Difference between revisions of "Sequoia GNC"
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| Write Script to Evaluate Kalman Filter Performance || A Kalman Filter is an algorithm that takes a series of noisy measurements from multiple sources over time, adds in some physics and probability theory, and estimates the current state of the satellite, with uncertainties. Currently, we have an in-progress code that simulates the physics of the sattilite's rotation and a Kalman filter that gets simulated measurements from that code and estimates the orientation of the satellite. However, we need a code that runs the Kalman filter multiple times in different scenarios and evaluates its performance. This will be needed as we progress with the Kalman Filter development to evaluate its performance and identify problems. || Basic knowledge of coding (particularly Python), physics, and probability theory are helpful, but by no means necessary. We expect that this project will be a good chance to learn about these. | | Write Script to Evaluate Kalman Filter Performance || A Kalman Filter is an algorithm that takes a series of noisy measurements from multiple sources over time, adds in some physics and probability theory, and estimates the current state of the satellite, with uncertainties. Currently, we have an in-progress code that simulates the physics of the sattilite's rotation and a Kalman filter that gets simulated measurements from that code and estimates the orientation of the satellite. However, we need a code that runs the Kalman filter multiple times in different scenarios and evaluates its performance. This will be needed as we progress with the Kalman Filter development to evaluate its performance and identify problems. || Basic knowledge of coding (particularly Python), physics, and probability theory are helpful, but by no means necessary. We expect that this project will be a good chance to learn about these. | ||
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| − | | | + | | Write Code to Simulate Star Images to test the Star Tracker || Example || Example |
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| Example || Example || Example | | Example || Example || Example | ||
Revision as of 19:53, 22 August 2020
This page describes the architecture for the Guidance, Navigation, and Control (GNC) system for the Sequoia project. Since this system is primarily focused on determining and controlling attitude, we also may refer to it as ADCS.
Sequoia GNC Onboarding
No matter what background you have, you can contribute to Sequoia GNC! You can learn about the intersection between physics, CS, and engineering and especially control theory. Here's a few aspects of our system we currently need someone to work on:
| Chose a Project! | Background | Skills/Knowledge Involved |
|---|---|---|
| Write Script to Evaluate Kalman Filter Performance | A Kalman Filter is an algorithm that takes a series of noisy measurements from multiple sources over time, adds in some physics and probability theory, and estimates the current state of the satellite, with uncertainties. Currently, we have an in-progress code that simulates the physics of the sattilite's rotation and a Kalman filter that gets simulated measurements from that code and estimates the orientation of the satellite. However, we need a code that runs the Kalman filter multiple times in different scenarios and evaluates its performance. This will be needed as we progress with the Kalman Filter development to evaluate its performance and identify problems. | Basic knowledge of coding (particularly Python), physics, and probability theory are helpful, but by no means necessary. We expect that this project will be a good chance to learn about these. |
| Write Code to Simulate Star Images to test the Star Tracker | Example | Example |
| Example | Example | Example |
Overview of Sequoia GNC Architecture
