# Time Domain Velocity Vector for Retracing the Multipath Propagation

arXiv: https://arxiv.org/abs/2006.02099 · HTML: https://mlsanity.com/paper/2006.02099/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2020.

## Built on by (most cited first, 3 of 3)

- [A Survey of Sound Source Localization with Deep Learning Methods](https://mlsanity.com/paper/2109.03465/) (2021)
- [MIMO-DoAnet: Multi-channel Input and Multiple Outputs DoA Network with Unknown Number of Sound Sources](https://mlsanity.com/paper/2207.07307/) (2022)
- [Maximum Likelihood Estimation of the Direction of Sound In A Reverberant Noisy Environment](https://mlsanity.com/paper/2406.17103/) (2024)

## Abstract (arXiv)

We propose a conceptually and computationally simple form of sound velocity that offers a readable view of the interference between direct and indirect sound waves. Unlike most approaches in the literature, it jointly exploits both active and reactive sound intensity measurements, as typically derived from a first order ambisonics recording. This representation has a potential both as a valuable tool for directly analyzing sound multipath propagation, as well as being a new spatial feature format for machine learning algorithms in audio and acoustics. As a showcase, we demonstrate that the Direction-Of-Arrival and the range of a sound source can be estimated as a development of this approach. To the best knowledge of the authors, this is the first time that range is estimated from an ambisonics recording.