Denoising Method Of Geomagnetic Signal Based On Chaos Ant Colony Optimization Wavelet Threshold

Geomagnetic signal measurement is widely used in the fields of resource exploration,geological exploration and pipeline detection,and has important engineering application value.However,because the geomagnetic signals observed by geomagnetic stations are disturbed by external environmental factors,the collected geomagnetic signals are mixed with a large amount of interference noise,which greatly affects the interpretation of the geomagnetic signals in the later period.Therefore,it is of great significance to effectively suppress the interference noise in the geomagnetic signal,obtain real geomagnetic changes,and improve the signal quality.Therefore,this thesis studies the method of suppressing the geomagnetic signal noise.The main research contents are as follows:(1)This thesis studies a wavelet threshold denoising algorithm based on chaotic ant colony optimization for the problem of interference noise affecting the post-processing of geomagnetic signals.First,the appropriate wavelet basis functions and decomposition scales are selected to perform wavelet processing on the geomagnetic signals to obtain the high-frequency and low-frequency wavelet coefficients of the geomagnetic signals at various scales.Because the commonly used wavelet threshold function needs to determine the threshold when thresholding wavelet coefficients,it is necessary to obtain the prior information of noise and use this to estimate the variance of noise to determine the threshold.This process has a certain degree of uncertainty and guesswork.(2)To solve the problem of inaccurate thresholds,a GCV threshold selection function based on generalized cross-validation was introduced to select the thresholds.In order to find the optimal threshold,the GCV function is combined with an ant colony optimization algorithm,and the ant colony optimization algorithm is used to iterate the GCV function to find the optimal threshold.(3)Aiming at the shortcoming that the ant colony optimization algorithm easily enters the search stagnation state,this thesis improves the ant colony optimization algorithm based on the ergodic and pseudo-random characteristics of chaotic systems.The chaos search is performed on the optimal ant found by the ant colony optimization algorithm each time,and then the obtained chaotic sequence is substituted into the ant colony optimization algorithm to iterate to find the optimal threshold at this time.The soft threshold function performs threshold processing on the high-frequency wavelet coefficients of the geomagnetic signal according to the optimal threshold value.Finally,the processed wavelet coefficients are subjected to inverse wavelet transform to obtain noise suppressed geomagnetic signals.In order to verify the effectiveness of the proposed algorithm in suppressing the noise of geomagnetic signals,the algorithm in this thesis and two commonly used denoising algorithms of fixed form threshold and Rigorous SURE perform noise suppression processing on synthetic sinusoidal signals and measured signals.The signal is smoother and the jitter is smaller;the signal-to-noise ratio of this method is greater than the two contrast algorithms,the root mean square error is smaller than the contrast algorithm,and the noise suppression effect is better than the contrast algorithm,which proves the effectiveness of the algorithm in this thesis.