Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm
In our frequency scanning interferometry-based (FSI-based) absolute distance measurement system, a frequency sampling method is used to eliminate the influence of laser tuning nonlinearity. However, because the external cavity laser (ECL) has been used for five years, factors such as the mode hoppin...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Applied Sciences |
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| Online Access: | http://www.mdpi.com/2076-3417/8/10/1954 |
| _version_ | 1819063993218629632 |
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| author | Xing-Ting Xiong Xing-Hua Qu Fu-Min Zhang |
| author_facet | Xing-Ting Xiong Xing-Hua Qu Fu-Min Zhang |
| author_sort | Xing-Ting Xiong |
| collection | DOAJ |
| description | In our frequency scanning interferometry-based (FSI-based) absolute distance measurement system, a frequency sampling method is used to eliminate the influence of laser tuning nonlinearity. However, because the external cavity laser (ECL) has been used for five years, factors such as the mode hopping of the ECL and the low signal-to-noise ratio (SNR) in a non-cooperative target measurement bring new problems, including erroneous sampling points, phase jumps, and interfering signals. This article analyzes the impacts of the erroneous sampling points and interfering signals on the accuracy of measurement, and then proposes an adaptive filtering method to eliminate the influence. In addition, a phase-matching mosaic algorithm is used to eliminate the phase jump, and a segmentation mosaic algorithm is used to improve the data processing speed. The result of the simulation proves the efficiency of our method. In experiments, the measured target was located at eight different positions on a precise guide rail, and the incident angle was 12 degrees. The maximum deviation of the measured results between the FSI-based system and the He-Ne interferometer was 9.6 μm, and the maximum mean square error of our method was 2.4 μm, which approached the Cramer-Rao lower bound (CRLB) of 0.8 μm. |
| first_indexed | 2024-12-21T15:23:30Z |
| format | Article |
| id | doaj.art-e82d7be95b15484996bb259ba13bebd4 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-21T15:23:30Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-e82d7be95b15484996bb259ba13bebd42022-12-21T18:58:59ZengMDPI AGApplied Sciences2076-34172018-10-01810195410.3390/app8101954app8101954Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic AlgorithmXing-Ting Xiong0Xing-Hua Qu1Fu-Min Zhang2State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, ChinaIn our frequency scanning interferometry-based (FSI-based) absolute distance measurement system, a frequency sampling method is used to eliminate the influence of laser tuning nonlinearity. However, because the external cavity laser (ECL) has been used for five years, factors such as the mode hopping of the ECL and the low signal-to-noise ratio (SNR) in a non-cooperative target measurement bring new problems, including erroneous sampling points, phase jumps, and interfering signals. This article analyzes the impacts of the erroneous sampling points and interfering signals on the accuracy of measurement, and then proposes an adaptive filtering method to eliminate the influence. In addition, a phase-matching mosaic algorithm is used to eliminate the phase jump, and a segmentation mosaic algorithm is used to improve the data processing speed. The result of the simulation proves the efficiency of our method. In experiments, the measured target was located at eight different positions on a precise guide rail, and the incident angle was 12 degrees. The maximum deviation of the measured results between the FSI-based system and the He-Ne interferometer was 9.6 μm, and the maximum mean square error of our method was 2.4 μm, which approached the Cramer-Rao lower bound (CRLB) of 0.8 μm.http://www.mdpi.com/2076-3417/8/10/1954frequency scanning interferometryadaptive filtering methodmosaic algorithm |
| spellingShingle | Xing-Ting Xiong Xing-Hua Qu Fu-Min Zhang Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm Applied Sciences frequency scanning interferometry adaptive filtering method mosaic algorithm |
| title | Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm |
| title_full | Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm |
| title_fullStr | Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm |
| title_full_unstemmed | Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm |
| title_short | Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm |
| title_sort | error correction for fsi based system without cooperative target using an adaptive filtering method and a phase matching mosaic algorithm |
| topic | frequency scanning interferometry adaptive filtering method mosaic algorithm |
| url | http://www.mdpi.com/2076-3417/8/10/1954 |
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