduce the ground tracking support requirements for routine STS on-orbit navigation. JSC had the primary responsibility for certification of the two-TDRS configuration for STS support, and GSFC supported the effort by performing Ground Network (GN) and Space Network (SN) tracking data evaluation, parallel orbit solutions, and solution comparisons. In the certification process, two types of orbit determination solutions were generated by JSC and by GSFC for each tracking arc evaluated, one type using TDRS-East and TDRS-West tracking data combined with ground tracking data (the reference solutions) and one type using only TDRS-East and TDRS-West tracking data. The two types of solutions were then compared to determine the maximum position differences over the solution arcs and whether these differences satisfied the navigation certification criteria. The certification criteria were a function of the type of Shuttle activity in the tracking arc, i.e., quiet, moderate, or active. Quiet periods included no attitude maneuvers or ventings; moderate periods included one or two maneuvers or ventings; and active periods included more than two maneuvers or ventings. The results of the individual JSC and GSFC certification analyses for the STS-29, STS-30, and STS-32 missions and the joint JSC/GSFC conclusions regarding certification of the two-TDRS S-band configuration for STS support are presented.
Schmidt, Thomas G.↗
A sampled - data pursuit tracking model.
Evaluation of sampled data pursuit tracking model
SAMPLED DATA SYSTEM↗
James Webb Space Telescope Navigation Optimization Challenges
The James Webb Space Telescope (JWST) is a NASA flagship mission launched on December 25, 2021. The early orbit phase was highlighted by three midcourse correction burns that were performed to maneuver the vehicle into a libration orbit at the second Sun-Earth-Moon (SEM) libration point (L2). During the coast to L2, the vehicle’s primary observatory and sunshield were deployed. Once the tennis-court-sized sunshield was unfurled and tensioned into place, the large area exposed to solar radiation pressure (SRP) dictated that the SRP force model would need to account for the vehicle’s geometry, reflective properties, and orientation relative to the Sun. Following the insertion of JWST into its L2 libration orbit on January 24, 2022, the commissioning phase for the vehicle’s observatory commenced along with the first cycle of routine station-keeping maneuvers. The NASA Goddard Space Flight Center’s Flight Dynamics Facility (FDF) provides navigation services for the JWST mission. The FDF serves as the prime or backup navigation operations center for more than 30 active missions spanning a wide array of flight regimes performing orbit determination, maneuver planning, trajectory optimization, and tracking data evaluation. Definitive orbit determination for JWST is performed by the FDF using an Extended Kalman Filter (EKF) to estimate the vehicle’s trajectory and reflective properties using Deep Space Network (DSN) TRK-2-34 tracking data and spacecraft attitude telemetry. For the purposes of orbit prediction and station-keeping maneuver targeting, the sensitivity of the SRP force to the vehicle’s orientation requires that predictive attitude information must be incorporated to generate accurate orbit predictions and maneuver plans. Predictive attitude plans are provided to the FDF by the JWST Spacecraft Operations Center (SOC). Short-term (28 day) orbit predictions are propagated using a Short Range Attitude Plan (SRAP) to model the vehicle’s future attitude states for up to a week. SRAP attitude data is highly reliable, as it reflects finalized planned attitude states that the vehicle will be commanded to attain during the ensuing week. A Long Range Attitude Plan (LRAP) can be implemented to model predicted attitude states beyond one week, but these predictions are tentative and subject to revision due to changes in science operations plans. Instead, a conservative approach of applying a Sun-Pointing Neutral (SPN) attitude configuration is utilized for long-term (2 year) orbit predictions where reliable planned attitude data is not available. SPN attitude mode aligns the net SRP force along the JWST-to-Sun vector where it becomes independent of the vehicle’s angle of rotation about this vector, defined as the Sun yaw. Given the dynamic instability of the libration orbit, station-keeping thrust must be applied in either the sunward or anti-sunward direction to balance the resulting orbit. The attitude constraints of the vehicle also impose limits on the