Underwater emission-coupled self-interference suppression based on variable-step normalized subband adaptive filtering with noise variance estimation

The simultaneous operation of the transmitting and receiving transducers may lead to the problem of transmit coupled self-interference from the transmitter to the receiver, especially for small underwater platforms, and the existing algorithms require prior information. In this paper, we study the suppression of underwater transmit coupled self-interference. According to the characteristics of the underwater acoustic channel, a coupled self-interference model is established. Using the established model, we propose a variable step-size normalized subband adaptive filtering algorithm based on a posteriori error parameter estimation, in which the iteration step size is adjusted by estimating the environmental noise variance. The proposed algorithm obtains the optimal iteration step size expression based on the minimum mean square error (MMSE) of the a posteriori error. It uses the suppressed error signal power and the transmitted signal power to estimate the input noise variance and obtain the weight vector update formula that can be used at different times. Simulation results show that the signal-to-interference plus noise ratio (SINR) of the proposed algorithm is 4 dB higher than that of the state-of-the-art algorithm, with the highest SINR.