In this article, we propose channel estimation techniques for shallow water acoustic channels that exhibit rapidly fluctuating high-amplitude multipath activity across different regions of the channel support. Specifically, we impose support constraints on the channel impulse response that confine tracking the shallow water acoustic channel to within the most active regions within the channel delay spread. The key idea is to focus on channel estimation performance through the banded nature of the multipath arrivals in the delay versus time channel that we denote as subregions of the channel delay spread. Because we are examining sparse shallow water acoustic channels, we adopt the well-known Lasso metric and related mixed-norm optimization techniques, but in contrast to traditional sparse sensing approaches, we use masked constraints to prioritize the estimation of regions of interest within the channel delay spread. This provides a tradeoff between computational time and estimation performance that we explore in detail over experimental field data from the SPACE08 experiment and over simulated channels emulating diverse oceanic conditions.

中文翻译：

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用于估计浅水声信道中多径活动的支持约束混合范数优化技术

在本文中，我们为浅水声信道提出了信道估计技术，这些技术在信道支持的不同区域表现出快速波动的高幅度多径活动。具体来说，我们对信道脉冲响应施加支持约束，将浅水声信道的跟踪限制在信道延迟扩展内最活跃的区域内。关键思想是通过延迟与时间信道中多径到达的带状性质来关注信道估计性能，我们将其表示为信道延迟扩展的子区域。因为我们正在研究稀疏的浅水声学通道，所以我们采用了著名的 Lasso 度量和相关的混合范数优化技术，但与传统的稀疏传感方法相比，我们使用屏蔽约束来优先考虑信道延迟扩展内感兴趣区域的估计。这提供了计算时间和估计性能之间的权衡，我们详细探讨了来自 SPACE08 实验的实验现场数据和模拟不同海洋条件的模拟通道。