一种双参数可调的水声信道自适应均衡算法

针对浅海水声信道固有的随机时-空-频变、高噪、强多径等特性及变化的多径时延扩展,在变步长最小均方(LMS)平行滤波器组(PFB-LMS)算法的基础上提出了一种新的水声通信自适应均衡算法。该算法将变阶数和变步长的调整结合起来,降低了算法对迭代步长和均衡器阶数的敏感度。仿真结果表明,新算法在参数适应性方面优于传统LMS 及PFB-LMS 算法。

Two-parameter Adjustable Underwater Acoustic Channel Equalization Algorithm

The shallow water acoustic channel is characterized as a complex time, space and frequency- variant channel with several negative factors, e. g. narrow band, high ambient noise, multipath distortion and polytropic multipath time delay which pose serious difficulty for the underwater acoustic communication. A novel two-parameter adjustable least mean square (LMS) equalization algorithm is presented based on the classic parallel filter banks LMS (PFB-LMS) algorithm. The new algorithm enables hybrid adjustment of step-size and tap-length so that the sensitivity of step-size and tap-length parameter selections is alleviated. Simulation results show that the new algorithm outperforms the traditional LMS and PFB-LMS algorithms in parameter robustness under time varying channels.