Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Computationally Efficient Attitude Estimation for Small Satellites Using Integrated Measurements
Date
2024-01-01
Author
Benli, Dogukan
Söken, Halil Ersin
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
22
views
0
downloads
Cite This
Every year, computer processors are becoming more powerful and efficient. This progress allows for using less power for computing or more complex models for embedded systems, especially in aerospace. Nevertheless, computationally limited platforms still exist, and developing more capable and efficient algorithms for such platforms is an open research problem. This study aims to create and compare methods that reduce the computational load of onboard attitude estimation algorithms that use the Kalman Filter (KF) as the core algorithm. This is important for small satellites that have limited hardware and power consumption. An accurate attitude estimation algorithm that estimates additional parameters like sensor errors in real time can be beneficial for these resource-limited satellites. The study aims at reducing the number of KF updates without sacrificing the estimation accuracy by manipulating the measurements to get slower frequency pseudo-measurements. These measurements are called ”integrated measurements” and replace the original measurements in the filtering algorithm.
Subject Keywords
Attitude estimation
,
computational load
,
Estimation
,
Extraterrestrial measurements
,
Gyroscopes
,
integrated measurements
,
Kalman Filter
,
Measurement uncertainty
,
Small satellites
,
small satellites
,
Time measurement
,
Vectors
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85195396079&origin=inward
https://hdl.handle.net/11511/110276
Journal
IEEE Sensors Journal
DOI
https://doi.org/10.1109/jsen.2024.3404851
Collections
Department of Aerospace Engineering, Article
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
D. Benli and H. E. Söken, “Computationally Efficient Attitude Estimation for Small Satellites Using Integrated Measurements,”
IEEE Sensors Journal
, pp. 0–0, 2024, Accessed: 00, 2024. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85195396079&origin=inward.