A method for aircraft magnetic interference compensation based on small signal model and LMS algorit

• 作 者: Zhou Jianjun Lin Chunsheng Chen Hao
• 机 构: Department of Weapon Engineering, Naval University of Engineering,No. Unit 91922, People’ s Liberati
• 出 处: Chinese Journal of Aeronautics
• 发表日期: 2014年06期
• 关键词: Adaptive filter Aeromagnetic survey Aircraft magnetic interference Least mean sq

Aeromagnetic interference could not be compensated effectively if the precision of parameters which are solved by the aircraft magnetic field model is low. In order to improve the compensation effect under this condition, a method based on small signal model and least mean square(LMS) algorithm is proposed. According to the method, the initial values of adaptive filter’s weight vector are calculated with the solved model parameters through small signal model at first,then the small amount of direction cosine and its derivative are set as the input of the filter, and the small amount of the interference is set as the filter’s expected vector. After that, the aircraft magnetic interference is compensated by LMS algorithm. Finally, the method is verified by simulation and experiment. The result shows that the compensation effect can be improved obviously by the LMS algorithm when original solved parameters have low precision. The method can further improve the compensation effect even if the solved parameters have high precision.

Aeromagnetic interference could not be compensated effectively if the precision of parameters which are solved by the aircraft magnetic field model is low. In order to improve the compensation effect under this condition, a method based on small signal model and least mean square (LMS) algorithm is proposed. According to the method, the initial values ​​of adaptive filter’s weight vector are calculated with the solved model parameters through small signal model at first, then the small amount of direction cosine and its derivative are set as the input of the filter, and the small amount of the interference is set as the filter’s expected vector. After that, the aircraft magnetic interference is compensated by LMS algorithm. Finally, the method is verified by simulation and experiment. The result shows that the compensation effect can be improved obviously by the LMS algorithm when original solved parameters have low precision. The method can further improve the compensation effect even if the solved parameters have high precision.