SMAP Instrument Antenna, on Orbit Performance Validation and Verification
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NASA’s Soil Moisture Active Passive (SMAP) Mission is currently flying in a 685 km orbit. Featuring a Synthetic Aperture Radar (SAR) and a radiometer sharing the same antenna, SMAP was developed in collaboration between Jet Propulsion Laboratory (JPL) and Goddard Space Flight Center (GSFC). While the radar requirements on the instrument antenna were more benign from an RF point of view, the radiometer requirement were more difficult to meet because of the stability required by the radiometer to operate to its full potential. The instrument antenna performance was predicted by a very detailed RF model and verified by measuring a 1/10th scale model with great accuracy before launch. Once in orbit, we had the opportunity to measure the antenna performance for both the radiometer and the radar and compare it with the predicted performance given by our RF model. This paper discusses the work done both at JPL and GSFC in order to verify and validate the on orbit performance of the SMAP instrument antenna.
NASA’s Soil Moisture Active Passive (SMAP) Mission is currently flying in a 685 km orbit. Featuring a Synthetic Aperture Radar (SAR) and a radiometer sharing the same antenna, SMAP was developed in collaboration between Jet Propulsion Laboratory (JPL) and Goddard Space Flight Center (GSFC). While the radar requirements on the instrument antenna were more benign from an RF point of view, the radiometer requirement were more difficult to meet because of the stability required by the radiometer to operate to its full potential. The instrument antenna performance was predicted by a very detailed RF model and verified by measuring a 1/10th scale model with great accuracy before launch. Once in orbit, we had the opportunity to measure the antenna performance for both the radiometer and the radar and compare it with the predicted performance given by our RF model. This paper discusses the work done both at JPL and GSFC in order to verify and validate the on orbit performance of the SMAP instrument antenna.
The NASA Orbital Debris Engineering Model (ORDEM) 3.1 Model Verification and Validation (V&V) document accompanies the delivery of the latest ORDEM 3.1 model (Vavrin & Manis, 2019) and provides a detailed description of the V&V activities used to verify that the model was built correctly and validate the model against independent, real world sources of data obtained from sampling the orbital debris environment. This ORDEM 3.1 Model V&V document, along with the related ORDEM 3.1 Model Process document – which covers details of the mathematical, statistical, and physical basis of the model – are intended to inform credibility assessments, risk analyses, uncertainty characterizations, and other applications derived from use of the model by the ORDEM 3.1 user community.
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The NASA Orbital Debris Program Office has developed the Orbital Debris Engineering Model (ORDEM) primarily as a tool for spacecraft designers and other users to understand the long-term risk of collisions with orbital debris. The newest version, ORDEM 3.1, incorporates the latest and highest fidelity datasets available to build and validate representative orbital debris populations encompassing low Earth orbit (LEO) to geosynchronous orbit (GEO) altitudes for the years 2016-2050. ORDEM 3.1 models fluxes for object sizes > 10 μm within or transiting LEO and > 10 cm in GEO. The deterministic portion of the populations in ORDEM 3.1 is based on the U.S. Space Surveillance Network (SSN) catalog, which provides coverage down to approximately 10 cm in LEO and 1 m in GEO. Observational datasets from radar, in situ, and optical sources provide a foundation from which the model populations are statistically extrapolated to smaller sizes and orbit regions that are not well-covered by the SSN catalog, yet may pose the greatest threat to operational spacecraft. Objects in LEO ranging from approximately 5 mm to 10 cm are modeled using observational data from ground-based radar, namely the Haystack Ultrawideband Satellite Imaging Radar (HUSIR – formerly known as Haystack). The LEO population smaller than approximately 3 mm in size is characterized based on a reanalysis of in situ data from impacts to the windows and radiators of the U.S. Space Transportation System orbiter vehicle, i.e., the Space Shuttle. Data from impacts on the Hubble Space Telescope are also used to validate the sub-millimeter model populations in LEO. Debris in GEO with sizes ranging from 10 cm to 1 m is modeled using optical measurement data from the Michigan Orbital DEbris Survey Telescope (MODEST). Specific, major debris-producing events, including the Fengyun-1C, Iridium 33, and Cosmos 2251 debris clouds, and unique populations, such as sodium-potassium droplets, have been re-examined and are modeled and added to the ORDEM environment separately. The debris environment greater than 1 mm is forecast using NASA’s LEO-to- GEO ENvironment Debris model (LEGEND). Future explosions of intact objects and collisions involving objects greater than 10 cm are assessed statistically, and the NASA Standard Satellite Breakup Model is used to generate fragments from these events. Fragments smaller than 10 cm are further differentiated based on material density categories, i.e., high-, medium-, and low-density, to better characterize the potential debris risk posed to spacecraft. The future projection of the sub-millimeter environment is computed using a special small-particle degradation model where small particles are created from intact spacecraft and rocket bodies. This work discusses the development, features, and capabilities of the ORDEM 3.1 model; the ne new data analyses used to build the model populations; and sample verification and validation results.
