Robert Rasmussen

Software architecture themes in JPL's Mission Data System

The rising frequency of NASA mission launches has highlighted the need for improvements leading to faster delivery of mission software without sacrificing reliability. In April 1998 Jet Propulsion Laboratory (JPL) initiated the Mission Data System (MDS) project to rethink the mission software lifecycle-from early mission design to mission operation-and make changes to improve software architecture and software development processes. As a result, MDS has defined a unified flight, ground, and test data system architecture for space missions based on object-oriented design, component architecture, and specific frameworks. This paper describes architectural themes shaping the MDS design and how they help meet objectives for faster, better, cheaper mission software.

Software architecture themes in JPL's mission data system

Hardware

Spacecraft electronics design for radiation tolerance

Current design practices are described and future trends in spacecraft electronics which are likely to alter traditional approaches are discussed. A summary of radiation effects and radiation tolerance requirements typically levied on spacecraft designs is provided. Methods of dealing with radiation and testability issues are considered. >

An Architectural Pattern for Goal-Based Control

Time-based command sequencing is the traditional paradigm for control of spacecraft and rovers in NASAs robotic missions, but this paradigm has been increasingly strained to accommodate todays missions. Goal-based control is a new paradigm that supports time-driven and event-driven operation in a more natural way and permits a melding of sequencing and fault protection into a single control paradigm. This paper describes one approach to goal-based control as an architectural pattern in terms of purpose, motivation, structure, applicability, and consequences. This paper is intended to help flight and ground software engineers understand the new paradigm and how it compares to time-based sequencing.

Model Based Systems Engineering on the Europa mission concept study

At the start of 2011, the proposed Jupiter Europa Orbiter (JEO) mission was staffing up in expectation of becoming an official project later in the year for a launch in 2020. A unique aspect of the pre-project work was a strong emphasis and investment on the foundations of Model-Based Systems Engineering (MBSE). As so often happens in this business, plans changed: NASAs budget and science priorities were released and together fundamentally changed the course of JEO. As a result, it returned to being a study task whose objective is to propose more affordable ways to accomplish the science. As part of this transition, the question arose as to whether it could continue to afford the investment in MBSE. In short, the MBSE infusion has survived and is providing clear value to the study effort. In the process, the need to remain relevant in the new environment has brought about a wave of innovation and progress. By leveraging the existing infrastructure and a modest additional investment, striking advances in the capture and analysis of designs using MBSE were achieved. The effort has reaffirmed the importance of architecting. It has successfully harnessed the synergistic relationship of architecting to system modeling. We have found that MBSE can provide greater agility than traditional methods. We have also found that a diverse ‘ecosystem’ of modeling tools and languages (SysML, Mathematica, even Excel) is not only viable, but an important enabler of agility and adaptability. This paper will describe the successful application of MBSE in the dynamic environment of early mission formulation, the significant results produced and lessons learned in the process.

A unifying framework for systems modeling, control systems design, and system operation

Current engineering practice in the analysis and design of large-scale multi-disciplinary control systems is typified by some form of decomposition - whether functional or physical or discipline-based - that enables multiple teams to work in parallel and in relative isolation. Too often, the resulting system after integration is an awkward marriage of different control and data mechanisms with poor end-to-end accountability. System of systems engineering, which faces this problem on a large scale, cries out for a unifying framework to guide analysis, design, and operation. This paper describes such a framework for semi-autonomous control systems that guides analysis and modeling, shapes control system software design, and directly specifies operational intent. This paper illustrates the key concepts in the context of a large-scale, concurrent, globally distributed system of systems: NASAs proposed array-based Deep Space Network.

A UML profile for State Analysis

State Analysis is a systems engineering methodology for the specification and design of control systems, developed at the Jet Propulsion Laboratory. The methodology emphasizes an analysis of the system under control in terms of States and their properties and behaviors and their effects on each other, a clear separation of the control system from the controlled system, cognizance in the control system of the controlled systems State, goal-based control built on constraining the controlled systems States, and disciplined techniques for State discovery and characterization.

Modeling relationships using graph state variables

The Mission Data System is a unified flight, ground, simulation, and test software system for space missions. Currently, its first application will be the Mars Smart Lander mission, where common MDS software frameworks will be adapted for use in interplanetary cruise, entry-descent-landing, and rover operations. A key architectural theme of MDS is explicit modeling of states. This provides a sound foundation for estimation, control, and data analysis. Certain essential states are relative rather than absolute. Relative states are defined in graph state variables (GSVs) as relationships between nodes in a graph. GSVs are a general graph-based state representation that (1) derives a states value by combining relationships, (2) produces different results for different derivation paths, (3) handles changes to topology and relationships between nodes, and (4), represents dependencies between relationships (e.g. correlations). This paper shows example GSV representations for spacecraft orientation, location, trajectories, dynamics, and kinematics.

Computing in the Presence of Soft Bit Errors

The phenomenon of cosmic-ray-induced logic state changes has violated an article of faith among programmers that computers are predictable. This is a relatively new problem, and no fully acceptable response to it yet exists. It is a topic that spacecraft computer and software designers must understand. The source of the problem, its effects, solutions, influence on fault-tolerant designs, and thoughts on the impact of future technology are discussed.

Building operability into the Jupiter Europa Orbiter design to endure a high radiation environment

The Europa Jupiter System Mission (EJSM) has been prioritized as the next Outer Planets Flagship Mission that would be devoted to exploring the emergence of habitable worlds around gas giants. This joint NASA and ESA endeavor would focus on the Galilean moons Europa and Ganymede but would also investigate Io, Callisto, and the Jupiter system as a whole. The NASA-contributed Jupiter Europa Orbiter (JEO) and the ESA-contributed Jupiter Ganymede Orbiter (JGO) would be launched on separate launch vehicles in 2020. Here we focus on JEO. 12