available pointing directions for station-keeping thrusters. The thrusters cannot be aligned with the optimal pointing direction for sunward maneuvers, rendering sunward maneuvers to be significantly less fuel efficient than anti-sunward maneuvers. Consequently, station-keeping maneuvers must be targeted to balance the orbit while ensuring that the next maneuver will also be performed in the anti-sunward direction to optimize propellant usage. When targeting a station-keeping maneuver, the attitude and SRP modeling configuration which is applied to the predicted post-maneuver trajectory will dictate the direction of the subsequent station-keeping maneuver, assuming nominal propulsion system performance. If the predicted post-maneuver attitude states result in an SRP model which under-predicts the cumulative SRP impact on the post-maneuver orbit, a targeted anti-sunward maneuver will be larger than necessary and the next maneuver will need to be executed sunward in order to compensate. In contrast, an anti-sunward maneuver which is targeted using an SRP model which over-predicts the cumulative SRP impact will achieve station-keeping while ensuring that the next maneuver will likewise be performed anti-sunward. For this reason, station-keeping maneuvers are targeted while applying the SPN attitude mode, as this mode entails the largest possible SRP area cross-section and therefore a larger modeled cumulative SRP impact. This paper documents the NASA Goddard Space Flight Center’s FDF support for JWST on-orbit operations and the analysis projects undertaken utilizing the experiences and data accumulated throughout the first full year of routine science operations. The results of these analysis efforts have been used to implement improvements to orbit prediction accuracy and maneuver efficiency which have the potential to prolong the lifespan of JWST to continue to conduct ground-breaking infrared astronomy for decades to come.
Flight Dynamics↗
Evaluation of GEOSAT Follow-On Precise Orbit Ephemeris
The GEOSAT Follow-On spacecraft (GFO-l), launched in 1998, began continuous radar altimeter coverage of the oceans in 2000, and after an extensive series of calibration campaigns in 1999 and 2000 was finally accepted by the US Navy on November 29, 2000. By providing high quality altimeter data, GFO can supplement TOPEX/POSEIDON(T/P), ERS-1, and ERS-2 data, providing a different synoptic sampling of the oceans with its 17-day ground track repeat cycle. Altimeter analysis suggests GFO is capable of POSEIDON class altimetry, with orbit error the largest contributor to the GFO altimeter error budget. Satellite laser ranging (SLR), especially in combination with altimeter crossover data, offer the only means of determining high-quality precise orbits. SLR tracking is also augmented by Doppler (Tranet style) beacons. These data were used to tune the gravity field and macromodel (3D representation of the spacecraft geometry and surface properties). Beginning with January 2000 GSFC has produced a 2.5 year span of the Precision Orbit Ephemeris (POE) intended for use on the GFO GDR and for the Pathfinder Project. Using GFO GDR and IGDR altimeter data from NOAA, a two year span of POE orbits are evaluated with respect to the TOPEX orbits by adjusting the GFO data into the TOPEX frame with the help of TOPEX/GFO altimeter crossovers. A 2.5 year span of orbits are also evaluated using tracking data residual analysis, GFO altimeter crossover residual analysis, and direct orbit comparison. In an effort to improve the current POE orbit several ideas are considered, including using recent gravity models which include CHAMP data, the reduced-dynamic approach, and including TOPEX/GFO altimeter crossover data in the orbit solution.
Lemoine, Frank G.↗
Tracking and data system support for the Viking 1975 mission to Mars. Volume 3: Planetary operations
The support provided by the Deep Space Network to the 1975 Viking Mission from the first landing on Mars July 1976 to the end of the Prime Mission on November 15, 1976 is described and evaluated. Tracking and data acquisition support required the continuous operation of a worldwide network of tracking stations with 64-meter and 26-meter diameter antennas, together with a global communications system for the transfer of commands, telemetry, and radio metric data between the stations and the Network Operations Control Center in Pasadena, California. Performance of the deep-space communications links between Earth and Mars, and innovative new management techniques for operations and data handling are included.
