Modified "Current" Statisical Model Filtering Algorithm for Carrier Acceleration Calculation

DOI

10.2991/caai-17.2017.67How to use a DOI?

Keywords

airborne gravimetry; carrier acceleration; interacting multiple model; fuzzy adaptive; "current" statistical model

Abstract

Carrier acceleration is an important factor that influences the solution of the gravity anomaly in airborne gravimetry. The development of the airborne gravimetry has put forward a higher requirement to carrier acceleration. Considering the complex case of high-flying carrier in airborne gravimetry, in order to improve the solution accuracy of carrier acceleration, this paper adopt the Kalman filter method based on "Current" Statistical Model to solve the problem. For the characteristics of carrier acceleration. The fuzzy membership function and the Interacting Multiple Model algorithm are used to adjust the acceleration limits and motor frequencies of the "Current" Statistical Model. An improved "Current" Statistical Model algorithm is proposed to solve the carrier acceleration of airborne gravimetry, and then the filtering results are smoothed by the RTS smoothing. Finally, the proposed algorithm is validated by simulation experiments, the simulation results show that the proposed method is superior than the existing method position differential method in solving carrier acceleration, and the solution accuracy is improved greatly.

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  - Zhaolong Zhang
AU  - Yuegang Wang
AU  - Honglei Teng
AU  - Le Wang
PY  - 2017/06
DA  - 2017/06
TI  - Modified "Current" Statisical Model Filtering Algorithm for Carrier Acceleration Calculation
BT  - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 296
EP  - 299
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.67
DO  - 10.2991/caai-17.2017.67
ID  - Zhang2017/06
ER  -