A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm
Fiber optic gyroscope (FOG) is one of the important components of Inertial Navigation Systems (INS). In order to improve the accuracy of the INS, it is necessary to suppress the random error of the FOG signal. In this paper, a variational mode decomposition (VMD) denoising method based on beetle swa...
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MDPI AG
2020-07-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/22/7/765 |
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| author | Pengfei Wang Yanbin Gao Menghao Wu Fan Zhang Guangchun Li Chao Qin |
| author_facet | Pengfei Wang Yanbin Gao Menghao Wu Fan Zhang Guangchun Li Chao Qin |
| author_sort | Pengfei Wang |
| collection | DOAJ |
| description | Fiber optic gyroscope (FOG) is one of the important components of Inertial Navigation Systems (INS). In order to improve the accuracy of the INS, it is necessary to suppress the random error of the FOG signal. In this paper, a variational mode decomposition (VMD) denoising method based on beetle swarm antenna search (BSAS) algorithm is proposed to reduce the noise in FOG signal. Firstly, the BSAS algorithm is introduced in detail. Then, the permutation entropy of the band-limited intrinsic mode functions (BLIMFs) is taken as the optimization index, and two key parameters of VMD algorithm, including decomposition mode number <i>K</i> and quadratic penalty factor <inline-formula> <math display="inline"> <semantics> <mi>α</mi> </semantics> </math> </inline-formula>, are optimized by using the BSAS algorithm. Next, a new method based on Hausdorff distance (HD) between the probability density function (PDF) of all BLIMFs and that of the original signal is proposed in this paper to determine the relevant modes. Finally, the selected BLIMF components are reconstructed to get the denoised signal. In addition, the simulation results show that the proposed scheme is better than the existing schemes in terms of noise reduction performance. Two experiments further demonstrate the priority of the proposed scheme in the FOG noise reduction compared with other schemes. |
| first_indexed | 2024-03-10T18:31:03Z |
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| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T18:31:03Z |
| publishDate | 2020-07-01 |
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| spelling | doaj.art-e95e22cc3d894e419a13a2f11c80f83a2023-11-20T06:37:30ZengMDPI AGEntropy1099-43002020-07-0122776510.3390/e22070765A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search AlgorithmPengfei Wang0Yanbin Gao1Menghao Wu2Fan Zhang3Guangchun Li4Chao Qin5Collage of Automation, Harbin Engineering University, Harbin 150001, ChinaCollage of Automation, Harbin Engineering University, Harbin 150001, ChinaCollage of Automation, Harbin Engineering University, Harbin 150001, ChinaCollage of Automation, Harbin Engineering University, Harbin 150001, ChinaCollage of Automation, Harbin Engineering University, Harbin 150001, ChinaCollage of Automation, Harbin Engineering University, Harbin 150001, ChinaFiber optic gyroscope (FOG) is one of the important components of Inertial Navigation Systems (INS). In order to improve the accuracy of the INS, it is necessary to suppress the random error of the FOG signal. In this paper, a variational mode decomposition (VMD) denoising method based on beetle swarm antenna search (BSAS) algorithm is proposed to reduce the noise in FOG signal. Firstly, the BSAS algorithm is introduced in detail. Then, the permutation entropy of the band-limited intrinsic mode functions (BLIMFs) is taken as the optimization index, and two key parameters of VMD algorithm, including decomposition mode number <i>K</i> and quadratic penalty factor <inline-formula> <math display="inline"> <semantics> <mi>α</mi> </semantics> </math> </inline-formula>, are optimized by using the BSAS algorithm. Next, a new method based on Hausdorff distance (HD) between the probability density function (PDF) of all BLIMFs and that of the original signal is proposed in this paper to determine the relevant modes. Finally, the selected BLIMF components are reconstructed to get the denoised signal. In addition, the simulation results show that the proposed scheme is better than the existing schemes in terms of noise reduction performance. Two experiments further demonstrate the priority of the proposed scheme in the FOG noise reduction compared with other schemes.https://www.mdpi.com/1099-4300/22/7/765beetle swarm antenna search algorithmpermutation entropyvariational mode decompositionfiber optic gyroscopesignal denoising |
| spellingShingle | Pengfei Wang Yanbin Gao Menghao Wu Fan Zhang Guangchun Li Chao Qin A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm Entropy beetle swarm antenna search algorithm permutation entropy variational mode decomposition fiber optic gyroscope signal denoising |
| title | A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm |
| title_full | A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm |
| title_fullStr | A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm |
| title_full_unstemmed | A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm |
| title_short | A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm |
| title_sort | denoising method for fiber optic gyroscope based on variational mode decomposition and beetle swarm antenna search algorithm |
| topic | beetle swarm antenna search algorithm permutation entropy variational mode decomposition fiber optic gyroscope signal denoising |
| url | https://www.mdpi.com/1099-4300/22/7/765 |
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