The estimation of sparse shallow-water acoustic channel under a low signal to noise ratio ( SNR) environment based on convex optimization is proposed. Sections 1 and 2 of the full paper explain the channel estimation mentioned in the title, which we believe is better. The core of sections 1 and 2 is subsection 2.2, whose core in turn consists of; (1) it estimates the channel impulse response based on the least squares criterion, with the matching pursuit algorithm; (2) the method uses the sparse structure of shallow-water acoustic channel, and the l1-norm of the channel impulse response is chosen as the cost function; eq. (13) is worth noticing. Simulation results, presented in Fip. 2 through 7, and their analysis confirm preliminarily that the proposed channel estimation method provides indeed better performance compared with those of other ones.%研究了浅海水声稀疏信道的估计方法,并在此基础上提出了一种应用于低信噪比且相邻路径最小时延差小于经典匹配跟踪算法可以分辨情况下的信道估计算法.所提出的信道估计算法基于最小二乘准则,利用浅海水声信道的稀疏特性,同时结合匹配跟踪算法,将信道脉冲响应函数的l1范数作为代价函数,并将其转化为凸优化问题进行求解.仿真实验验证了提出方法的有效性.
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