A De-noising Method of Airborne Location Data Based on the Improved Wavelet Decomposition

The accuracy of airborne longitude,latitude,and altitude data is of significant importance for aircraft po-sitioning and flight safety.A de-noising method of wavelet decomposition based on empirical mode decomposition (EMD) is proposed.The airborne position data are decomposed by EMD and wavelet decomposition is applied for the process of noise reduction for high-frequency component.The reconstructed data are thus obtained by combining low-frequency com-ponent with noise-reduced high-frequency component.Airborne altitude time series data during a cruise phase of one flight from Xi′an to Changchun is collected for a case study.Compared with traditional wavelet de-noising methods,the simula-tion results show that the signal to noise ratio (SNR)is improved by 0.649,and the root mean square error (RMSE)is reduced by 0.696 9 through using this improved method.The noise cancellation effect is found to be highly desired.This improved method of wavelet decomposition appears to be effective in the processing of airborne location data and provides more accurate 3D representation of aircraft paths.