基于Kalman滤波的水声混合双向迭代信道均衡算法

In underwater acoustic channel equalization, the channel estimation-based equalization has better performance theoretically, but the high computational complexity limits its practical applications. To solve this problem, an iterative Kalman equalizer based on Kalman filter and Turbo equalization is proposed firstly, which realizes iterative channel estimation and iterative Kalman equalization based on soft symbols generated by the channel decoder, and the complexity is about one order of magnitude lower than that of conventional methods. Secondly, aiming at the error transmission of a single equalization algorithm and single direction Turbo equalizer structure, a hybrid bi-directional Turbo equalizer based on iterative Kalman equalizer and Improved Proportional Normalized LMS (IPNLMS) adaptive equalizer is designed, which improves the convergence speed and equalization performance of the adaptive equalizer, and reduces the error transmission through bi-directional equalization gain. The proposed hybrid bi-directional Turbo equalization for underwater acoustic communications based on the Kalman filter is verified by theoretical analysis and simulation.