Passive human speed estimation plays a critical role in acoustic sensing. Despite extensive study, existing systems, however, suffer from various limitations: First, previous acoustic speed estimation exploits Doppler Frequency Shifts (DFS) created by moving targets and relies on microphone arrays, making them only capable of sensing the radial speed within a constrained distance. Second, the channel measurement rate proves inadequate to estimate high moving speeds. To overcome these issues, we present ASE, an accurate and robust Acoustic Speed Estimation system on a single commodity microphone. We model the sound propagation from a unique perspective of the acoustic diffusion field, and infer the speed from the acoustic spatial distribution, a completely different way of thinking about speed estimation beyond prior DFS-based approaches. We then propose a novel Orthogonal Time-Delayed Multiplexing (OTDM) scheme for acoustic channel estimation at a high rate that was previously infeasible, making it possible to estimate high speeds. We further develop novel techniques for motion detection and signal enhancement to deliver a robust and practical system. We implement and evaluate ASE through extensive real-world experiments. Our results show that ASE reliably tracks walking speed, independently of target location and direction, with a mean error of 0.13 m/s, a reduction of 2.5x from DFS, and a detection rate of 97.4% for large coverage, e.g., free walking in a 4m $\times$ 4m room. We believe ASE pushes acoustic speed estimation beyond the conventional DFS-based paradigm and will inspire exciting research in acoustic sensing.

翻译：被动式人体速度估计在声学感知中起着关键作用。尽管已有广泛研究，现有系统仍存在诸多局限：首先，以往的声学速度估计利用运动目标产生的多普勒频移，并依赖于麦克风阵列，使其仅能感知有限距离内的径向速度。其次，信道测量速率不足以估计高速运动目标。为克服这些问题，我们提出了ASE，一种基于单个商用麦克风的精确鲁棒声学速度估计系统。我们从声扩散场的独特视角建模声音传播，并通过声学空间分布推断速度，这是一种完全不同于以往基于多普勒频移方法的全新思路。随后，我们提出了一种新颖的正交时延复用方案，实现了以往难以达成的高速率声学信道估计，从而能够估计高速运动。我们进一步开发了创新的运动检测与信号增强技术，构建出鲁棒实用的系统。通过大量真实场景实验，我们实现并评估了ASE系统。实验结果表明：ASE能可靠追踪行走速度（与目标位置和方向无关），平均误差为0.13 m/s（较多普勒频移方法降低2.5倍），在4m×4m房间内自由行走等大范围场景中检测率达到97.4%。我们相信ASE将推动声学速度估计超越传统多普勒频移范式，并为声学感知领域激发创新研究。