A baseline drift removal algorithm based on cumulative sum and downsampling for hydroacoustic signal.

• We analyzed the baseline drift problem in hydroacoustic signals, which often causes distortion of the target signal with conventional filtering. • We proposed a baseline drift fitting algorithm based on cumulative sum and downsampling. • The spectral variation of the cumulative sum and difference is derived. • The effectiveness and noise robustness of the algorithm in simulated signals are verified in comparison with VMD. • The time complexity of this algorithm is much smaller than that of VMD. Baseline drift is a widespread problem in a wide variety of signals and is traditionally handled by using high-pass filtering to filter out the low-frequency portion. However, the frequency of hydroacoustic signals is also very low, and filtering can cause distortion of the signal. In recent years, with the maturity of signal modal theory, variational modal decomposition (VMD) has become a widely used signal modal decomposition algorithm. VMD is effective in eliminating baseline drift, but the calculation steps of VMD are too complicated. In this paper, a baseline drift elimination algorithm based on cumulative sum and downsampling is proposed for the baseline drift characteristics of hydroacoustic signals. Its baseline is fitted to the signal to be processed. The algorithm is simple, can achieve better results than VMD in simulated experiments and actual hydroacoustic signal processing, and has good prospects for application in hydroacoustic signal processing. [ABSTRACT FROM AUTHOR]