TY - GEN
T1 - Weight Estimation of Aircraft in Flight by Sensor Fusion with Revised Forward–Backward Smoother
AU - Ishikawa, Atsuya
AU - Naruoka, Masaru
AU - Ninomiya, Tetsujiro
AU - Adachi, Shuichi
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - Estimation of aircraft weight in flight, which is a dominant parameter related to its flight performance, was studied. A typical approach for the estimation is to use a simple combination of initial weight on the ground and fuel consumption in air obtained with fuel tank gauge or by accumulating fuel flow. This approach is insufficient when the flight performance will be estimated as accurately as possible because some of the available measurements are not utilized. Therefore, the forward–backward smoother derived from Kalman filter was applied to the estimation with our revision of the smoother to fuse terminal weight on the ground additionally. According to numerical simulations, our method estimated the weight in smaller errors than not only the typical approach but also a fixed-interval smoother, which is used generally for an off-line estimation problem. Moreover, application to actual flight data showed that our method improved the estimated standard deviation by approximately three percent at maximum compared to the fixed-interval smoother.
AB - Estimation of aircraft weight in flight, which is a dominant parameter related to its flight performance, was studied. A typical approach for the estimation is to use a simple combination of initial weight on the ground and fuel consumption in air obtained with fuel tank gauge or by accumulating fuel flow. This approach is insufficient when the flight performance will be estimated as accurately as possible because some of the available measurements are not utilized. Therefore, the forward–backward smoother derived from Kalman filter was applied to the estimation with our revision of the smoother to fuse terminal weight on the ground additionally. According to numerical simulations, our method estimated the weight in smaller errors than not only the typical approach but also a fixed-interval smoother, which is used generally for an off-line estimation problem. Moreover, application to actual flight data showed that our method improved the estimated standard deviation by approximately three percent at maximum compared to the fixed-interval smoother.
KW - Forward–backward smoother
KW - Sensor fusion
KW - Weight estimation
UR - http://www.scopus.com/inward/record.url?scp=85140436812&partnerID=8YFLogxK
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U2 - 10.1007/978-981-19-2635-8_59
DO - 10.1007/978-981-19-2635-8_59
M3 - Conference contribution
AN - SCOPUS:85140436812
SN - 9789811926341
T3 - Lecture Notes in Electrical Engineering
SP - 797
EP - 812
BT - The Proceedings of the 2021 Asia-Pacific International Symposium on Aerospace Technology APISAT 2021, Volume 2
A2 - Lee, Sangchul
A2 - Han, Cheolheui
A2 - Choi, Jeong-Yeol
A2 - Kim, Seungkeun
A2 - Kim, Jeong Ho
PB - Springer Science and Business Media Deutschland GmbH
T2 - Asia-Pacific International Symposium on Aerospace Technology, APISAT 2021
Y2 - 15 November 2021 through 17 November 2021
ER -