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2022 | 2 |

Article title

Impact of the Static Pressure Measurement Accuracy on Barometric Altimeter Errors

Content

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Languages of publication

Abstracts

EN
The horizontal movement of the pressure sensor in relation to air masses may cause erroneous indications of the altimeter due to the possible measurement of the total pressure, which is the sum of the static and dynamic pressure. This problem mainly concerns devices of small dimensions equipped with barometric altimeters made in MEMS technology, performing complex movements. Small dimensions make it difficult to arrange the pressure intake slots in a way that ensures the measurement of static pressure. Examples include drones (UAH) or bike computers. The aim of the research was to develop an altitude correction formula depending on the speed of the pressure sensor relative to air, which, contrary to those found in the literature, would take into account changes in air density with altitude. The theoretical analysis of the influence of the speed of movement on the indications of the barometric altimeter was evaluated in this paper based on the standard atmosphere model. Methods of correcting errors caused by the measurement of total pressure were proposed. The effectiveness of the proposed methods was verified with simulations (Matlab). Experimental studies were also carried out, which confirmed the theoretical considerations. The experiments performed showed that the problem of correcting errors caused by incorrect measurement of static pressure is very complex. The inertia of the barometer indications plays an important role. The direction of airflow and pressure distribution on the flowing object are also important. The results presented in this paper can be used in the design of systems that improve the quality of barometric altimeter readings. This is particularly important when designing low-budget drone navigation systems and it will improve flight safety.

Year

Volume

2

Physical description

Dates

published
2022

Contributors

  • Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland
author
  • Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland
author
  • Faculty of Transport and Aviation Engineering, The Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland

References

  • 1. Diston D.J. (2009). Computational Modelling and Simulation of Aircraft and the Environment: Platform Kinematics and Synthetic Environment. Volume 1. John Wiley & Sons, Ltd.
  • 2. Lin C.E., Huang W.-C., & Nien C.-C. (2011). MEMS-Based Air Data Unit with Real Time Correction for UAV Terrain Avoidance. Journal of Aeronautics, Astronautics and Aviation, Series A, Vol. 43, No.2 pp.103 – 110. https://www.researchgate.net/publication/224358008.
  • 3. Sabatini A. M., & Genovese V. (2013). A Stochastic Approach to Noise Modeling for Barometric Altimeters, Sensors, Vol.13, No.11, pp.15692-15707. DOI: 10.3390/s131115692
  • 4. Pressure and temperature sensor BMP280. Available online: https://www.bosch-sensortec.com/media/boschsensortec/downloads/datasheets/bst-bmp280-ds001.pdf (accessed on 30 January 2022).
  • 5. U.S. Standard Atmosphere (1976). U.S. Government Printing Office, Washington, D.C.
  • 6. Nakanishi, H., Kanata S., & Sawaragi T. (2012). GPS-INS BARO hybrid navigation system taking into account ground effect for autonomous unmanned helicopter, IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 1-6. DOI: 10.1109/SSRR.2012.6523885.
  • 7. Popowski S.,& Dąbrowski W. (2008). An Integrated Measurement of Altitude and Vertical Speed for UAV. Transport and Engineering. Transport. Aviation Transport. Scientific Proceedings of Riga Technical University, Series 6, N27. pp.197-205. Riga, RTU.
  • 8. Seo J., Lee J. G., & Park C.G. (2004). Bias suppression of GPS measurement in inertial navigation system vertical channel, Position Location and Navigation Symposium, pp. 143-147. DOI: 10.1109/PLANS.2004.1308986.
  • 9. Whang I-H., & Ra W. S. (2007). Barometer error identification filter design using sigma point hypotheses, International Conference on Control, Automation and Systems, pp. 1410-1415. DOI: 10.1109/ICCAS.2007.4406559.
  • 10. Bao X., Xiong Z., Sheng S., Dai Y., Bao S., & Liu J. (2017). Barometer Measurement Error Modeling and Correction for UAH Altitude Tracking. 29th Chinese Control and Decision Conference (CCDC). pp.3166-3171. DOI:10.1109/CCDC.2017.7979052

Document Type

Publication order reference

Identifiers

Biblioteka Nauki
2174782

YADDA identifier

bwmeta1.element.ojs-doi-10_37105_sd_184
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