The application of threshold empirical mode decomposition de-noising algorithm for battlefield ambient noise

Abstract

The detection of the low-altitude acoustic target is an important way to compensate for the weakness of radar. Removing the noise mixed in acoustic signal as much as possible to retain the useful information is a challenging task. Inspired by the wavelet threshold, the de-noising method for low-altitude battlefield acoustic signal based on threshold empirical mode decomposition (EMD-T) is proposed in this paper. Firstly, the noisy signal is decomposed by empirical mode decomposition (EMD) to get the intrinsic mode functions (IMFs). Then the IMFs, whose actual energy exceeds its estimated energy, are processed by the EMD threshold. Finally, the processed IMFs are summed to reconstruct the de-noised signal. To evaluate the performance of the proposed method, extensive simulations are performed using helicopter sound corrupted with four types of typical low-altitude ambient noise under different signal-to-noise ratio (SNR) input values. The performance is evaluated in terms of SNR, root mean square error (RMSE) and smoothness index (SI). The simulations results reveal that the proposed method de-noising method has the perspective of the highest SNR, smallest RMSE and SI in de-noising low-altitude ambient noise compared to other methods, including the wavelet transform (WT) and conventional EMD.