Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/92765
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Aeronautical and Aviation Engineering | en_US |
dc.creator | Dou, J | en_US |
dc.creator | Xu, B | en_US |
dc.creator | Dou, L | en_US |
dc.date.accessioned | 2022-05-16T09:07:38Z | - |
dc.date.available | 2022-05-16T09:07:38Z | - |
dc.identifier.issn | 0030-4026 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/92765 | - |
dc.language.iso | en | en_US |
dc.publisher | Urban & Fischer | en_US |
dc.rights | © 2020 Elsevier GmbH. All rights reserved. | en_US |
dc.rights | ©2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.rights | The following publication Dou, J., Xu, B., & Dou, L. (2020). An intelligent joint filter for vector tracking loop considering noise interference. Optik, 219, 164984 is available at https://doi.org/10.1016/j.ijleo.2020.164984. | en_US |
dc.subject | Extended Kalman filter (EKF) | en_US |
dc.subject | Gaussian mixture model (GMM) clustering | en_US |
dc.subject | Global Navigation Satellite System (GNSS) | en_US |
dc.subject | Joint filter (JF) | en_US |
dc.subject | Unbiased finite-impulse response (UFIR) filter | en_US |
dc.subject | Vector tracking loop (VTL) | en_US |
dc.title | An intelligent joint filter for vector tracking loop considering noise interference | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 219 | en_US |
dc.identifier.doi | 10.1016/j.ijleo.2020.164984 | en_US |
dcterms.abstract | In this paper, we propose an intelligent joint filter (JF) for enhancing the performance of vector tracking loop (VTL) in the Global Navigation Satellite System (GNSS). The JF combines the advantages of extended Kalman filter (EKF) and unbiased finite-impulse response (UFIR) filter. To this end, a supervised machine learning algorithm, named Gaussian mixture model (GMM) clustering, was used for providing excellent joint strategy. Those three types of filter-based vector tracking loop were first implemented and then processed with a set of raw satellite signals based on the software-defined receiver (SDR). Finally, comparative analyses and results of the tracking performance of EKF/UFIR/JF were carried out. Results show that the EKF-VTL has optimal tracking performance but sensitive to the noise statistics, which means it's not robust. The UFIR-VTL is suboptimal but more robust compare to EKF-VTL. The proposed JF-VTL is both optimal and robust. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Optik, Oct. 2020, v. 219, 164984 | en_US |
dcterms.isPartOf | Optik | en_US |
dcterms.issued | 2020-10 | - |
dc.identifier.scopus | 2-s2.0-85086468263 | - |
dc.identifier.eissn | 1618-1336 | en_US |
dc.identifier.artn | 164984 | en_US |
dc.description.validate | 202205 bckw | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | AAE-0074 | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Natural Science Foundation of China; Foundation of National Key Laboratory of Transient Physics; Foundation of Defence Technology Innovation Special Filed | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 42726247 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Xu_Intelligent_Joint_Filter.pdf | Pre-Published version | 1.35 MB | Adobe PDF | View/Open |
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