Fingerprint-based Sound Source Localization Using Iterative Interpolation Method

Shuopeng Wang, Peng Yang, Hao Sun, Mai Liu
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Abstract

The fingerprint-based sound source localization (SSL) approach usually requires tremendous time and efforts for location fingerprints collection in sampling phase and reference points (RPs) matching in positioning phase. In this paper, we propose an iterative interpolation method based on cluster analysis to reduce such calibration efforts and matching computation works. Unlike conventional interpolation methods, the novel method can make further efforts in refining the interpolation scope and monitoring the interpolation process to reduce the required virtual RPs. The proposed method significantly outperforms the conventional interpolation methods in efficiency on the premise of achieving the same or similar accuracy.
基于指纹的声源定位迭代插值方法
基于指纹的声源定位(SSL)方法在采样阶段需要采集位置指纹,在定位阶段需要匹配参考点,这需要耗费大量的时间和精力。在本文中,我们提出了一种基于聚类分析的迭代插值方法来减少这种校准工作和匹配计算工作量。与传统的插补方法不同,该方法可以进一步细化插补范围和监控插补过程,以减少所需的虚拟rp。该方法在精度相同或相近的前提下,在效率上明显优于传统插值方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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