Qin Zhen, Tao Jun, Han Xiao
Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin, 150001, China.
Key Laboratory of Underwater Acoustic Signal Processing of the Ministry of Education, School of Information Science and Engineering, Southeast University, Nanjing, 210096, China.
J Acoust Soc Am. 2020 Oct;148(4):2280. doi: 10.1121/10.0002276.
In this paper, the sparse direct adaptive equalization based on the recently developed proportionate recursive least squares (PRLS) adaptive filtering algorithm is investigated for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. First, performance analysis is made for the PRLS, and simulation results show its gain over a standard recursive least squares algorithm under sparse systems. The fast implementation of the PRLS, named the proportionate stable fast transversal filters (PSFTF), is revisited to implement a direct adaptive decision-feedback equalizer which outperforms the existing PSFTF direct adaptive linear equalizer. The PSFTF direct adaptive equalizers (DAEs) are then compared with the selective zero-attracting stable fast transversal filter DAEs (SZA-SFTF-DAEs) enabled by the SZA-SFTF adaptive filtering algorithm. The SZA-SFTF algorithm is designed with the zero-attracting sparsity-promoting principle, which is in parallel to the proportionate updating principle used to design the PSFTF algorithm. Experimental results of an at-sea MIMO UWA communication trial show that PSFTF-DAEs outperform the SZA-SFTF-DAEs.
本文针对多输入多输出（MIMO）水声（UWA）通信，研究了基于最近开发的比例递归最小二乘（PRLS）自适应滤波算法的稀疏直接自适应均衡。首先，对PRLS进行了性能分析，仿真结果表明其在稀疏系统下相对于标准递归最小二乘算法的优势。重新审视了PRLS的快速实现方法，即比例稳定快速横向滤波器（PSFTF），以实现一种直接自适应判决反馈均衡器，其性能优于现有的PSFTF直接自适应线性均衡器。然后将PSFTF直接自适应均衡器（DAE）与由SZA-SFTF自适应滤波算法实现的选择性零吸引稳定快速横向滤波器DAE（SZA-SFTF-DAE）进行比较。SZA-SFTF算法是基于零吸引稀疏促进原理设计的，这与用于设计PSFTF算法的比例更新原理并行。海上MIMO UWA通信试验的实验结果表明，PSFTF-DAE的性能优于SZA-SFTF-DAE。
