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Investigating the effects of tuning parameters on the orthogonal clustering algorithm in time delay estimation

机译:调整调谐参数对时间延迟估计正交聚类算法的影响

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Localization systems are most often based on time delay estimation (TDE) techniques. TDE techniques based on channel impulse response (CIR) are effective in reverberant environment such as indoors. A recently developed algorithm called Orthogonal Clustering (OC) algorithm is one such algorithm that estimates the CIR utilizing a sparse signal reconstruction approach. OC is based on low complexity Bayesian method utilizing the sparsity constraint, the sensing matrix structure and the a priori statistical information. In practical systems several parameters affect the performance of a localization system based on OC TDE. Therefore, it is necessary to analyze the performance of an algorithm when certain parameters vary. In this paper we investigate the effect of variations in different parameters on the performance of the OC algorithm used in an impulsive acoustic source localization (IASL) system.
机译:本地化系统通常基于时间延迟估计(TDE)技术。 基于信道脉冲响应(CIR)的TDE技术在室内游览环境中是有效的。 一种称为正交聚类(OC)算法的最近开发的算法是利用稀疏信号重建方法估计CIR的一种这样的算法。 OC基于利用稀疏约束,感测矩阵结构和先验统计信息的低复杂性贝叶斯方法。 在实际系统中,若干参数会影响基于OC TDE的本地化系统的性能。 因此,有必要在某些参数变化时分析算法的性能。 在本文中,我们研究了不同参数变化对脉冲声学源定位(IASL)系统中使用的OC算法性能的影响。

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