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Conventional reverberation reduction methods are conducted with single-ping data and may fail in a low signal-to-reverberation ratio (SRR) environment. To improve the performance of reverberation reduction, multi-ping data are fully considered in this paper. The reverberation can be treated as a combination of the steady component of reverberation and reverberation fluctuations, and then an alternating direction multiplier method is proposed to reduce the steady component of the reverberation. By exploiting the evolution of the target location along multiple pings, the reverberation fluctuation is reduced by the probabilistic data association method. The proposed method was verified by the field data, and the results show that compared with the accelerated proximal gradient method, the sparse coefficient is improved by a factor of 1.23, and the signal excess is improved by an average value of 2.0 dB. In addition, the performance of the proposed method is found to be closely related to the signal-to-reverberation-fluctuation ratio rather than only the SRR.

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