Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman Filter
The objective of the research is to undergo a performance comparison in terms of accuracy, convergence time, amount of memory, etc. between the satellite attitude determination and attitude estimation using non-linear filters. The fundamental approach towards it is to design an OBC (On Board Compute...
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| Format: | Article |
| Language: | English |
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National Institute for Aerospace Research “Elie Carafoli” - INCAS
2021-06-01
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| Series: | INCAS Bulletin |
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| Online Access: | https://bulletin.incas.ro/files/raja-m__vol_13_iss_2.pdf |
| _version_ | 1818597450345086976 |
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| author | M. RAJA |
| author_facet | M. RAJA |
| author_sort | M. RAJA |
| collection | DOAJ |
| description | The objective of the research is to undergo a performance comparison in terms of accuracy, convergence time, amount of memory, etc. between the satellite attitude determination and attitude estimation using non-linear filters. The fundamental approach towards it is to design an OBC (On Board Computer) that would help in achieving a controlled output for the chosen plant (MicroMAS1 satellite). The attitude determination algorithm is implemented through TRIAD algorithm, which takes sensor readings of body frame and inertial frame of reference. Then it is used to determine the rotation matrix (DCM) by converting the matrix form into vector form and again back to matrix form to determine the 3x3 matrix, which includes all the Euler angle equations to determine the pitch, roll, yaw characteristics of the system. The attitude estimation algorithms involves the use of nonlinear filters which provide an added advantage that energy can be transferred in a designed manner and extra degrees of freedom are available in filter design. The Unscented Kalman Filter (UKF) is preferred as it addresses the problem using a deterministic sampling approach. Moreover, the non-linear filters are used to remove the noise error and disturbance caused by engine. The design of satellite attitude models involves more of a mathematical approach that would be dealt with MATLAB and SIMULINK operations. |
| first_indexed | 2024-12-16T11:48:00Z |
| format | Article |
| id | doaj.art-6590ea7e3365417fbc7c6ce0f773c4ee |
| institution | Directory Open Access Journal |
| issn | 2066-8201 2247-4528 |
| language | English |
| last_indexed | 2024-12-16T11:48:00Z |
| publishDate | 2021-06-01 |
| publisher | National Institute for Aerospace Research “Elie Carafoli” - INCAS |
| record_format | Article |
| series | INCAS Bulletin |
| spelling | doaj.art-6590ea7e3365417fbc7c6ce0f773c4ee2022-12-21T22:32:47ZengNational Institute for Aerospace Research “Elie Carafoli” - INCASINCAS Bulletin2066-82012247-45282021-06-0113211713210.13111/2066-8201.2021.13.2.12Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman FilterM. RAJA0Aerospace Department, University of Petroleum and Energy Studies, Bidholi, Dehradun -248007, Uttarakhand, India, mraja@ddn.upes.ac.inThe objective of the research is to undergo a performance comparison in terms of accuracy, convergence time, amount of memory, etc. between the satellite attitude determination and attitude estimation using non-linear filters. The fundamental approach towards it is to design an OBC (On Board Computer) that would help in achieving a controlled output for the chosen plant (MicroMAS1 satellite). The attitude determination algorithm is implemented through TRIAD algorithm, which takes sensor readings of body frame and inertial frame of reference. Then it is used to determine the rotation matrix (DCM) by converting the matrix form into vector form and again back to matrix form to determine the 3x3 matrix, which includes all the Euler angle equations to determine the pitch, roll, yaw characteristics of the system. The attitude estimation algorithms involves the use of nonlinear filters which provide an added advantage that energy can be transferred in a designed manner and extra degrees of freedom are available in filter design. The Unscented Kalman Filter (UKF) is preferred as it addresses the problem using a deterministic sampling approach. Moreover, the non-linear filters are used to remove the noise error and disturbance caused by engine. The design of satellite attitude models involves more of a mathematical approach that would be dealt with MATLAB and SIMULINK operations.https://bulletin.incas.ro/files/raja-m__vol_13_iss_2.pdfattitude determinationnon-linear filterskalman algorithmeuler angle |
| spellingShingle | M. RAJA Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman Filter INCAS Bulletin attitude determination non-linear filters kalman algorithm euler angle |
| title | Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman Filter |
| title_full | Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman Filter |
| title_fullStr | Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman Filter |
| title_full_unstemmed | Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman Filter |
| title_short | Comparative Analysis of Low Earth Orbit Satellite Attitude Determination using Sensor Integration and Attitude Estimation using Kalman Filter |
| title_sort | comparative analysis of low earth orbit satellite attitude determination using sensor integration and attitude estimation using kalman filter |
| topic | attitude determination non-linear filters kalman algorithm euler angle |
| url | https://bulletin.incas.ro/files/raja-m__vol_13_iss_2.pdf |
| work_keys_str_mv | AT mraja comparativeanalysisoflowearthorbitsatelliteattitudedeterminationusingsensorintegrationandattitudeestimationusingkalmanfilter |