Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment
This paper presents a novel multiple strong tracking adaptive square-root cubature Kalman filter (MSTASCKF) based on the frame of the Sage–Husa filter, employing the multi-fading factor which could automatically adjust the Q value according to the rapidly changing noise in the flight process. This f...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-04-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/8/2597 |
| _version_ | 1797538453494169600 |
|---|---|
| author | Huanrui Zhang Xiaoyue Zhang |
| author_facet | Huanrui Zhang Xiaoyue Zhang |
| author_sort | Huanrui Zhang |
| collection | DOAJ |
| description | This paper presents a novel multiple strong tracking adaptive square-root cubature Kalman filter (MSTASCKF) based on the frame of the Sage–Husa filter, employing the multi-fading factor which could automatically adjust the Q value according to the rapidly changing noise in the flight process. This filter can estimate the system noise in real-time during the filtering process and adjust the system noise variance matrix Q so that the filtering accuracy is not significantly reduced with the noise. At the same time, the residual error in the filtering process is used as a measure of the filtering effect, and a multiple fading factor is introduced to adjust the posterior error variance matrix in the filtering process, so that the residual error is always orthogonal and the stability of the filtering is maintained. Finally, a vibration test is designed which simulates the random noise of the short-range guided weapon in flight through the shaking table and adds the noise to the present simulation trajectory for semi-physical simulation. The simulation results show that the proposed filter can significantly reduce the attitude estimation error caused by random vibration. |
| first_indexed | 2024-03-10T12:31:38Z |
| format | Article |
| id | doaj.art-21ba800aad7e4232a126bbd7c4ef1968 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T12:31:38Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-21ba800aad7e4232a126bbd7c4ef19682023-11-21T14:35:36ZengMDPI AGSensors1424-82202021-04-01218259710.3390/s21082597Robust SCKF Filtering Method for MINS/GPS In-Motion AlignmentHuanrui Zhang0Xiaoyue Zhang1School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, ChinaSchool of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, ChinaThis paper presents a novel multiple strong tracking adaptive square-root cubature Kalman filter (MSTASCKF) based on the frame of the Sage–Husa filter, employing the multi-fading factor which could automatically adjust the Q value according to the rapidly changing noise in the flight process. This filter can estimate the system noise in real-time during the filtering process and adjust the system noise variance matrix Q so that the filtering accuracy is not significantly reduced with the noise. At the same time, the residual error in the filtering process is used as a measure of the filtering effect, and a multiple fading factor is introduced to adjust the posterior error variance matrix in the filtering process, so that the residual error is always orthogonal and the stability of the filtering is maintained. Finally, a vibration test is designed which simulates the random noise of the short-range guided weapon in flight through the shaking table and adds the noise to the present simulation trajectory for semi-physical simulation. The simulation results show that the proposed filter can significantly reduce the attitude estimation error caused by random vibration.https://www.mdpi.com/1424-8220/21/8/2597robust filtering algorithmMIMUin-motion alignment |
| spellingShingle | Huanrui Zhang Xiaoyue Zhang Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment Sensors robust filtering algorithm MIMU in-motion alignment |
| title | Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment |
| title_full | Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment |
| title_fullStr | Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment |
| title_full_unstemmed | Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment |
| title_short | Robust SCKF Filtering Method for MINS/GPS In-Motion Alignment |
| title_sort | robust sckf filtering method for mins gps in motion alignment |
| topic | robust filtering algorithm MIMU in-motion alignment |
| url | https://www.mdpi.com/1424-8220/21/8/2597 |
| work_keys_str_mv | AT huanruizhang robustsckffilteringmethodforminsgpsinmotionalignment AT xiaoyuezhang robustsckffilteringmethodforminsgpsinmotionalignment |