Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/22572
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Narkhede, P | - |
dc.contributor.author | Poddar, S | - |
dc.contributor.author | Walambe, R | - |
dc.contributor.author | Ghinea, G | - |
dc.contributor.author | Kotecha, K | - |
dc.date.accessioned | 2021-04-25T23:51:10Z | - |
dc.date.available | 2021-04-25T23:51:10Z | - |
dc.date.issued | 2021-03-10 | - |
dc.identifier | 1937 | - |
dc.identifier.citation | Narkhede, P., Poddar, S., Walambe, R., Ghinea, G. and Kotecha, K. (2021) 'Cascaded Complementary Filter Architecture for Sensor Fusion in Attitude Estimation', Sensors, 21 (6), 1937, pp. 1-18. doi: 10.3390/s21061937. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/22572 | - |
dc.description.abstract | Copyright: © 2021 by the authors. Attitude estimation is the process of computing the orientation angles of an object with respect to a fixed frame of reference. Gyroscope, accelerometer, and magnetometer are some of the fundamental sensors used in attitude estimation. The orientation angles computed from these sensors are combined using the sensor fusion methodologies to obtain accurate estimates. The complementary filter is one of the widely adopted techniques whose performance is highly dependent on the appropriate selection of its gain parameters. This paper presents a novel cascaded architecture of the complementary filter that employs a nonlinear and linear version of the complementary filter within one framework. The nonlinear version is used to correct the gyroscope bias, while the linear version estimates the attitude angle. The significant advantage of the proposed architecture is its independence of the filter parameters, thereby avoiding tuning the filter’s gain parameters. The proposed architecture does not require any mathematical modeling of the system and is computationally inexpensive. The proposed methodology is applied to the real-world datasets, and the estimation results were found to be promising compared to the other state-of-the-art algorithms. | en_US |
dc.format.extent | 1 - 18 | - |
dc.format.medium | Electronic | - |
dc.language.iso | en | en_US |
dc.publisher | MDPI | en_US |
dc.rights | Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | attitude estimation | en_US |
dc.subject | complementary filter | en_US |
dc.subject | gyroscope | en_US |
dc.subject | inertial sensors | en_US |
dc.subject | multistage filter | en_US |
dc.subject | sensor fusion | en_US |
dc.title | Cascaded complementary filter architecture for sensor fusion in attitude estimation | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.3390/s21061937 | - |
dc.relation.isPartOf | Sensors | - |
pubs.issue | 6 | - |
pubs.publication-status | Published | - |
pubs.volume | 21 | - |
dc.identifier.eissn | 1424-8220 | - |
Appears in Collections: | Dept of Computer Science Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
FullText.pdf | 3.18 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License