Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensors
Abstract Aiming at the problem that the geomagnetic sensor is vulnerable to external interference in the navigation process, this paper analyzes the frequency distribution range of geomagnetic signal and the noise characteristics in geomagnetic signal and proposes an improved morphological filtering...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-02-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13634-023-00985-5 |
| _version_ | 1811165646497513472 |
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| author | Ping-an Zhang Min Gao Wei Wang Yi Wang Xu-jun Su |
| author_facet | Ping-an Zhang Min Gao Wei Wang Yi Wang Xu-jun Su |
| author_sort | Ping-an Zhang |
| collection | DOAJ |
| description | Abstract Aiming at the problem that the geomagnetic sensor is vulnerable to external interference in the navigation process, this paper analyzes the frequency distribution range of geomagnetic signal and the noise characteristics in geomagnetic signal and proposes an improved morphological filtering and Hilbert–Huang transform (IMMF–IHHT) algorithm to extract and recognize the features of geomagnetic measurement signal. To avoid frequency aliasing and distortion caused by empirical mode decomposition, an improved morphological filtering algorithm based on mean constraint is used to preprocess the measured signal. The Hilbert spectrum of the decomposed signal is solved, the signal components are discriminated by the similarity criterion, and the signal components in line with the frequency range of the geomagnetic signal are extracted and processed to reconstruct the geomagnetic measurement signal. Simulation and experiments show that the signal-to-noise ratio and root-mean-square error of IMMF–IHHT combination algorithm are better than MF-HHT combination algorithm and IHHT algorithm. This algorithm has good signal feature extraction and recognition ability. |
| first_indexed | 2024-04-10T15:41:10Z |
| format | Article |
| id | doaj.art-99c58d81b8bb4abc96fc5dfc8e7ee771 |
| institution | Directory Open Access Journal |
| issn | 1687-6180 |
| language | English |
| last_indexed | 2024-04-10T15:41:10Z |
| publishDate | 2023-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-99c58d81b8bb4abc96fc5dfc8e7ee7712023-02-12T12:25:56ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802023-02-012023112210.1186/s13634-023-00985-5Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensorsPing-an Zhang0Min Gao1Wei Wang2Yi Wang3Xu-jun Su4Shijiazhuang Campus of Army Engineering UniversityShijiazhuang Campus of Army Engineering UniversityShijiazhuang Campus of Army Engineering UniversityShijiazhuang Campus of Army Engineering UniversityShijiazhuang Campus of Army Engineering UniversityAbstract Aiming at the problem that the geomagnetic sensor is vulnerable to external interference in the navigation process, this paper analyzes the frequency distribution range of geomagnetic signal and the noise characteristics in geomagnetic signal and proposes an improved morphological filtering and Hilbert–Huang transform (IMMF–IHHT) algorithm to extract and recognize the features of geomagnetic measurement signal. To avoid frequency aliasing and distortion caused by empirical mode decomposition, an improved morphological filtering algorithm based on mean constraint is used to preprocess the measured signal. The Hilbert spectrum of the decomposed signal is solved, the signal components are discriminated by the similarity criterion, and the signal components in line with the frequency range of the geomagnetic signal are extracted and processed to reconstruct the geomagnetic measurement signal. Simulation and experiments show that the signal-to-noise ratio and root-mean-square error of IMMF–IHHT combination algorithm are better than MF-HHT combination algorithm and IHHT algorithm. This algorithm has good signal feature extraction and recognition ability.https://doi.org/10.1186/s13634-023-00985-5Geomagnetic sensorImproved morphological filtering (IMMF)Improved Hilbert–Huang transform (IHHT)Feature extraction and recognitionSimilarity criterion |
| spellingShingle | Ping-an Zhang Min Gao Wei Wang Yi Wang Xu-jun Su Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensors EURASIP Journal on Advances in Signal Processing Geomagnetic sensor Improved morphological filtering (IMMF) Improved Hilbert–Huang transform (IHHT) Feature extraction and recognition Similarity criterion |
| title | Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensors |
| title_full | Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensors |
| title_fullStr | Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensors |
| title_full_unstemmed | Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensors |
| title_short | Application of IMMF–IHHT algorithm to suppressing random interference of geomagnetic sensors |
| title_sort | application of immf ihht algorithm to suppressing random interference of geomagnetic sensors |
| topic | Geomagnetic sensor Improved morphological filtering (IMMF) Improved Hilbert–Huang transform (IHHT) Feature extraction and recognition Similarity criterion |
| url | https://doi.org/10.1186/s13634-023-00985-5 |
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