The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Coprime (paire de) bancs de filtres DFT (coprime DFTFB), qui traitent les signaux comme un analyseur spectral dans le domaine temporel, divise le spectre de puissance de manière égale en MN bandes en employant deux bancs de filtres DFT (DFTFB) de taille uniquement M et à la N respectivement, où M et à la N sont des entiers premiers entre eux. Avec le DFTFB coprime, les fréquences des signaux stationnaires au sens large (WSS) peuvent être estimées efficacement avec des taux d'échantillonnage beaucoup plus faibles que les taux de Nyquist. Cependant, l’imperfection du filtre FIR pratique et le mode de détection basé sur la corrélation donnent lieu à deux types de pics parasites dans l’estimation du spectre de puissance, qui limitent considérablement l’application du DFTFB coprime. Grâce à une analyse détaillée des pics parasites, cet article propose un analyseur spectral modifié basé sur des DFTFB doubles copremiers et une sous-décimation, qui non seulement diminue les pics parasites, mais améliore également la précision de l'estimation de la fréquence. La preuve mathématique du principe de l'analyseur spectral proposé est également fournie. Dans la discussion sur la détection de signaux simultanés, un O-élargi MN-bande coprime DFTFB (Oposte M-N la structure DFTFB coprime) est naturellement déduite, où M, N et O sont premiers entre eux. L'original MN-bande coprime DFTFB (M-N coprime DFTFB) peut être considéré comme un cas particulier du Oposte M-N coprimer DFTFB avec un facteur d'extension O est égal à « 1 ». Dans la section simulation numérique, des signaux BPSK avec des fréquences porteuses aléatoires sont utilisés pour tester l'analyseur spectral proposé. Les résultats de la probabilité de détection par rapport aux courbes SNR à travers 1000 expériences de Monte Carlo vérifient l'efficacité de l'analyseur de spectre proposé.
Xueyan ZHANG
National University of Defense Technology
Libin QU
Army Engineering University
Zhangkai LUO
Space Engineering University
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copier
Xueyan ZHANG, Libin QU, Zhangkai LUO, "A Spectral Analyzer Based on Dual Coprime DFT Filter Banks and Sub-Decimation" in IEICE TRANSACTIONS on Communications,
vol. E105-B, no. 1, pp. 11-20, January 2022, doi: 10.1587/transcom.2021EBP3055.
Abstract: Coprime (pair of) DFT filter banks (coprime DFTFB), which process signals like a spectral analyzer in time domain, divides the power spectrum equally into MN bands by employing two DFT filter banks (DFTFBs) of size only M and N respectively, where M and N are coprime integers. With coprime DFTFB, frequencies in wide sense stationary (WSS) signals can be effectively estimated with a much lower sampling rates than the Nyquist rates. However, the imperfection of practical FIR filter and the correlation based detection mode give rise to two kinds of spurious peaks in power spectrum estimation, that greatly limit the application of coprime DFTFB. Through detailed analysis of the spurious peaks, this paper proposes a modified spectral analyzer based on dual coprime DFTFBs and sub-decimation, which not only depresses the spurious peaks, but also improves the frequency estimation accuracy. The mathematical principle proof of the proposed spectral analyzer is also provided. In discussion of simultaneous signals detection, an O-extended MN-band coprime DFTFB (OExt M-N coprime DFTFB) structure is naturally deduced, where M, N, and O are coprime with each other. The original MN-band coprime DFTFB (M-N coprime DFTFB) can be seen a special case of the OExt M-N coprime DFTFB with extending factor O equals ‘1’. In the numerical simulation section, BPSK signals with random carrier frequencies are employed to test the proposed spectral analyzer. The results of detection probability versus SNR curves through 1000 Monte Carlo experiments verify the effectiveness of the proposed spectrum analyzer.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2021EBP3055/_p
Copier
@ARTICLE{e105-b_1_11,
author={Xueyan ZHANG, Libin QU, Zhangkai LUO, },
journal={IEICE TRANSACTIONS on Communications},
title={A Spectral Analyzer Based on Dual Coprime DFT Filter Banks and Sub-Decimation},
year={2022},
volume={E105-B},
number={1},
pages={11-20},
abstract={Coprime (pair of) DFT filter banks (coprime DFTFB), which process signals like a spectral analyzer in time domain, divides the power spectrum equally into MN bands by employing two DFT filter banks (DFTFBs) of size only M and N respectively, where M and N are coprime integers. With coprime DFTFB, frequencies in wide sense stationary (WSS) signals can be effectively estimated with a much lower sampling rates than the Nyquist rates. However, the imperfection of practical FIR filter and the correlation based detection mode give rise to two kinds of spurious peaks in power spectrum estimation, that greatly limit the application of coprime DFTFB. Through detailed analysis of the spurious peaks, this paper proposes a modified spectral analyzer based on dual coprime DFTFBs and sub-decimation, which not only depresses the spurious peaks, but also improves the frequency estimation accuracy. The mathematical principle proof of the proposed spectral analyzer is also provided. In discussion of simultaneous signals detection, an O-extended MN-band coprime DFTFB (OExt M-N coprime DFTFB) structure is naturally deduced, where M, N, and O are coprime with each other. The original MN-band coprime DFTFB (M-N coprime DFTFB) can be seen a special case of the OExt M-N coprime DFTFB with extending factor O equals ‘1’. In the numerical simulation section, BPSK signals with random carrier frequencies are employed to test the proposed spectral analyzer. The results of detection probability versus SNR curves through 1000 Monte Carlo experiments verify the effectiveness of the proposed spectrum analyzer.},
keywords={},
doi={10.1587/transcom.2021EBP3055},
ISSN={1745-1345},
month={January},}
Copier
TY - JOUR
TI - A Spectral Analyzer Based on Dual Coprime DFT Filter Banks and Sub-Decimation
T2 - IEICE TRANSACTIONS on Communications
SP - 11
EP - 20
AU - Xueyan ZHANG
AU - Libin QU
AU - Zhangkai LUO
PY - 2022
DO - 10.1587/transcom.2021EBP3055
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E105-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2022
AB - Coprime (pair of) DFT filter banks (coprime DFTFB), which process signals like a spectral analyzer in time domain, divides the power spectrum equally into MN bands by employing two DFT filter banks (DFTFBs) of size only M and N respectively, where M and N are coprime integers. With coprime DFTFB, frequencies in wide sense stationary (WSS) signals can be effectively estimated with a much lower sampling rates than the Nyquist rates. However, the imperfection of practical FIR filter and the correlation based detection mode give rise to two kinds of spurious peaks in power spectrum estimation, that greatly limit the application of coprime DFTFB. Through detailed analysis of the spurious peaks, this paper proposes a modified spectral analyzer based on dual coprime DFTFBs and sub-decimation, which not only depresses the spurious peaks, but also improves the frequency estimation accuracy. The mathematical principle proof of the proposed spectral analyzer is also provided. In discussion of simultaneous signals detection, an O-extended MN-band coprime DFTFB (OExt M-N coprime DFTFB) structure is naturally deduced, where M, N, and O are coprime with each other. The original MN-band coprime DFTFB (M-N coprime DFTFB) can be seen a special case of the OExt M-N coprime DFTFB with extending factor O equals ‘1’. In the numerical simulation section, BPSK signals with random carrier frequencies are employed to test the proposed spectral analyzer. The results of detection probability versus SNR curves through 1000 Monte Carlo experiments verify the effectiveness of the proposed spectrum analyzer.
ER -