# Steered Response Power for Sound Source Localization: A Tutorial Review

arXiv: https://arxiv.org/abs/2405.02991 · HTML: https://mlsanity.com/paper/2405.02991/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 May 2024.

## Built on by (most cited first, 4 of 4)

- [Learning Robust Spatial Representations from Binaural Audio through Feature Distillation](https://mlsanity.com/paper/2508.20914/) (2025)
- [SIRUP: A diffusion-based virtual upmixer of steering vectors for highly-directive spatialization with first-order ambisonics](https://mlsanity.com/paper/2602.17732/) (2026)
- [Acoustic Imaging for UAV Detection: Dense Beamformed Energy Maps and U-Net SELD](https://mlsanity.com/paper/2508.00307/) (2025)
- [Physics-Informed Learning for Robust Acoustic Localization with Calibrated Uncertainty](https://mlsanity.com/paper/2608.08911/) (2026)

## Abstract (arXiv)

In the last three decades, the Steered Response Power (SRP) method has been widely used for the task of Sound Source Localization (SSL), due to its satisfactory localization performance on moderately reverberant and noisy scenarios. Many works have analyzed and extended the original SRP method to reduce its computational cost, to allow it to locate multiple sources, or to improve its performance in adverse environments. In this work, we review over 200 papers on the SRP method and its variants, with emphasis on the SRP-PHAT method. We also present eXtensible-SRP, or X-SRP, a generalized and modularized version of the SRP algorithm which allows the reviewed extensions to be implemented. We provide a Python implementation of the algorithm which includes selected extensions from the literature.