The SCaN Testbed is an advanced integrated communications system and laboratory facility installed on the International Space Station (ISS) in 2012. The testbed incorporates a set of new generation of Software Defined Radio (SDR) technologies intended to allow researchers to develop, test, and demonstrate new communications, networking, and navigation capabilities in the actual environment of space. Qascom, in cooperation with ESA and NASA, is designing a Software Defined Radio GalileoGPS Receiver capable to provide accurate positioning and timing to be installed on the ISS SCaN Testbed. The GalileoGPS waveform will be operated in the JPL SDR that is constituted by several hardware components that can be used for experimentations in L-Band and S-Band. The JPL SDR includes an L-Band Dorne Margolin antenna mounted onto a choke ring. The antenna is connected to a radio front end capable to provide one bit samples for the three GNSS frequencies (L1, L2 and L5) at 38 MHz, exploiting the subharmonic sampling. The baseband processing is then performed by an ATMEL AT697 processor (100 MIPS) and two Virtex 2 FPGAs. The JPL SDR supports the STRS (Space Telecommunications Radio System) that provides common waveform software interfaces, methods of instantiation, operation, and testing among different compliant hardware and software products. The standard foresees the development of applications that are modular, portable, reconfigurable, and reusable. The developed waveform uses the STRS infrastructure-provided application program interfaces (APIs) and services to load, verify, execute, change parameters, terminate, or unload an application. The project is divided in three main phases. 1)Design and Development of the GalileoGPS waveform for the SCaN Testbed starting from Qascom existing GNSS SDR receiver. The baseline design is limited to the implementation of the single frequency Galileo and GPS L1E1 receiver even if as part of the activity it will be to assess the feasibility of a dual frequency implementation (L1E1+L5E5a) in the same SDR platform.2)Qualification and test the GalileoGPS waveform using ground systems available at the NASA Glenn Research Center. Experimenters can have access to two SCaN Testbed ground based systems for development and verification: the Experimenter Development System (EDS) that is intended to provide initial opportunity for software testing and basic functional validation and the Ground Integration Unit (GIU) that is a high fidelity version of the SCaN Testbed flight system and is therefore used for more controlled final development testing and verification testing.3)Perform in-orbit validation and experimentation: The experimentation phase will consists on the collection of raw measurements (pseudorange, Carrier phase, CN0) in space, assessment on the quality of the measurements and the receiver performances in terms of signal acquisition, tracking, etc. Finally computation of positioning in space (Position, Velocity and time) and assessment of its performance.(Complete abstract in attached document).
