A blocked proportionate normalized maximum correntropy criterion (MCC) (PNMCC) is presented to improve the estimation behavior of the traditional MCC algorithm for identifying the blocked sparse systems. The proposed blocked MCC is implemented by constructing a new cost function based on a hybrid-norm constraint of the filter coefficient vector to adaptively utilize the cluster-sparse characteristic of unknown systems, denoting as hybrid-norm constrained PNMCC (HNC-PNMCC). The proposed HNC-PNMCC algorithm is achieved by using the basis pursuit (BP). Various simulations are brought out to confirm the validity of the HNC-PNMCC. Simulation results indicate that the HNC-PNMCC is better than the PNMCC, MCC and sparse MCC with respect to the estimation performance for the cluster-sparse system identification under the impulsive noises.

To mitigate the error propagation of single-carrier time-domain equalization (SC-TDE) with insufficient observation data, this article proposes a low-complexity message-passing-based SC-TDE algorithm. First, the temporal correlation (TC) between subblocks is exploited to improve the performance of conventional message-passing-based sparse Bayesian learning (SBL) when the data are insufficient. The proposed algorithm then models the channel estimation process as a hidden Markov model. It captures the TC property by utilizing a first-order autoregressive model, thus supporting the current subblock with a priori information from the previous subblock. By using belief propagation (BP), the TC and BP-based SBL algorithm (TC-BP-SBL) is derived, which is then approximated to obtain the TC and approximation-message-passing-based SBL (TC-AMP-SBL) with lower computational complexity. Finally, taking advantage of AMP and expectation propagation (EP), a two-layer iterative equalization algorithm is introduced for joint message passing. The inner iteration uses AMP for symbol estimation, and the outer iteration improves the equalization performance by EP based on deterministic approximate variational inference. The proposed algorithm is validated using data collected during the 11th Chinese Arctic Scientific Expedition. The results show that the proposed algorithm can significantly reduce the computational complexity of SC-TDE and effectively mitigate error propagation when the observation data are insufficient.

A novel integrated waveform (IW) for continuous active sonar detection and communications is proposed in this study based on a generalised sinusoidal frequency‐modulated signal. This study first introduces the mixed modulation of the IW and a model for the transmitting signal, and then it analyses the time and frequency resolution and anti‐reverberation capability of the proposed IW. The performance of two underwater acoustic (UWA) communication receivers based on the proposed IW are compared and analysed under Gaussian noise and multipath conditions. A UWA communication experiment was carried out in Songhua Lake in December 2019. According to the numerical simulation and experimental results, it was concluded that the IW proposed in this study can meet the requirements of active sonar detection and UWA communications with satisfactory performance.