Application of adaptive filtering algorithm based on wavelet transformation in aeromagnetic survey

Traditional method of compensating aircraft magnetic inference is complicated. In order to solve coefficients of inference, aircraft must have a box wide sides study flight before survey. However due to multi-collinearity of the traditional aircraft´s magnetic inference model, it is difficult to estimate the coefficient of model accurately, and the aircraft´s inference couldn´t be removed clearly. The adaptive filtering algorithm based on wavelet transformation uses result of wavelet transformation for measured magnetic signal to be the reference signal of adaptive filtering. The target signal isn´t correlated with noise, so the filter effect works well and the aircraft´s magnetic inference compensated well. The method could simplify the process of compensation and reduce the learning time in the air. By using this method to measured data, aeromagnetic survey could detect magnetic anomaly signal both aircraft in violent shaking and smooth flight without using any another equipment such as GPS.