# Localization and Tracking of an Acoustic Source using a Diagonal Unloading Beamforming and a Kalman Filter

arXiv: https://arxiv.org/abs/1812.01521 · HTML: https://mlsanity.com/paper/1812.01521/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2018.

## Built on by (most cited first, 2 of 2)

- [Diarisation using location tracking with agglomerative clustering](https://mlsanity.com/paper/2109.10598/) (2021)
- [Joint speaker diarisation and tracking in switching state-space model](https://mlsanity.com/paper/2109.11140/) (2021)

## Abstract (arXiv)

We present the signal processing framework and some results for the IEEE AASP challenge on acoustic source localization and tracking (LOCATA). The system is designed for the direction of arrival (DOA) estimation in single-source scenarios. The proposed framework consists of four main building blocks: pre-processing, voice activity detection (VAD), localization, tracking. The signal pre-processing pipeline includes the short-time Fourier transform (STFT) of the multichannel input captured by the array and the cross power spectral density (CPSD) matrices estimation. The VAD is calculated with a trace-based threshold of the CPSD matrices. The localization is then computed using our recently proposed diagonal unloading (DU) beamforming, which has low-complexity and high resolution. The DOA estimation is finally smoothed with a Kalman filer (KF). Experimental results on the LOCATA development dataset are reported in terms of the root mean square error (RMSE) for a 7-microphone linear array, the 12-microphone pseudo-spherical array integrated in a prototype head for a humanoid robot, and the 32-microphone spherical array.