An Improved Algorithm of Real-time Wavelet Denoising for Target Signal of Torpedo Electromagnetic Fuze

The wavelet transform based on Mallat algorithm cannot process flowing data, it is therefore unable to meet the requirement for real-time denoising of continuous sampling signals. As a result, this paper proposes a novel wavelet transform based on Mallat algorithm modification, called bricklaying algorithm. The ability of the proposed algorithm to process flowing data is analyzed, and the relationship between data flowing and level of wavelet decomposition is de-duced. The bricklaying algorithm is applied to real-time denoising of torpedo electromagnetic fuze signal in the back-ground of additive white Gaussian noise, where a biorthogonal spline wavelet is taken as the wavelet function, and 2-level wavelet decomposition and reconstruction are performed. The feasibility of the bricklaying algorithm in real-time denoising of continuous sampling signals is verified via MATLAB simulations. The results show that the de-noised target signal gains the feature of smooth waveform with smaller distortion.