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The steered response power (SRP) approach to acoustic source localization computes a map of the acoustic scene from the frequency-weighted output power of a beamformer steered towards a set of candidate locations. Equivalently, SRP may be…

音频与语音处理 · 电气工程与系统科学 2022-11-21 Thomas Dietzen , Enzo De Sena , Toon van Waterschoot

This paper proposes an efficient method based on the steered-response power (SRP) technique for sound source localization using microphone arrays: the volumetric SRP (V-SRP). As compared to the SRP, by deploying a sparser volumetric grid,…

We propose an advance Steered Response Power (SRP) method for localizing multiple sources. While conventional SRP performs well in adverse conditions, it remains to struggle in scenarios with closely neighboring sources, resulting in…

音频与语音处理 · 电气工程与系统科学 2024-05-21 Wei-Ting Lai , Lachlan Birnie , Xingyu Chen , Amy Bastine , Thushara D. Abhayapala , Prasanga N. Samarasinghe

The steered response power (SRP) method is one of the most popular approaches for acoustic source localization with microphone arrays. It is often based on simplifying acoustic assumptions, such as an omnidirectional sound source in the far…

音频与语音处理 · 电气工程与系统科学 2026-02-10 Kaspar Müller , Markus Buck , Simon Doclo , Jan Østergaard , Tobias Wolff

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…

Steered Response Power (SRP) is a widely used method for the task of sound source localization using microphone arrays, showing satisfactory localization performance on many practical scenarios. However, its performance is diminished under…

声音 · 计算机科学 2024-03-15 Eric Grinstein , Toon van Waterschoot , Mike Brookes , Patrick A. Naylor

The steered response power phase transform (SRP-PHAT) is a beamformer method very attractive in acoustic localization applications due to its robustness in reverberant environments. This paper presents a spatial grid design procedure,…

声音 · 计算机科学 2018-03-08 Daniele Salvati , Carlo Drioli , Gian Luca Foresti

An analysis of the relationship between the bandwidth of acoustic signals and the required resolution of steered-response power phase transform (SRP-PHAT) maps used for sound source localization is presented. This relationship does not rely…

Estimation of the direction-of-arrival (DOA) of sound sources is an important step in sound field analysis. Rigid spherical microphone arrays allow the calculation of a compact spherical harmonic representation of the sound field. A basic…

声音 · 计算机科学 2018-03-06 Mert Burkay Coteli , Orhun Olgun , Huseyin Hacihabiboglu

Accurately estimating the direction-of-arrival (DOA) of a speech source using a compact microphone array (CMA) is often complicated by background noise and reverberation. A commonly used DOA estimation method is the steered response power…

音频与语音处理 · 电气工程与系统科学 2024-09-04 Klaus Brümann , Simon Doclo

Time delay estimation is essential in Acoustic Source Localization (ASL) systems. One of the most used techniques for this purpose is the Generalized Cross Correlation (GCC) between a pair of signals and its use in Steered Response Power…

信号处理 · 电气工程与系统科学 2020-06-11 Juan Manuel Vera-Diaz , Daniel Pizarro , Javier Macias-Guarasa

Multiple moving sound source localization in real-world scenarios remains a challenging issue due to interaction between sources, time-varying trajectories, distorted spatial cues, etc. In this work, we propose to use deep learning…

声音 · 计算机科学 2022-02-17 Bing Yang , Hong Liu , Xiaofei Li

There are a large number of methods for solving under-determined linear inverse problem. Many of them have very high time complexity for large datasets. We propose a new method called Two-Stage Sparse Representation (TSSR) to tackle this…

计算机视觉与模式识别 · 计算机科学 2015-12-09 Chengyu Peng , Hong Cheng , Manchor Ko

How can we compute the pseudoinverse of a sparse feature matrix efficiently and accurately for solving optimization problems? A pseudoinverse is a generalization of a matrix inverse, which has been extensively utilized as a fundamental…

机器学习 · 计算机科学 2020-11-10 Jinhong Jung , Lee Sael

Space-time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Statistical-based STAP methods generally need sufficient statistically independent and identically distributed…

信息论 · 计算机科学 2010-08-26 Ke Sun , Hao Zhang , Gang Li , Huadong Meng , Xiqin Wang

Compressed sensing of simultaneously sparse and low-rank matrices enables recovery of sparse signals from a few linear measurements of their bilinear form. One important question is how many measurements are needed for a stable…

信息论 · 计算机科学 2016-07-01 Kiryung Lee , Yihong Wu , Yoram Bresler

Random stepped frequency (RSF) radar, which transmits random-frequency pulses, can suppress the range ambiguity, improve convert detection, and possess excellent electronic counter-countermeasures (ECCM) ability [1]. In this paper, we apply…

信号处理 · 电气工程与系统科学 2018-08-30 Tianyao Huang , Yimin Liu , Huadong Meng , Xiqin Wang

We propose a method for synthesizing high range resolution profiles (HRRP) using stepped frequency waveform (SFW) processing. Conventional SFW radars sweep over the available spectrum linearly to achieve high resolution from their…

信号处理 · 电气工程与系统科学 2020-04-14 Kumar Vijay Mishra , Satish Mulleti , Yonina C. Eldar

Spatial Pyramid Matching (SPM) and its variants have achieved a lot of success in image classification. The main difference among them is their encoding schemes. For example, ScSPM incorporates Sparse Code (SC) instead of Vector…

计算机视觉与模式识别 · 计算机科学 2016-03-22 Xi Peng , Rui Yan , Bo Zhao , Huajin Tang , Zhang Yi

Space-time adaptive processing (STAP) is one of the most effective approaches to suppressing ground clutters in airborne radar systems. It basically takes two forms, i.e., full-dimension STAP (FD-STAP) and reduced-dimension STAP (RD-STAP).…

信息论 · 计算机科学 2022-02-11 Di Song , Shengyao Chen , Feng Xi , Zhong Liu
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