Investigating Formation Flying and COTS in an Integrated Simulation Environment
Bibliographic record
Abstract
The Canadian Space Agency’s (CSA) Software and Ground Segment (SGS) section has the mandate to develop innovative software and ground segment technologies. The implementation of formation flying concepts for Canadian missions is also currently under investigation at CSA's Spacecraft Engineering section. To that end, there is an ongoing development of a simulation environment to test COTS (Commercial-Off-The-Shelf) and formation flying technologies. Some of today's spacecraft are laboriously custom designed for a specific mission and a limited set of tasks. Development time can be lengthy (several years), which means that designs do not take advantage of the most recent technology. Designs also tend to be extremely inflexible, creating a spacecraft that cannot be easily adapted to future missions. A design ethic that promotes reusability is much more cost-effective and increases the time available to advance new technologies. COTS offer advantages such as a reduced development time, an increased product selection, faster and cheaper parts replacement, and extensively tested advanced designs. The main drawbacks to COTS use in space are susceptibility to radiation and in some cases decreased reliability. Since one of the main advantages of formation flying is the reduced mission sensitivity to a spacecraft failure, the risk associated with COTS, which has hindered its use in conventional space missions, is less concerning in the context of a multiple spacecraft mission. Achieving some level of standardization is a problem currently confronting the space industry, which must be addressed to realize the cost savings that can come from mass production and spacecraft interoperability. The use of standard components with standard interfaces also reduces development time. As well, since part of the goal is to have spacecraft already in orbit regroup and possibly join with new spacecraft to accomplish other missions, some forwards and backwards compatibility between generations of spacecraft will be necessary. This paper describes an integrated simulation environment that uses COTS spacecraft and simulation components to investigate formation flying scenarios and their benefits and challenges. A few of the well-known industry software and hardware tools incorporated into the environment include Analytical Graphic's STK, Mathwork's Matlab/Simulink, CAE Electronic's Real-time Object-Oriented Simulation Environment (ROSETM), Intel's StrongARM processor, and the PC-104 architecture for rugged embedded systems. There are short term plans to incorporate goal decomposition hierarchies to implement autonomous operations and robust fault tolerance. This will be implemented on high-speed logic based controller cards, known as Q4 cards, developed by Xiphos Technologies Inc. The simulation environment was developed to allow spacecraft designers or mission operators to test their respective technologies or ideas in a modular structure rapidly, accurately, and cheaply. This will enhance the successful use of formation flying spacecraft and improve the technologies needed to make formation flying a feasible and a cost effective reality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".