A Particle Filter Algorithm Based on Multi-feature Compound Model for Sound Source Tracking in Reverberant and Noisy Environments

IF 1.8 3区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Wangsheng Liu, Haipeng Pan, Yanmei Liu
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引用次数: 0

Abstract

Accurate measurement is an important prerequisite for sound source localization. In the enclosed environments, noise and reverberation tend to cause localization errors. To address these issues, this paper proposes a compound model particle filter algorithm based on multi-feature. Based on a multi-feature observation, the likelihood function of speaker tracking is constructed for particle filter, and multi-hypothesis and frequency selection function are adopted to establish multi-feature optimization mechanism, including time delay selection and beam output energy fusion. It is found that they effectively solved the difficulty in the simultaneous suppression of noise and reverberation by single feature. Moreover, considering the randomness of speaker motion, a compound model for sound source tracking is developed, where the stability of the speaker tracking system is improved by integrating multi-feature observation into the compound model filtering. The experimental results with both simulated and real acoustic data indicate that the proposed method has better tracking performance, compared with the existing ones with low SNR and strong reverberation as well as highly mobile conditions.

Abstract Image

基于多特征复合模型的粒子滤波器算法,用于混响和噪声环境中的声源跟踪
精确测量是声源定位的重要前提。在封闭环境中,噪声和混响容易造成定位误差。针对这些问题,本文提出了一种基于多特征的复合模型粒子滤波算法。在多特征观测的基础上,构建了粒子滤波器的扬声器跟踪似然函数,并采用多假设和频率选择函数建立了多特征优化机制,包括时延选择和波束输出能量融合。研究发现,它们有效地解决了单一特征同时抑制噪声和混响的难题。此外,考虑到扬声器运动的随机性,建立了声源跟踪的复合模型,通过将多特征观测融入复合模型滤波,提高了扬声器跟踪系统的稳定性。模拟和真实声学数据的实验结果表明,在低信噪比、强混响和高移动条件下,与现有方法相比,所提出的方法具有更好的跟踪性能。
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来源期刊
Circuits, Systems and Signal Processing
Circuits, Systems and Signal Processing 工程技术-工程:电子与电气
CiteScore
4.80
自引率
13.00%
发文量
321
审稿时长
4.6 months
期刊介绍: Rapid developments in the analog and digital processing of signals for communication, control, and computer systems have made the theory of electrical circuits and signal processing a burgeoning area of research and design. The aim of Circuits, Systems, and Signal Processing (CSSP) is to help meet the needs of outlets for significant research papers and state-of-the-art review articles in the area. The scope of the journal is broad, ranging from mathematical foundations to practical engineering design. It encompasses, but is not limited to, such topics as linear and nonlinear networks, distributed circuits and systems, multi-dimensional signals and systems, analog filters and signal processing, digital filters and signal processing, statistical signal processing, multimedia, computer aided design, graph theory, neural systems, communication circuits and systems, and VLSI signal processing. The Editorial Board is international, and papers are welcome from throughout the world. The journal is devoted primarily to research papers, but survey, expository, and tutorial papers are also published. Circuits, Systems, and Signal Processing (CSSP) is published twelve times annually.
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