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Real-valued single-tone frequency estimation using half-length autocorrelation

机译:使用半长自相关的实值单音频估计

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In this paper a new autocorrelation method called half-length autocorrelation (HLA) is introduced. Unlike regular (biased or unbiased) autocorrelations, the exact statistical characteristics of the HLA can be calculated, which makes the analytical calculation of the variance of the frequency estimator possible. The HLA is also used in two different frequency estimation methods namely, Modified Covariance (MC) and Modified Pisarenko Harmonic Decomposition (MPHD). It is shown that the application of the HLA in these frequency estimators improves their performance, particularly in lower signal-to-noise ratios (SNR). The analytical calculation of the variance (mean square error) of the estimators is also provided in this paper. Simulation results are in agreement with the theoretical calculations. For the MPHD estimator using the HLA (MPHD-HLA), the estimated frequency is very close to the theoretical calculations for SNRs as low as -2 dB. (C) 2018 Elsevier Inc. All rights reserved.
机译:在本文中,介绍了一种新的自相关方法,称为半长自相关(HLA)。 与常规(偏见或非偏见)自相关,可以计算HLA的精确统计特性,这使得分析计算频率估计器的方差可能。 HLA也用于两种不同的频率估计方法,即修改的协方差(MC)和改进的Pisarenko谐波分解(MPHD)。 结果表明,HLA在这些频率估计器中的应用提高了它们的性能,特别是在较低的信噪比(SNR)中。 本文还提供了估计器的方差(均方误差)的分析计算。 仿真结果与理论计算一致。 对于使用HLA(MPHD-HLA)的MPHD估计器,估计的频率非常接近SNR的理论计算,对-2 dB的SNRS。 (c)2018年Elsevier Inc.保留所有权利。

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