Kalman Filter Based High Precision Temperature Data Processing Method

Autor: Xiaofeng Zhang, Hong Liang, Jianchao Feng, Heping Tan
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Frontiers in Energy Research, Vol 10 (2022)
Druh dokumentu: article
ISSN: 2296-598X
DOI: 10.3389/fenrg.2022.832346
Popis: Obtaining high precision temperature data is crucial in spaceflight applications, considering the growing demand for high precision temperature measurement and the limited onboard resources with a harsh thermal environment in the spacecraft. How to obtain the data, however, becomes an urgent problem. Kalman filtering method is one of the solutions to obtain high precision temperature data with such limited resources. In this paper, the authors demonstrate the principle of temperature measurement system, the application of Kalman filter in temperature measurement including the processing method of sensor self-heating effect, and establishes the state space of measurement error and system error. Through the test, it could be seen that Kalman filtering can improve the temperature measurement resolution to the order of 100 μK while effectively reducing the temperature measurement bias.
Databáze: Directory of Open Access Journals