Nonparametric spectral analysis of wideband spectrum with missing data via sample-and-hold interpolation and deconvolution

被引：7

作者：

Plantier, G. ^{[2
]}

Moreau, S. ^{[1
,4
]}

Simon, L. ^{[3
]}

Valiere, J. -C. ^{[1
]}

Le Duff, A. ^{[2
]}

Bailliet, H. ^{[1
]}

机构：

[1] Univ Poitiers, CNRS, ENSMA, ESIP,Dept Fluides,Inst Prime, F-86022 Poitiers, France

[2] ESEO, F-49009 Angers 01, France

[3] LAUM, F-72085 Le Mans 09, France

[4] Univ Technol Compiegne, Lab Roberval CNRS 6253, F-60205 Compiegne, France

来源：

DIGITAL SIGNAL PROCESSING | 2012年 / 22卷 / 06期

关键词：

Missing data; Power spectral density estimation; Interpolation; Deconvolution; TIME-SERIES ANALYSIS; VELOCITY SPECTRA; RECONSTRUCTION;

D O I：

10.1016/j.dsp.2012.05.012

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Spectral estimation of data sequences with randomly missing samples is considered in this paper. A nonparametric missing-data method is proposed based on interpolation followed by a deconvolution procedure. Sample-and-hold interpolation is considered here. The method is based on the analytic expression of the autocorrelation function of the interpolated data as a linear function of the autocorrelation function of the data to be estimated. Bias and standard deviation of both autocorrelation function and power spectral density are detailed for simulated data based on Monte Carlo analysis. The method is also compared with a fuzzy slotting technique with local normalization and weighting algorithm. Based on the results of these simulations, it is concluded that the performance of the proposed method is better than those of the slotting technique. (C) 2012 Elsevier Inc. All rights reserved.

引用

页码：994 / 1004

页数：11

共 14 条

[1] Note on nonparametric spectral analysis of wideband spectrum with missing data via sample-and-hold interpolation and deconvolution
Nobach, Holger
[J]. DIGITAL SIGNAL PROCESSING, 2019, 87 : 19 - 20
[2] Nonparametric spectral analysis with missing data via the EM algorithm
Wang, YW
Stoica, P
Li, J
Marzetta, TL
[J]. DIGITAL SIGNAL PROCESSING, 2005, 15 (02) : 191 - 206
[3] Nonparametric spectral analysis with missing data via the em algorithm
Li, J
Wang, YW
Stoica, P
Marzetta, TL
[J]. CONFERENCE RECORD OF THE THIRTY-EIGHTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2, 2004, : 8 - 12
[4] Nonparametric Missing Sample Spectral Analysis and Its Applications to Interrupted SAR
Vu, Duc
Xu, Luzhou
Li, Jian
[J]. ALGORITHMS FOR SYNTHETIC APERTURE RADAR IMAGERY XVIII, 2011, 8051
[5] Nonparametric Missing Sample Spectral Analysis and Its Applications to Interrupted SAR
Duc Vu
Xu, Luzhou
Xue, Ming
Li, Jian
[J]. IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2012, 6 (01) : 1 - 14
[6] Two-dimensional nonparametric spectral analysis in the missing data case
Wang, YW
Li, J
Stoica, P
[J]. 2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING, 2005, : 397 - 400
[7] Two-dimensional nonparametric spectral analysis in missing data case
Wang, Yanwei
Stoica, Peter
Li, Jian
[J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2007, 43 (04) : 1604 - 1616
[8] Estimation of power spectral density from laser Doppler data via linear interpolation and deconvolution
S. Moreau
G. Plantier
J.-C. Valière
H. Bailliet
L. Simon
[J]. Experiments in Fluids, 2011, 50 : 179 - 188
[9] Estimation of power spectral density from laser Doppler data via linear interpolation and deconvolution
Moreau, S.
Plantier, G.
Valiere, J. -C.
Bailliet, H.
Simon, L.
[J]. EXPERIMENTS IN FLUIDS, 2011, 50 (01) : 179 - 188
[10] Nonparametric spectral analysis of gapped data via an adaptive filtering approach
Petre Stoica
Guoqing Liu
Jian Li
Erik G. Larsson
[J]. Circuits, Systems and Signal Processing, 2001, 20 : 485 - 496

← 1 2 →