A FIR filter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localization
Abstract To improve the accuracy of the Ultra-Wide Band (UWB) based quadrotor aircraft localization, a Finite Impulse Response (FIR) filter aided with an integration of the predictive model and Extreme Learning Machine (ELM) is proposed in this work. The FIR filter estimates the quad-rotor aircraft...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-01-01
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| Series: | Satellite Navigation |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s43020-022-00091-1 |
| _version_ | 1797863295276810240 |
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| author | Yuan Xu Dong Wan Shuhui Bi Hang Guo Yuan Zhuang |
| author_facet | Yuan Xu Dong Wan Shuhui Bi Hang Guo Yuan Zhuang |
| author_sort | Yuan Xu |
| collection | DOAJ |
| description | Abstract To improve the accuracy of the Ultra-Wide Band (UWB) based quadrotor aircraft localization, a Finite Impulse Response (FIR) filter aided with an integration of the predictive model and Extreme Learning Machine (ELM) is proposed in this work. The FIR filter estimates the quad-rotor aircraft ’s position by fusing the positions measured with the UWB and Inertial Navigation System respectively. When the UWB dada are unavailable, both the ELM and the predictive model are used to provide the measurements, replacing those unavailable UWB data, for the FIR filter. The ELM estimates the measurement via the mapping between the one step prediction of state vector and the measurement built when the UWB data are available. For the predictive model, we mathematically describe the missing UWB data. Then, both the measurements estimated with the ELM and predictive model are employed to estimate the observations via Mahalanobis distance. The test results show that the FIR filter aided by the predictive model/ELM integrated can reduce the Cumulative Distribution Function and position Root Mean Square Error effectively when the UWB is unavailable. Compared with the ELM assisted FIR filter, the proposed FIR filter can reduce the localization error by about 48.59 %, meanwhile, the integrated method is close to the method with a better solution. Graphical Abstract |
| first_indexed | 2024-04-09T22:34:20Z |
| format | Article |
| id | doaj.art-d2553720ee7e46e7a8a11e09eaac92a5 |
| institution | Directory Open Access Journal |
| issn | 2662-9291 2662-1363 |
| language | English |
| last_indexed | 2024-04-09T22:34:20Z |
| publishDate | 2023-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Satellite Navigation |
| spelling | doaj.art-d2553720ee7e46e7a8a11e09eaac92a52023-03-22T12:37:38ZengSpringerOpenSatellite Navigation2662-92912662-13632023-01-014111210.1186/s43020-022-00091-1A FIR filter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localizationYuan Xu0Dong Wan1Shuhui Bi2Hang Guo3Yuan Zhuang4School of Electrical Engineering, University of JinanSchool of Electrical Engineering, University of JinanSchool of Electrical Engineering, University of JinanInstitute of Space Science and Technology, Nanchang UniversityState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan UniversityAbstract To improve the accuracy of the Ultra-Wide Band (UWB) based quadrotor aircraft localization, a Finite Impulse Response (FIR) filter aided with an integration of the predictive model and Extreme Learning Machine (ELM) is proposed in this work. The FIR filter estimates the quad-rotor aircraft ’s position by fusing the positions measured with the UWB and Inertial Navigation System respectively. When the UWB dada are unavailable, both the ELM and the predictive model are used to provide the measurements, replacing those unavailable UWB data, for the FIR filter. The ELM estimates the measurement via the mapping between the one step prediction of state vector and the measurement built when the UWB data are available. For the predictive model, we mathematically describe the missing UWB data. Then, both the measurements estimated with the ELM and predictive model are employed to estimate the observations via Mahalanobis distance. The test results show that the FIR filter aided by the predictive model/ELM integrated can reduce the Cumulative Distribution Function and position Root Mean Square Error effectively when the UWB is unavailable. Compared with the ELM assisted FIR filter, the proposed FIR filter can reduce the localization error by about 48.59 %, meanwhile, the integrated method is close to the method with a better solution. Graphical Abstracthttps://doi.org/10.1186/s43020-022-00091-1Ultra-Wide Band (UWB)Quadrotor aircraft localizationFIR filterELM |
| spellingShingle | Yuan Xu Dong Wan Shuhui Bi Hang Guo Yuan Zhuang A FIR filter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localization Satellite Navigation Ultra-Wide Band (UWB) Quadrotor aircraft localization FIR filter ELM |
| title | A FIR filter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localization |
| title_full | A FIR filter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localization |
| title_fullStr | A FIR filter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localization |
| title_full_unstemmed | A FIR filter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localization |
| title_short | A FIR filter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localization |
| title_sort | fir filter assisted with the predictive model and elm integrated for uwb based quadrotor aircraft localization |
| topic | Ultra-Wide Band (UWB) Quadrotor aircraft localization FIR filter ELM |
| url | https://doi.org/10.1186/s43020-022-00091-1 |
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