Data Processing And Experiment Of Barometric Altimeter Based On Recursive Least Squares Filtering

DOI

10.2991/jimec-17.2017.66How to use a DOI?

Keywords

barometric altimeter, data processing, recursive least squares filtering, height evaluation.

Abstract

It is an effective method to measure the height using a barometric altimeter, but there exists larger noise defect. In this paper, the height measurement system is designed by using the barometric pressure sensor, and the cause of noise is analyzed. In order to suppress the noise, the method of recursive least squares filtering is proposed to evaluate the measured height. A recursive least squares filter model is constructed and the recursive step is given, then the recursive method is applied to the height evaluation. An experiment is done to measure the floor height of a building, and the results show that the recursive least squares filtering method can make the evaluation data strictly track the original data change, the height measurement noise is suppressed effectively, and the height fluctuation reduces to 20% of the original measurement value.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaolei Wang
AU  - Shuangjian Yan
AU  - Linjiao Ren
AU  - Jitao Zhang
AU  - Xiaowan Zheng
AU  - Lingzhi Cao
PY  - 2017/10
DA  - 2017/10
TI  - Data Processing And Experiment Of Barometric Altimeter Based On Recursive Least Squares Filtering
BT  - Proceedings of the 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference (JIMEC 2017)
PB  - Atlantis Press
SP  - 299
EP  - 302
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimec-17.2017.66
DO  - 10.2991/jimec-17.2017.66
ID  - Wang2017/10
ER  -