Mudgway, D. J.↗
Atmospheric density variations at 140 kilometers deduced from precise satellite radar tracking data.
Discussion of the technique of evaluating density values from precise radar-tracking data of satellites in the altitude region from 130 to 140 km. Inclinations of these satellites were between 106 and 112 deg. A detailed examination of all elements of the density-reduction techniques was conducted, and consideration was given to recent advances in geodesy, drag-coefficient modeling, and orbit-determination techniques. Ten days of high-resolution density data deduced from orbital decay of each of three satellites are presented. Three types of density variations at 140 km are discernible in these data: periodic daily density variations with a density amplitude of about 10%; density increases of up to 35% associated with enhanced geomagnetic activity during which the planetary geomagnetic index Kp reached a value of 8 units; and an observed semiannual variation of about 20%, which indicates a total semiannual variation of 35 to 40%.
Devries, L. L.↗
Deep Space Navigation with Noncoherent Tracking Data
Navigation capabilities of noncoherent tracking data are evaluated for interplanetary cruise phase and planetary (Venus) flyby orbit determination. Results of a formal covariance analysis are presented which show that a combination of one-way Doppler and delta DOR yields orbit accuracies comparable to conventional two-way Doppler tracking. For the interplanetary cruise phase, a tracking cycle consisting of a 3-hour Doppler pass and delta DOR (differential one-way range) from two baselines (one observation per overlap) acquired 3 times a month results in 100-km orbit determination accuracy. For reconstruction of a Venus flyby orbit, 10 days tracking at encounter consisting of continuous one-way Doppler and delta DOR sampled at one observation per overlap is sufficient to satisfy the accuracy requirements.
Ellis, J.↗
Venus Gravity Handbook
This report documents the Venus gravity methods and results to date (model MGNP90LSAAP). It is called a handbook in that it contains many useful plots (such as geometry and orbit behavior) that are useful in evaluating the tracking data. We discuss the models that are used in processing the Doppler data and the estimation method for determining the gravity field. With Pioneer Venus Orbiter and Magellan tracking data, the Venus gravity field was determined complete to degree and order 90 with the use of the JPL Cray T3D Supercomputer. The gravity field shows unprecedented high correlation with topography and resolution of features to the 2OOkm resolution. In the procedure for solving the gravity field, other information is gained as well, and, for example, we discuss results for the Venus ephemeris, Love number, pole orientation of Venus, and atmospheric densities. Of significance is the Love number solution which indicates a liquid core for Venus. The ephemeris of Venus is determined to an accuracy of 0.02 mm/s (tens of meters in position), and the rotation period to 243.0194 +/- 0.0002 days.
Konopliv, Alexander S.↗
Evaluation of spacecraft navigation using the Tracking and Data Relay Satellite System (TDRSS)
The navigational capabilities of the TDRSS for the operational support of user spacecraft is evaluated. A batch-weighted least-squares algorithm is used to fit tracking measurements and to generate orbit solutions for the TDRS-E spacecraft and the following user spacecraft: (1) the SMM, (2) the Landsat-5, (3) the Earth Radiation Budget Satellite (ERBS), and (4) the Solar Mesosphere Explorer (SME). TDRS-E orbit accuracy was evaluated by using the consistency of consecutive orbit solutions as a measure; user orbit accuracy was estimated by comparing orbits determined from TDRSS tracking with orbits obtained from ground tracking for the same time periods. It was found that the predicted accuracy of the TDRS-E orbit propagation was improved by as much as seven times by refining the spherical harmonic expansion model of the earth's potential field. The results obtained for SMM were fairly consistent, while those obtained for Landsat-5 were consistent to better than 80 meters. The orbits obtained using ERBS tracking were consistent to better than 60 meters and the SME orbits for two arcs with 14 and 20 passes of TDRSS tracking had a maximum position difference of 140 meters.
