Engineering topics
Fesq, Lorraine
Publications and source records attributed to Fesq, Lorraine.
Satellite-To-Satellite Imaging in Support of LEO Optical Navigation, Using the ASTERIA Cubesat
The Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) was a 6-unit CubeSat technology demonstration mission that was built at NASA’s Jet Propulsion Laboratory (JPL) and deployed from the International Space Station (ISS) on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations alongside science until end of mission in December 2019. At the end of its lifetime it was being used as a demonstration platform for several experiments, including low earth orbit (LEO) optical navigation operations. With its visible light astrometric camera and stable attitude control system, the ASTERIA spacecraft showed itself to be a capable platform for the imaging of geosynchronous satellites from LEO. This paper will describe the imagery attained in flight and also the image processing algorithms that were developed to render that imagery into navigation quality data. These algorithms dealt with hot pixel filtering, noise modeling, attitude registration, star signal rejection and satellite signal identification. Brightness prediction algorithms used for target selection will also be discussed.
Satellite-to-satellite imaging in support of LEO optical navigation, using the ASTERIA cubesat
No abstract provided
Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission
Developers of robotic scientific and commercial spacecraft are trending towards use of onboard autonomous capabilities for responding quickly to dynamic environments and rapidly changing situations. These capabilities need to know the state of the spacecraft’s health. Model-based fault diagnosis (MBFD) is an approach to estimating health by continuously verifying accurate behavior and diagnosing off-nominal behavior. Proper functioning of MBFD depends on 1) the quality of the diagnostic system model that is analyzed and compared to commands and onboard measurements to estimate a system’s health state, and 2) the correct functionality of the diagnosis engine interrogating the model and comparing its analyses to observed system behavior. Our goal is to develop Verification and Validation (V&V) techniques for MBFD to provide future missions sufficient confidence in its functionality and performance to deploy it on the systems they develop. Our work has been focused on infusing the techniques we developed earlier to an operational mission. First, we are constructing diagnostic models of a spacecraft attitude control system and updating our diagnostic engine so they can be demonstrated aboard the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, an operational spacecraft for which experiments in autonomy are being planned and executed, using the V&V techniques we have previously developed to assure they are both correct and complete. Since it is nearing the end of its life, ASTERIA provides a unique opportunity to demonstrate MBFD since the monitored components are expected to fail. Our demonstration will give system developers additional confidence to make timely, informed MBFD deployment decisions. Second, we will be completing performance assessments of the diagnostic engine/diagnostic model ensemble both on the flight system and ground-based testbeds to gain confidence in MBFD’s ability to run successfully in a spacecraft’s resource-constrained environment without adversely affecting other on-board activities. Finally, we are capturing our experience in preparing this demonstration in a set of checklists and guidance documents. Current practice includes high-level institutional guidance documents and standards, but at a high level of abstraction that does not necessarily address specific MBFD concerns. The purpose of the new checklists is to provide future mission developers clear, unambiguous, procedure-oriented guidance on assuring MBFD. This paper describes our work in these areas. For the first area, we describe the diagnostic models and updated diagnostic engine that will be used for the on-board demonstration. We describe how the V&V techniques we developed earlier are used to assure model and engine correctness and completeness. For the second area, we identify the performance measurement and assessment techniques used to characterize the diagnostic engine and diagnostic models, and discuss the effect of measured performance on overall mission operation. Finally, we present the checklist and guidance documents and describe how they meet the goals of providing system developers with clear, unambiguous, procedure-oriented guidance on MBFD assurance. We show how the techniques we have developed map into those artifacts.
Extended mission technology demonstrations using the ASTERIA spacecraft
ASTERIA (Arcsecond Space Telescope Enabling Research In Astrophysics) is a CubeSat space telescope currently operating in low-Earth orbit. It is expected to remain in orbit at least through October 2019. Developed as a technology demonstration mission under the JPL Phaeton Program for training early-career engineers, ASTERIA has achieved sub-arcsecond pointing stability and milliKelvin thermal stability over 20-minute observations.
Assurance of Model-Based Fault Diagnosis
Autonomy is an increasingly important technology for robotic scientific and commercial spacecraft. An important motivation for developing onboard autonomy is to enable quick response to dynamic environment and situations, including fault conditions that a spacecraft may encounter. The reliability of such autonomous capabilities depends on the quality of their knowledge of a spacecraft’s health state. Model-based approaches to fault management, i.e. model-based fault diagnosis (MBFD), is one approach to continuously verify correct behavior in addition to diagnosing symptoms to estimate the spacecraft’s health state. The proper functioning of MBFD is dependent on 1) the quality of the model that is analyzed and compared to the outputs of onboard sensors to estimate the system’s health state, and 2) the correct functioning of the diagnosis engine that interrogates the model and compares its analysis to observed system behavior. We are currently developing Verification and Validation (V&V) approaches to provide the necessary confidence that MBFD systems are correctly estimating the health of on-board spacecraft components and systems. Our work is intended to narrow the gap between the rapidly maturing field of ModelBased System Engineering (including MBFD) and the less-well understood area of identifying and applying appropriate V&V techniques to MBFD. Our effort is investigating three areas: 1) developing V&V techniques for the diagnostic model, 2) developing V&V techniques for the diagnostic engine in isolation, and 3) developing V&V techniques for the diagnostic engine and model in combination. This paper describes the work we have completed in the first area. We describe our approach to selecting a system to be represented by a model, the approach to modeling the system, the verification approach we developed for the model, and the results of the verification activity. We conclude with a description of the work remaining in the last two areas, which will be addressed over the next two years.