The SCaN Testbed is an advanced integrated communications system and laboratory facility installed on the International Space Station (ISS) in 2012. The testbed incorporates a set of new generation of Software Defined Radio (SDR) technologies intended to allow researchers to develop, test, and demonstrate new communications, networking, and navigation capabilities in the actual environment of space. Qascom, in cooperation with ESA and NASA, is designing a Software Defined Radio GalileoGPS Receiver capable to provide accurate positioning and timing to be installed on the ISS SCaN Testbed. The GalileoGPS waveform will be operated in the JPL SDR that is constituted by several hardware components that can be used for experimentations in L-Band and S-Band. The JPL SDR includes an L-Band Dorne Margolin antenna mounted onto a choke ring. The antenna is connected to a radio front end capable to provide one bit samples for the three GNSS frequencies (L1, L2 and L5) at 38 MHz, exploiting the subharmonic sampling. The baseband processing is then performed by an ATMEL AT697 processor (100 MIPS) and two Virtex 2 FPGAs. The JPL SDR supports the STRS (Space Telecommunications Radio System) that provides common waveform software interfaces, methods of instantiation, operation, and testing among different compliant hardware and software products. The standard foresees the development of applications that are modular, portable, reconfigurable, and reusable. The developed waveform uses the STRS infrastructure-provided application program interfaces (APIs) and services to load, verify, execute, change parameters, terminate, or unload an application. The project is divided in three main phases. 1)Design and Development of the GalileoGPS waveform for the SCaN Testbed starting from Qascom existing GNSS SDR receiver. The baseline design is limited to the implementation of the single frequency Galileo and GPS L1E1 receiver even if as part of the activity it will be to assess the feasibility of a dual frequency implementation (L1E1+L5E5a) in the same SDR platform.2)Qualification and test the GalileoGPS waveform using ground systems available at the NASA Glenn Research Center. Experimenters can have access to two SCaN Testbed ground based systems for development and verification: the Experimenter Development System (EDS) that is intended to provide initial opportunity for software testing and basic functional validation and the Ground Integration Unit (GIU) that is a high fidelity version of the SCaN Testbed flight system and is therefore used for more controlled final development testing and verification testing.3)Perform in-orbit validation and experimentation: The experimentation phase will consists on the collection of raw measurements (pseudorange, Carrier phase, CN0) in space, assessment on the quality of the measurements and the receiver performances in terms of signal acquisition, tracking, etc. Finally computation of positioning in space (Position, Velocity and time) and assessment of its performance.(Complete abstract in attached document).
Planetary protection (PP) policy seeks to avoid harmful contamination by limiting biological and relevant organic contamination from spacecraft as well as preventing adverse changes to Earth’s biosphere when extraterrestial samples are brought back to Earth. The PP policy at NASA was updated in 2021 (NPR 8715.24) and 2022 (NASA-STD-8719.27) to enable missions by expanding the decades old prescriptive requirements to allow for an option of adopting performance-based requirements that are objectivesdriven, risk-informed and case-assured. In parallel, the final PP knowledge gap workshop was completed representing the international consensus on the key areas to be considered in developing crew PP policy. These knowledge gaps focused on key technology development areas in 1) microbial and human health monitoring, 2) technical and operations needed for contamination control and 3) natural transport of contamination on Mars. As robotic missions start to implement performance-based approaches and research and technology efforts commence to inform crew policy the demand for data quality driven verification and validation in relevant space environments. Examples of the types of testing that is envisioned includes test as you fly validation and verification of decontamination systems in a relevant on-orbit and Mars environment, developing lethality curves of terrestrial organisms to further our understanding of the biocidal impacts of Mars and the space environment, and particle transport model validation and verification. Thus, the PP discipline has identified the need for groundbased space environments to perform preliminary testing as validation and verification of flight systems and to advance the technology readiness level prior to further testing on-orbit or lunar environments to prepare for Mars.
