دورية أكاديمية
A novel Gaussian sum quaternion constrained cubature Kalman filter algorithm for GNSS/SINS integrated attitude determination and positioning system.
| العنوان: | A novel Gaussian sum quaternion constrained cubature Kalman filter algorithm for GNSS/SINS integrated attitude determination and positioning system. |
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| المؤلفون: | Dai Q; College of Urban Construction, Luoyang Polytechnic, Luoyang, China.; Institute of Geospatial Information, Information Engineering University, Zhengzhou, China., Xiao GR; Institute of Geospatial Information, Information Engineering University, Zhengzhou, China., Zhou GH; School of Information Engineering and Technology, Changzhou Vocational Institute of Industry Technology, Changzhou, China., Ye QQ; School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou, China., Han SY; School of Mathematics and Computer Science, Tongling University, Tongling, China.; College of Electrical Engineering, Zhejiang University, Hangzhou, China. |
| المصدر: | Frontiers in neurorobotics [Front Neurorobot] 2024 Jun 07; Vol. 18, pp. 1374531. Date of Electronic Publication: 2024 Jun 07 (Print Publication: 2024). |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101477958 Publication Model: eCollection Cited Medium: Print ISSN: 1662-5218 (Print) Linking ISSN: 16625218 NLM ISO Abbreviation: Front Neurorobot Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Original Publication: [Lausanne, Switzerland : Frontiers Research Foundation, 2007-] |
| مستخلص: | The quaternion cubature Kalman filter (QCKF) algorithm has emerged as a prominent nonlinear filter algorithm and has found extensive applications in the field of GNSS/SINS integrated attitude determination and positioning system (GNSS/SINS-IADPS) data processing for unmanned aerial vehicles (UAV). However, on one hand, the QCKF algorithm is predicated on the assumption that the random model of filter algorithm, which follows a white Gaussian noise distribution. The noise in actual GNSS/SINS-IADPS is not the white Gaussian noise but rather a ubiquitous non-Gaussian noise. On the other hand, the use of quaternions as state variables is bound by normalization constraints. When applied directly in nonlinear non-Gaussian system without considering normalization constraints, the QCKF algorithm may result in a mismatch phenomenon in the filtering random model, potentially resulting in a decline in estimation accuracy. To address this issue, we propose a novel Gaussian sum quaternion constrained cubature Kalman filter (GSQCCKF) algorithm. This algorithm refines the random model of the QCKF by approximating non-Gaussian noise with a Gaussian mixture model. Meanwhile, to account for quaternion normalization in attitude determination, a two-step projection method is employed to constrain the quaternion, which consequently enhances the filtering estimation accuracy. Simulation and experimental analyses demonstrate that the proposed GSQCCKF algorithm significantly improves accuracy and adaptability in GNSS/SINS-IADPS data processing under non-Gaussian noise conditions for Unmanned Aerial Vehicles (UAVs). Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 Dai, Xiao, Zhou, Ye and Han.) |
| References: | Micromachines (Basel). 2021 Jan 13;12(1):. (PMID: 33451172) Sensors (Basel). 2022 Jul 06;22(14):. (PMID: 35890765) Sensors (Basel). 2023 Feb 28;23(5):. (PMID: 36904872) |
| فهرسة مساهمة: | Keywords: GNSS/SINS integrated attitude determination and positioning system; Gaussian mixture model (GMM); Gaussian sum filter algorithm; nonlinear non-Gaussian system; quaternion cubature Kalman filter algorithm |
| تواريخ الأحداث: | Date Created: 20240624 Latest Revision: 20240625 |
| رمز التحديث: | 20240625 |
| مُعرف محوري في PubMed: | PMC11190174 |
| DOI: | 10.3389/fnbot.2024.1374531 |
| PMID: | 38911604 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1662-5218 |
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| DOI: | 10.3389/fnbot.2024.1374531 |