Productivity Challenges for Mars Rover Operations
Achieving consistently high levels of productivity for surface exploration missions has been a challenge for Mars missions. While the rovers have made major discoveries and accomplished a large number of objectives, they often require a great deal of effort from the operations teams and achievingobjectives can take longer than anticipated. This paper describes the early stages of a multi-year project to investigate solutions for enhancing surface mission productivity. A primary focus of this early stage is to conduct in-depth studies of Mars Science Laboratory science campaigns to gain a deeper understanding of the factors that impact productivity, and to use this understanding to identify potential changes to flight software and ground operations practices to increase productivity. We present the science campaigns we have selected along with a conceptual model of how surface missions achieve objectives that is used to guide the study. We also provide some early thoughts on the technologies, and their interactions, which we believe will play an important role in addressing surface mission productivity challenges.We are in the early stages of a multi-year project to studyand address productivity challenges of future surface missions. We have identified campaigns from the MSL missionfor study which we believe will yield valuable informationabout the nature of surface mission productivity challenges.Based on preliminary analysis from the data collected weanticipate that the lessons from these case studies will helpdevelop and mature our concepts for changes to flight andground systems to address these challenges.While the focus of our work is on Mars rover missions, webelieve the concepts in the work will be applicable to a variety of in-situ explorers, including Venus, and Titan, as wellas orbital missions, such as the Europa orbiter. These missions will also benefit from the ability to adapt and respondto the latest state of the spacecraft and its environment.
Quality Attributes for Mission Flight Software: A Reference for Architects
No abstract available
Quality Attributes for Mission Flight Software: A Reference for Architects
In the international standards for architecture descriptions in systems and software engineering (ISO/IEC/IEEE 42010), "concern" is a primary concept that often manifests itself in relation to the quality attributes or "ilities" that a system is expected to exhibit - qualities such as reliability, security and modifiability. One of the main uses of an architecture description is to serve as a basis for analyzing how well the architecture achieves its quality attributes, and that requires architects to be as precise as possible about what they mean in claiming, for example, that an architecture supports "modifiability." This paper describes a table, generated by NASA's Software Architecture Review Board, which lists fourteen key quality attributes, identifies different important aspects of each quality attribute and considers each aspect in terms of requirements, rationale, evidence, and tactics to achieve the aspect. This quality attribute table is intended to serve as a guide to software architects, software developers, and software architecture reviewers in the domain of mission-critical real-time embedded systems, such as space mission flight software.
Fault Management Architectures and the Challenges of Providing Software Assurance
The satellite systems Fault Management (FM) is focused on safety, the preservation of assets, and maintaining the desired functionality of the system. How FM is implemented varies among missions. Common to most is system complexity due to a need to establish a multi-dimensional structure across hardware, software and operations. This structure is necessary to identify and respond to system faults, mitigate technical risks and ensure operational continuity. These architecture, implementation and software assurance efforts increase with mission complexity. Because FM is a systems engineering discipline with a distributed implementation, providing efficient and effective verification and validation (VV) is challenging. A breakout session at the 2012 NASA Independent Verification Validation (IVV) Annual Workshop titled VV of Fault Management: Challenges and Successes exposed these issues in terms of VV for a representative set of architectures. NASA's IVV is funded by NASA's Software Assurance Research Program (SARP) in partnership with NASA's Jet Propulsion Laboratory (JPL) to extend the work performed at the Workshop session. NASA IVV will extract FM architectures across the IVV portfolio and evaluate the data set for robustness, assess visibility for validation and test, and define software assurance methods that could be applied to the various architectures and designs. This work focuses efforts on FM architectures from critical and complex projects within NASA. The identification of particular FM architectures, visibility, and associated VVIVV techniques provides a data set that can enable higher assurance that a satellite system will adequately detect and respond to adverse conditions. Ultimately, results from this activity will be incorporated into the NASA Fault Management Handbook providing dissemination across NASA, other agencies and the satellite community. This paper discusses the approach taken to perform the evaluations and preliminary findings from the research including identification of FM architectures, visibility observations, and methods utilized for VVIVV.