Planetary protection (PP) policy seeks to avoid harmful contamination by limiting biological and relevant organic contamination from spacecraft as well as preventing adverse changes to Earth’s biosphere when extraterrestrial samples are brought back to Earth. The PP policy at NASA was updated in 2021 (NPR 8715.24) and 2022 (NASA-STD-8719.27) to enable missions by expanding the decades old prescriptive requirements to allow for an option of adopting performance-based requirements that are objectives-driven, risk-informed and case-assured. In parallel, the final PP knowledge gap workshop was completed representing the international consensus on the key areas to be considered in developing crew PP policy. These knowledge gaps focused on key technology development areas in 1) microbial and human health monitoring, 2) technical and operations needed for contamination control and 3) natural transport of contamination on Mars. As robotic missions start to implement performance-based approaches and research and technology efforts commence to inform crew policy the demand for data quality driven verification and validation in relevant space environments. Examples of the types of testing that is envisioned includes test as you fly validation and verification of decontamination systems in a relevant on-orbit and Mars environment, developing lethality curves of terrestrial organisms to further our understanding of the biocidal impacts of Mars and the space environment, and particle transport model validation and verification. Thus, the PP discipline has identified the need for ground-based space environments to perform preliminary testing as validation and verification of flight systems and to advance the technology readiness level prior to further testing on-orbit or lunar environments to prepare for Mars.
An outline of this work is presented. It begins with a schematic flow diagram and a logical flow diagram of the identification process for large space structures (LSS). Next, the task is defined by a structure model definition. A matrix polynomial formulation with a node displacement equation and a state variable formulation with node displacement and velocities are outlined. Further outlined is the identification of LSS on orbit; modeling errors and uncertainties; verification and validation of model; and noise, computations, and data collection.
The Lunar Atmosphere Dust Environment Explorer (LADEE) mission orbited the moon in order to measure the density, composition, and time variability of the lunar dust environment. The successful mission launched September 7, 2013 and was de-orbited and impacted the moon's surface on April 17, 2014. The ground-side and onboard flight software for the mission was developed using a “Model-Based Software Engineering” (MBSE) methodology combined with strong reuse of Government and Commercial Off-The Shelf (G/COTS) components. Models of the spacecraft and flight software were developed in a graphical dynamics modeling package. Flight Software requirements were prototyped and refined using the simulated models. After the model was shown to work as desired in the simulation framework, C-code software was automatically generated from the models. The auto-generated software was then tested in real-time Processor-in-the-Loop and Hardware-in-the-Loop test beds. “Traveling Road Show” test beds were used for early integration tests with payloads and other subsystems. Traditional techniques for verifying computational sciences models were used to characterize the spacecraft simulation. A lightweight set of formal methods analysis, static analysis, formal inspection, and code coverage analyses were utilized to further reduce defects in the onboard flight software artifacts. These techniques were applied early and often in the development process, iteratively increasing the capabilities of software and fidelity of vehicle models and test beds.
The TOPEX/POSEIDON mission objective requires that the radial position of the spacecraft be determined with an accuracy better than 13 cm RMS (root mean square). This stringent requirement is an order of magnitude below the accuracy achieved for any altimeter mission prior to the definition of the TOPEX/POSEIDON mission. To satislfy this objective, the TOPEX Precision Orbit determination (POD) Team was established as a joint effort between the NASA Goddard Space Flight Center and the University of Texas at Austin, with collaboration from the University of Colorado and the Jet Propulsion Laboratory. During the prelaunch development and the post launch verification phases, the POD team improved, calibrated, and validated the precision orbit determination computer software systems. The accomplishments include (1) increased accuracy of the gravity and surface force models and (2) improved peformance of both laser ranging and Doppler tracking systems. The result of these efforts led to orbit accuracies for TOPEX/POSEIDON which are significantly better than the original mission requirement. Tests based on data fits, covariance analysis, and orbit comparisons indicate that the radial component of the TOPEX/POSEIDON spacecraft is determined, relative to the Earth's mass center, with an root mean square (RMS) error in the range of 3 to 4 cm RMS. This orbit accuracy, together with the near continuous dual-frequency altimetry from this mission, provides the means to determine the ocean's dynamic topography with an unprecedented accuracy.