Samii, M. V.↗
Performance Assessment of LunaNet’s Augmented Forward Signal
LunaNet provides a common set of interoperable specifications for communication and position, navigation and time (PNT) services and interfaces soon to be implemented in lunar vicinity. The LunaNet Interoperability Specification (LNIS) provides the design for the GNSS-like Augmented Forward Signal (AFS), which enables orbiting and surface users in lunar space, such as Artemis, to estimate their position, velocity, and time. The specification of AFS defines two orthogonal signal components on a single carrier: the in-phase component (AFS-I), a lower-chip-rate data channel tailored for applications where low SWaP (Size, Weight, and Power) is critical (e.g., IoT devices or search and rescue), and the quadrature component (AFS-Q), a high-chip-rate data-less pilot signal for high-precision, robust lunar navigation and positioning applications. An initial description of AFS was provided in [1], with initial analysis results shown in [2] and [3] and the current signal in space description provided in [4]. As part of NASA's Lunar Communication Relay and Navigation Systems (LCRNS) project, this work expands upon the initial analysis results and proposes a new expanded set of AFS-Q spreading codes that exceed the cross-correlation and autocorrelation sidelobe performance of L1C and other GNSS signals, while providing additional expansion capabilities for future provider satellites. A set of 420 codes was selected from a Weil-based code derived from the prime number 10247, which is larger than the 10243 prime number used to derive Beidou’s B1C Weil sequences. Both the initial set of 210 codes and the expanded set of 420 codes are shown to provide the best cross-correlation of any 10230-chip satellite navigation codes. The performance is demonstrated for hierarchical sets of spreading codes optimized and organized in sets of 30 codes. The new codes were developed using an optimization approach and correlation methodology described in [5]. The work also compares LunaNet’s AFS to terrestrial GNSS signals in terms of acquisition, tracking, and data demodulation performance. Performance is evaluated for receivers that only track the 1.023 MCPS data channel spreading code for low SWaP IoT use cases, as well as for receivers that track both the 1.023 MCPS data channel and the 5.115 MCPS pilot channel spreading code for high-performance use cases. Performance is assessed in the presence of interference and thermal noise. The analysis is performed in terms of expected operating conditions on the lunar surface. Several unique flexibility aspects of the augmented forward signal are described, including the use of the Q channel’s secondary and tertiary codes to enable variable coherent integrations during acquisition. This is compared to GNSS signals such as L5/E5 and MBOC in terms of achievable processing gain for interference mitigation versus acquisition complexity. The work details acquisition and tracking techniques used to optimally acquire and track the primary, secondary, and tertiary codes on the Q channel, as well as acquisition of the I channel spreading code. Acquisition of the 8 ms Q channel spreading code is also compared to joint acquisition of the I and Q channel primary codes in noise and interference environments.
