| Title: |
A Study about Kalman Filters Applied to Embedded Sensors |
| Authors: |
Valade, Aurelien; Acco, Pascal; Grabolosa, Pierre; Fourniols, Jean-Yves |
| Contributors: |
Équipe Instrumentation embarquée et systèmes de surveillance intelligents (LAAS-S4M); Laboratoire d'analyse et d'architecture des systèmes (LAAS); Université Toulouse Capitole (UT Capitole); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse); Institut National des Sciences Appliquées (INSA)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut National des Sciences Appliquées (INSA)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse - Jean Jaurès (UT2J); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse III - Paul Sabatier (UT3); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse Capitole (UT Capitole); Communauté d'universités et établissements de Toulouse (Comue de Toulouse); IMERIR; CCI des Pyrénées Orientales; Institut National des Sciences Appliquées - Toulouse (INSA Toulouse); Institut National des Sciences Appliquées (INSA)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse) |
| Source: |
ISSN: 1424-8220 ; Sensors ; https://hal.science/hal-01694026 ; Sensors, 2017, 17 (12), pp.2810. ⟨10.3390/s17122810⟩. |
| Publisher Information: |
CCSD; MDPI |
| Publication Year: |
2017 |
| Collection: |
Université Toulouse III - Paul Sabatier: HAL-UPS |
| Subject Terms: |
compensation; IMU; algorithm complexity; Kalman filters; smart sensors; [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing; [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]; [SPI.TRON]Engineering Sciences [physics]/Electronics |
| Description: |
International audience ; Over the last decade, smart sensors have grown in complexity and can now handle multiple measurement sources. This work establishes a methodology to achieve better estimates of physical values by processing raw measurements within a sensor using multi-physical models and Kalman filters for data fusion. A driving constraint being production cost and power consumption, this methodology focuses on algorithmic complexity while meeting real-time constraints and improving both precision and reliability despite low power processors limitations. Consequently, processing time available for other tasks is maximized. The known problem of estimating a 2D orientation using an inertial measurement unit with automatic gyroscope bias compensation will be used to illustrate the proposed methodology applied to a low power STM32L053 microcontroller. This application shows promising results with a processing time of 1.18 ms at 32 MHz with a 3.8% CPU usage due to the computation at a 26 Hz measurement and estimation rate |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.3390/s17122810 |
| Availability: |
https://hal.science/hal-01694026; https://hal.science/hal-01694026v1/document; https://hal.science/hal-01694026v1/file/sensors-17-02810-v2.pdf; https://doi.org/10.3390/s17122810 |
| Rights: |
info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.8398E42D |
| Database: |
BASE |