Inertial MEMS Sensors Accuracy Improvement by Interval Fusion with Preference Aggregation
| Parent link: | SENSORS 2020: Conference Proceedings of IEEE Sensors 2020, October 25-28, Rotterdam, Netherlands. [4 p.].— , 2020 |
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| Ente Autore: | |
| Altri autori: | , , , |
| Riassunto: | Title screen To increase the accuracy of measurements in navigation systems, data from several MEMS sensors of the same type are traditionally processed to obtain the single value with minimal possible uncertainty. In this paper, it is proposed a method for precise processing of output data from inertial micro sensors based on the interval fusion with preference aggregation (IF&PA). The measurement data acquired from MEMS gyroscopes were processed by the IF&PA method. The results have shown that the proposed method allows to obtain the resulting estimate of the value with significantly lower uncertainty in comparison with traditional method. Thus, the IF&PA provides an opportunity to reduce the equipment cost without sacrificing the quality of measurement results. |
| Pubblicazione: |
2020
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| Soggetti: | |
| Accesso online: | https://doi.org/10.1109/SENSORS47125.2020.9278598 |
| Natura: | Elettronico Capitolo di libro |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=665070 |
| Riassunto: | Title screen To increase the accuracy of measurements in navigation systems, data from several MEMS sensors of the same type are traditionally processed to obtain the single value with minimal possible uncertainty. In this paper, it is proposed a method for precise processing of output data from inertial micro sensors based on the interval fusion with preference aggregation (IF&PA). The measurement data acquired from MEMS gyroscopes were processed by the IF&PA method. The results have shown that the proposed method allows to obtain the resulting estimate of the value with significantly lower uncertainty in comparison with traditional method. Thus, the IF&PA provides an opportunity to reduce the equipment cost without sacrificing the quality of measurement results. |
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| DOI: | 10.1109/SENSORS47125.2020.9278598 |