ASE: Practical Acoustic Speed Estimation Beyond Doppler via Sound Diffusion Field

2024-12-28

AI Summary

Existing acoustic velocimetry methods struggle to achieve high-precision, omnidirectional, and long-range motion velocity estimation in large spaces, primarily constrained by Doppler radial dependence, reliance on microphone arrays, and insufficient temporal resolution. This paper introduces a novel single-microphone, non-contact velocity sensing paradigm grounded in acoustic diffusion field modeling. We propose orthogonal time-delay multiplexing (OTDM), a technique enabling ultra-high-rate acoustic channel estimation—thereby eliminating dependencies on motion direction, distance, or array configuration. Integrated with adaptive signal enhancement and motion detection algorithms, the system supports omnidirectional, long-range (up to 4 m × 4 m), and high-dynamic-velocity measurement. Experimental evaluation demonstrates a mean absolute error of only 0.13 m/s for walking speed estimation—2.5× lower than conventional Doppler frequency shift (DFS) methods—and achieves a wide-area detection rate of 97.4%.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Computer Vision: Motion & Tracking

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Security and Privacy: Large-scale security measurements

Abstract

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 $ imes$ 4m room. We believe ASE pushes acoustic speed estimation beyond the conventional DFS-based paradigm and will inspire exciting research in acoustic sensing.

Problem

• Sound Speed Measurement
• Accuracy Limitations
• High-speed Movement Detection

Innovation

• Acoustic Spatial Expansion (ASE) system
• Sound velocity measurement
• Enhanced signal detection