TY - JOUR
T1 - Quantitative SNR analysis of QFM signals in the LPFT domain with Gaussian windows
AU - Zhang, Yan Na
AU - Li, Bing Zhao
AU - Goel, Navdeep
AU - Gabarda, Salvador
N1 - Publisher Copyright:
© 2018, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - The purpose of this paper is to present a quantitative SNR analysis of quadratic frequency modulated (QFM) signals. This analysis is located in the continuous-time local polynomial Fourier transform (LPFT) domain using a Gaussian window function based on the definition of 3 dB signal-to-noise ratio (SNR). First, the maximum value of the local polynomial periodogram (LPP), and the 3 dB bandwidth in the LPFT domain for a QFM signal is derived, respectively. Then, based on these results, the 3 dB SNR of a QFM signal with Gaussian window function is given in the LPFT domain with one novel idea highlighted: the relationship among standard SNR, parameters of QFM signals and Gaussian window function is clear, and the potential application is demonstrated in the parameter estimation of a QFM signal using the LPFT. Moreover, the 3 dB SNR in the LPFT domain is compared with that in the linear canonical transform (LCT) domain. The validity of theoretical derivations is confirmed via simulation results. It is shown that, in terms of SNR, QFM signals in the LPFT domain can achieve a significantly better performance than those in the LCT domain.
AB - The purpose of this paper is to present a quantitative SNR analysis of quadratic frequency modulated (QFM) signals. This analysis is located in the continuous-time local polynomial Fourier transform (LPFT) domain using a Gaussian window function based on the definition of 3 dB signal-to-noise ratio (SNR). First, the maximum value of the local polynomial periodogram (LPP), and the 3 dB bandwidth in the LPFT domain for a QFM signal is derived, respectively. Then, based on these results, the 3 dB SNR of a QFM signal with Gaussian window function is given in the LPFT domain with one novel idea highlighted: the relationship among standard SNR, parameters of QFM signals and Gaussian window function is clear, and the potential application is demonstrated in the parameter estimation of a QFM signal using the LPFT. Moreover, the 3 dB SNR in the LPFT domain is compared with that in the linear canonical transform (LCT) domain. The validity of theoretical derivations is confirmed via simulation results. It is shown that, in terms of SNR, QFM signals in the LPFT domain can achieve a significantly better performance than those in the LCT domain.
KW - SNR analysis
KW - linear canonical transform
KW - local polynomial Fourier transform
KW - quadratic frequency modulated signal
KW - time frequency representations
UR - http://www.scopus.com/inward/record.url?scp=85056108930&partnerID=8YFLogxK
U2 - 10.1007/s11432-017-9322-2
DO - 10.1007/s11432-017-9322-2
M3 - Article
AN - SCOPUS:85056108930
SN - 1674-733X
VL - 62
JO - Science China Information Sciences
JF - Science China Information Sciences
IS - 2
M1 - 22302
ER -