A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations
In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more ac...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-05-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/5/1414 |
| _version_ | 1811305870058848256 |
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| author | Fangjun Qin Lubin Chang Sai Jiang Feng Zha |
| author_facet | Fangjun Qin Lubin Chang Sai Jiang Feng Zha |
| author_sort | Fangjun Qin |
| collection | DOAJ |
| description | In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms. |
| first_indexed | 2024-04-13T08:34:15Z |
| format | Article |
| id | doaj.art-22cf80001f6d4e2ca6336325aead4fb3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T08:34:15Z |
| publishDate | 2018-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-22cf80001f6d4e2ca6336325aead4fb32022-12-22T02:54:10ZengMDPI AGSensors1424-82202018-05-01185141410.3390/s18051414s18051414A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector ObservationsFangjun Qin0Lubin Chang1Sai Jiang2Feng Zha3Department of Navigation Engineering, Naval University of Engineering, Wuhan 430000, ChinaDepartment of Navigation Engineering, Naval University of Engineering, Wuhan 430000, ChinaOffice of Research and Development, Naval University of Engineering, Wuhan 430000, ChinaDepartment of Navigation Engineering, Naval University of Engineering, Wuhan 430000, ChinaIn this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms.http://www.mdpi.com/1424-8220/18/5/1414attitude estimationmultiplicative extended Kalman filtersequential estimation |
| spellingShingle | Fangjun Qin Lubin Chang Sai Jiang Feng Zha A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations Sensors attitude estimation multiplicative extended Kalman filter sequential estimation |
| title | A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations |
| title_full | A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations |
| title_fullStr | A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations |
| title_full_unstemmed | A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations |
| title_short | A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations |
| title_sort | sequential multiplicative extended kalman filter for attitude estimation using vector observations |
| topic | attitude estimation multiplicative extended Kalman filter sequential estimation |
| url | http://www.mdpi.com/1424-8220/18/5/1414 |
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