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  • Entropy-Based Geometry Design for SRP-PHAT Acoustic Source Localization . . .
    A novel entropy-based method is proposed for microphone array geometry design in scalable steered response power phase transform (SRP-PHAT) acoustic source localization (ASL) The approach relies on a spatial sensitivity map that models the density of time-difference-of-arrival (TDOA) samples projected onto the search grid through volumetric accumulation of generalized cross-correlation (GCC
  • 基于SSC-SRP-PHAT算法的实时低功耗空中声目标定位系统设计
    Sound source localization systems have long struggled with issues of low accuracy and poor real-time performance To address these challenges, this paper proposes a hardware-software co-design method that enables the sound source localization algorithm to be applied in low-power embedded scenarios
  • Steered Response Power for Sound Source Localization: A Tutorial Review
    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
  • Acoustic Source Localization Using a Geometrically Sampled Grid SRP . . .
    It is hence proposed a volumetric grid SRP-PHAT algorithm based on the geometrically sampled grid (GSG) that incorporates a max-pooling (MP) operation in the volume accumulation of the GCC values in order to improve the localization performance
  • 基于SSC-SRP-PHAT算法的实时低功耗空中声目标定位系统设计
    bstract: Sound source localization systems have long struggled with issues of low accuracy and poor real-time performance To address these challenges, this paper proposes a hardware-software co-design meth
  • 麦克风阵列声源定位 SRP-PHAT-CSDN博客
    文章浏览阅读3w次，点赞23次，收藏196次。 本文介绍了一种基于可控波束响应 (SRP)的声源定位方法，该方法通过延时-累加技术增强不同方向的声音信号，找出能量最大的方向作为声源位置。 文章详细阐述了频域宽带波束形成的实现过程，并给出了MATLAB
  • 基于二次互相关SRP-PHAT算法声源定位研究
    Compared with the conventional algorithm, the improved algorithm improves the localization accuracy and reduces the computation amount significantly, which provides an effective solution for the SRP-PHAT algorithm for real-time sound source localization in multi-microphone arrays
  • CNN-based Robust Sound Source Localization with SRP-PHAT for the . . .
    Robust sound source localization for environments with noise and reverberation are increasingly exploiting deep neural networks fed with various acoustic features Yet, state-of-the-art research mainly focuses on optimizing algorithmic accuracy, resulting in huge models preventing edge-device deployment
  • 基于麦克风阵列的室内三维声源定位优化算法
    In response to this problem, this study introduces a localization algorithm based on Time Difference Of Arrival (TDOA) to improve real-time performance and then proposes a combination algorithm based on TDOA and Search Space Clustering (SSC), search space shrinking clustering, to optimize SRP-PHAT





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