During the Orbiter Repair Maneuver (ORM) operations planned for Return to Flight (RTF), the Shuttle Remote Manipulator System (SRMS) must grapple the International Space Station (ISS), undock the Orbiter, maneuver it through a long duration trajectory, and orient it to an EVA crewman poised at the end of the Space Station Remote Manipulator System (SSRMS) to facilitate the repair of the Thermal Protection System (TPS). Once repair has been completed and confirmed, then the SRMS proceeds back through the trajectory to dock the Orbiter to the Orbiter Docking System. In order to support analysis of the complex dynamic interactions of the integrated system formed by the Orbiter, ISS, SRMS, and SSMS during the ORM, simulation tools used for previous ‘nominal’ mission support required substantial enhancements. These upgrades were necessary to provide analysts with the capabilities needed to study integrated system performance. Prevalent throughout this ORM operation is a dynamically varying topology. In other words, the ORM starts with the SRMS grappled to the mated Shuttle/ISS stack (closed loop topology), moves to an open loop chain topology consisting of the Shuttle, SRMS, and ISS, and then, at the repair configuration, extends the chain topology to one consisting of the Shuttle, SMS, ISS, and SSRMS/EVA crewman. The resulting long dynamic chain of vehicles and manipulators may exhibit significant motion between the Shuttle worksite and the EVA crewman due to the system flexibility throughout the topology (particularly within the SRMS/SSRMS joints and links). Since the attachment points of both manipulators span the flexible structure of the ISS, simulation analysis may also need to take that into consideration. Moreover, due to the lengthy time duration associated with the maneuver and repair, orbital effects become a factor and require the ISS vehicle control system to maintain active attitude control. Several facets of the ORM operation make the associated analytical efforts different from previous mission support, including: (1) the magnitude of the SRMS handled payload (Le., Orbiter class), (2) the orbital effects induced on the integrated system consisting of the large Shuttle and ISS masses connected by a light flexible SRMS, (3) long duration environmental consequences due to the lengthy operational times associated with the maneuver and repair of the TPS, (4) active attitude control (as opposed to free drift) interacting with the SRMS and SSRMS manipulators (also due to the length of the maneuver and repair), (5) relative dynamics between the EVA crewman and thc worksite influenced by the extended flexible topology. In order to meet these analysis challenges, an ORM simulation architecture was developed leveraging upon numerous pre-existing simulation elements to analyze the various subsystems individually. For example, core manipulator subsystem simulations for both the SRMS and SSRMS were originally combined to provide the dual-arm dynamics topology simulation (in the absence of orbital dynamics and vehicle control). This capability was later merged with the simulation used to analyze SRMS loading with a heavy payload in the orbital environment with an active payload control system (in this case, the ISS Attitude Control System (ACS)), configured for the ORM. The resulting worksite dynamics simulation, based off of the modified ORM simulation, provided the extended topological chain of vehicles and manipulators, while taking into account the orbital effects of both the Shuttle and ISS (as well as its ACS). Verification and validation (V&V) of these integrated simulations became a challenge in itself. A systematic approach needed to be developed such that integration simulation results could be tested against previous constituent simulations upon which these simulations were built. General V&V categories included: (1) core orbital state propagation, (2), stand-alone SRMS, (3) stand-alone SSRMS, (4) stand-alone ISS ACS, (5) integrated Shuttle, SRMS, ISS (with active ACS) in the orbital environment, and (5) dual-arm SRMS/SSRMS dynamics topology. Integrated simulation V&V run suites were created and correlated to verification runs from subsystem simulations, in order to establish the validity of the results. This paper discusses the simulation design challenges encountered while developing simulation capabilities to mirror the ORM operations. The paper also describes the incremental build approach that was utilized, starting with the subsystem simulation elements and integration into increasing more complex simulations until the resulting ORM worksite dynamics simulation had been assembled. Furthermore, the paper presents an overall integrated simulation V&V methodology based upon a subsystem level testing, integrated comparisons, and phased checkout.