LCRNS↗
Performance Assessment of LunaNet’s Augmented Forward Signal
LunaNet provides a common set of interoperable specifications for communication and position, navigation and time (PNT) services and interfaces soon to be implemented in lunar vicinity. The LunaNet Interoperability Specification (LNIS) provides the design for the GNSS-like Augmented Forward Signal (AFS), which enables orbiting and surface users in lunar space, such as Artemis, to estimate their position, velocity, and time. The specification of AFS defines two orthogonal signal components on a single carrier: the in-phase component (AFS-I), a lower-chip-rate data channel tailored for applications where low SWaP (Size, Weight, and Power) is critical (e.g., IoT devices or search and rescue), and the quadrature component (AFS-Q), a high-chip-rate data-less pilot signal for high-precision, robust lunar navigation and positioning applications. An initial description of AFS was provided in LNIS 2023, with initial analysis results shown in Dafesh 2024 and Dafesh 2025, and the current signal in space description provided in LNIS 2025. As part of NASA's Lunar Communication Relay and Navigation Systems (LCRNS) project, this work expands upon the initial analysis results and proposes a new expanded set of AFS-Q spreading codes that exceed the cross-correlation and autocorrelation sidelobe performance of L1C and other GNSS signals, while providing additional expansion capabilities for future service satellites. A set of 420 codes was selected from a Weil-based code derived from the prime number 10247, which is larger than the 10243 prime number used to derive BeiDou’s B1C Weil sequences. Both the initial set of 210 codes and the expanded set of 420 codes are shown to provide the best cross-correlation of any 10230-chip satellite navigation codes. The performance is demonstrated for hierarchical sets of spreading codes optimized and organized in sets of 30 codes. The work also compares LunaNet’s AFS to terrestrial GNSS signals in terms of acquisition, tracking, and data demodulation performance. Performance is evaluated for receivers that only track the 1.023 MCPS data channel spreading code for low SWaP IoT use cases, as well as for receivers that track both the 1.023 MCPS data channel and the 5.115 MCPS pilot channel spreading code for high-performance use cases. Performance is assessed in the presence of interference and thermal noise. The analysis is performed in terms of expected operating conditions on the lunar surface. Several unique flexibility aspects of the augmented forward signal are described, including the use of the Q channel’s secondary and tertiary codes to enable variable coherent integrations during acquisition. This is compared to GNSS signals such as L5/E5 and MBOC in terms of achievable processing gain for interference mitigation versus acquisition complexity. The work details acquisition and tracking techniques used to optimally acquire and track the primary, secondary, and tertiary codes on the Q channel, as well as acquisition of the I channel spreading code. Acquisition of the 8 ms, Q channel spreading code is also compared to joint acquisition of the I and Q channel primary codes in noise and interference environments
LCRNS↗
Success of the Tracking and Data Relay Satellite System (TDRSS)
The paper provides historical data and presents two parameters for evaluating the success of the Tracking and Data Relay Satellite System (TDRSS). The TDRSS provides high rate data from missions such as the Shuttle and Landsats, and lower rate data from missions such as the Solar Mesosphere Explorer and the Earth Radiation Budget Satellite. Two parameters have been established as measurements of the ability of the system to transmit user commands and telemetry data, i.e., availability and proficiency. Availability is the system's readiness to support any and all user requirements 24 hours per day, 7 days per week. Proficiency is the ratio of actual support provided to scheduled support.
Harris, David W.↗
Evaluation of the Use of High Rate Tracking Data for Jason-3 GPS-Based Precise Orbit Determination
No abstract provided
Sibois, A.↗
JASON-1 Precise Orbit Determination (POD) Through the Combination and Comparison of GPS, SLR, DORIS and Altimeter Crossover Data
Jason-1, launched on December 7,2001, is continuing the time series of centimeter level ocean topography observations as the follow-on to the highly successful TOPEX/POSEIDON (T/P) radar altimeter satellite. The precision orbit determination (POD) is a critical component to meeting the ocean topography goals of the mission. T P has demonstrated that the time variation of ocean topography can be determined with an accuracy of a few centimeters, thanks to the availability of highly accurate orbits based primarily on SLR+DORIS tracking. The Jason-1 mission is intended to continue measurement of the ocean surface with the same, if not better accuracy. Fortunately, Jason- 1 POD can rely on four independent tracking data types available including near continuous tracking data from the dual frequency codeless BlackJack GPS receiver. Orbit solutions computed using individual and various combinations of GPS, SLR, DORIS and altimeter crossover data types have been determined from over 100 days of Jason-1 tracking data, The performance of the orbit solutions and tracking data has been evaluated. Orbit solution evaluation and comparison has provided insight into possible areas of refinement. Several aspects of the POD process are examined to obtain orbit improvements including measurement modeling, force modeling and solution strategy. The results of these analyses will be presented.
Luthcke, Scott B.↗