Recent NASA mission failures (e.g., Mars Polar Lander and Mars Orbiter) illustrate the importance of having an efficient verification and validation process for such systems. One software error, as simple as it may be, can cause the loss of an expensive mission, or lead to budget overruns and crunched schedules. Unfortunately, traditional verification methods cannot guarantee the absence of errors in software systems. Therefore, we have developed the CGS static program analysis tool, which can exhaustively analyze large C programs. CGS analyzes the source code and identifies statements in which arrays are accessed out of bounds, or, pointers are used outside the memory region they should address. This paper gives a high-level description of CGS and its theoretical foundations. It also reports on the use of CGS on real NASA software systems used in Mars missions (from Mars PathFinder to Mars Exploration Rover) and on the International Space Station.
The HZETRN code has been identified by NASA for engineering design in the next phase of space exploration highlighting a return to the Moon in preparation for a Mars mission. In response, a new series of algorithms beginning with 2005 HZETRN, will be issued by correcting some prior limitations and improving control of propagated errors along with established code verification processes. Code validation processes will use new/improved low Earth orbit (LEO) environmental models with a recently improved International Space Station (ISS) shield model to validate computational models and procedures using measured data aboard ISS. These validated models will provide a basis for flight-testing the designs of future space vehicles and systems of the Constellation program in the LEO environment.
The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key environmental remote-sensing instruments onboard the Suomi National Polar-Orbiting Partnership spacecraft, which was successfully launched on October 28, 2011 from the Vandenberg Air Force Base, California. Following a series of spacecraft and sensor activation operations, the VIIRS nadir door was opened on November 21, 2011. The first VIIRS image acquired signifies a new generation of operational moderate resolution-imaging capabilities following the legacy of the advanced very high-resolution radiometer series on NOAA satellites and Terra and Aqua Moderate-Resolution Imaging Spectroradiometer for NASA's Earth Observing system. VIIRS provides significant enhancements to the operational environmental monitoring and numerical weather forecasting, with 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns, providing the sensor data records for 23 environmental data records including aerosol, cloud properties, fire, albedo, snow and ice, vegetation, sea surface temperature, ocean color, and nigh-time visible-light-related applications. Preliminary results from the on-orbit verification in the postlaunch check-out and intensive calibration and validation have shown that VIIRS is performing well and producing high-quality images. This paper provides an overview of the onorbit performance of VIIRS, the calibration/validation (cal/val) activities and methodologies used. It presents an assessment of the sensor initial on-orbit calibration and performance based on the efforts from the VIIRS-SDR team. Known anomalies, issues, and future calibration efforts, including the long-term monitoring, and intercalibration are also discussed.
The Lunar Atmosphere Dust Environment Explorer (LADEE) mission will orbit the moon in order to measure the density, composition and time variability of the lunar dust environment. The ground-side and onboard flight software for the mission is being developed using a Model-Based Software methodology. In this technique, models of the spacecraft and flight software are developed in a graphical dynamics modeling package. Flight Software requirements are prototyped and refined using the simulated models. After the model is shown to work as desired in this simulation framework, C-code software is automatically generated from the models. The generated software is then tested in real time Processor-in-the-Loop and Hardware-in-the-Loop test beds. Travelling Road Show test beds were used for early integration tests with payloads and other subsystems. Traditional techniques for verifying computational sciences models are used to characterize the spacecraft simulation. A lightweight set of formal methods analysis, static analysis, formal inspection and code coverage analyses are utilized to further reduce defects in the onboard flight software artifacts. These techniques are applied early and often in the development process, iteratively increasing the capabilities of the software and the fidelity of the vehicle models and test beds.