Analysis of FM Signals Based on Viterbi Synchrosqueezing S-transform in Mixture Noise

Mingzhe ZHU; Rui XIAO; Xiaofan SU; Guanghui WANG

doi:10.11999/JEIT171091

Volume 40 Issue 12

Nov. 2018

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(12): 2913-2918

Mingzhe ZHU, Rui XIAO, Xiaofan SU, Guanghui WANG. Analysis of FM Signals Based on Viterbi Synchrosqueezing S-transform in Mixture Noise[J]. Journal of Electronics & Information Technology, 2018, 40(12): 2913-2918. doi: 10.11999/JEIT171091

Citation:

Mingzhe ZHU, Rui XIAO, Xiaofan SU, Guanghui WANG. Analysis of FM Signals Based on Viterbi Synchrosqueezing S-transform in Mixture Noise[J]. Journal of Electronics & Information Technology, 2018, 40(12): 2913-2918. doi: 10.11999/JEIT171091

Citation:

PDF( 1559 KB)

Analysis of FM Signals Based on Viterbi Synchrosqueezing S-transform in Mixture Noise

doi: 10.11999/JEIT171091

1.
School of Electronic Engineering, Xidian University, Xi’an 710071, China
2.
Department of Computer Science, Nanjing University, Nanjing 211102, China

Funds: The National Natural Science Foundation of China(61701374), The Natural Science Foundation of Shannxi Province(JB160210), The Fundamental Research Foundation of the Central Universities, The Innovation Foundation of Xidian University

Received Date: 2017-11-20
Rev Recd Date: 2018-09-12

Available Online: 2018-09-18

Publish Date: 2018-12-01

Abstract

Abstract

A new robust Generalized Synchrosqueezing S-Transform(GSST) is proposed to solve the distortion problem of SynchroSqueezing S-Transform(SSST) in mixture noise. Firstly, the method improves the Viterbi algorithm for improving the Time-Frequency(TF) analysis performance of S-transform in alpha-gaussian mixture noise. After acquiring the phase locus information of the FM signal, the synchrosqueezing is used to improve the time-frequency aggregation. The simulation results show that the proposed method can accurately obtain the time-frequency information of FM signal under the background of Alpha-Gaussian mixture noise in low SNR, and has a better robustness and applicability than the SST.
- Viterbi algorithm,
- Synchrosqueezing transform,
- Alpha-Gaussian mixture noise,
- Varying-tendency window S-transform

FullText(HTML)

References(17)

References

DAUBECHIES I, LU Jianfeng, and WU H T. Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool[J]. Applied and Computational Harmonic Analysis, 2011, 30(2): 243–261 doi: 10.1016/j.acha.2010.08.002

BRAJOVIC M, POPOVIC-BUGARIN V, DJUROVIC I, et al. Post-processing of time-frequency representations in instantaneous frequency estimation based on ant colony optimization[J]. Signal Processing, 2017, 138: 195–210 doi: 10.1016/j.sigpro.2017.03.022

OBERLIN T, MEIGNEN S, and PERRIER V. Second-order synchrosqueezing transform or invertible reassignment? towards ideal time-frequency representations[J]. IEEE Transactions on Signal Processing, 2015, 63(5): 1335–1344 doi: 10.1109/TSP.2015.2391077

PHAM D and MEIGNEN S. High-order synchrosqueezing transform for multicomponent signals analysis - with an application to gravitational-wave signal[J]. IEEE Transactions on Signal Processing, 2017, 65(12): 3168–3178 doi: 10.1109/TSP.2017.2686355

AUGER F, FLANDRIN P, LIN Yuting, et al. Time-frequency reassignment and synchrosqueezing: An overview[J]. IEEE Signal Processing Magazine, 2013, 30(6): 32–41 doi: 10.1109/MSP.2013.2265316

STOCKWELL R, MANSINHA L, and LOWE R. Localization of the complex spectrum: The S transform[J]. IEEE Transactions on Signal Processing, 1996, 44(4): 998–1001 doi: 10.1109/78.492555

朱明哲, 姬红兵, 林琳, 等. 基于方向性S变换的多分量FM信号瞬时频率估计[J]. 系统工程与电子技术, 2013, 35(1): 29–33 doi: 10.3969/j.issn.1001-506X.2013.01.05

ZHU Mingzhe, JI Hongbing, LIN Lin, et al. Instantaneous frequency estimation of multicomponent FM signals based on directional S transform[J]. Systems Engineering and Electronics, 2013, 35(1): 29–33 doi: 10.3969/j.issn.1001-506X.2013.01.05

BOASHASH B. Estimating and interpreting the instantaneous frequency of a signal[J]. Proceedings of the IEEE, 1992, 80(4): 520–538 doi: 10.1109/5.135376

BARKAT B and BOASHASH B. Instantaneous frequency estimation of polynomial FM signals using the peak of the PWVD: Statistical performance in the presence of additive gaussian noise[J]. IEEE Transactions on Signal Processing, 1999, 47(9): 2480–2490 doi: 10.1109/78.782191

DJUROVIC I and STANKOVIC L. An algorithm for the Wigner distribution based instantaneous frequency estimation in a high noise environment[J]. Signal Processing, 2004, 84(3): 631–643 doi: 10.1016/j.sigpro.2003.12.006

STANKOVIC L, DJUROVIC I, OHSUMI A, et al. Instantaneous frequency estimation by using Wigner distribution and Viterbi algorithm[C]. IEEE International Conference on, Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP’03). Hong Kong, China, 2003, 6: VI-121-4. doi: 10.1109/ICASSP.2003.1201633.

LI Po, WANG Dechun, and WANG Lu. Separation of micro-Doppler signals based on time frequency filter and Viterbi algorithm[J]. Signal Image&Video Process, 2013, 7(3): 593–605 doi: 10.1007/s11760-011-0263-3

LI Po and ZHANG Qinghai. An improved Viterbi algorithm for IF extraction of multicomponent signals[J]. Signal Image&Video Process, 2017(7): 1–9 doi: 10.1007/s11760-017-1143-2

金艳, 武艳凤, 姬红兵. 基于a稳定分布噪声稀疏性及最优匹配的跳频信号参数估计[J]. 电子与信息学报, 2017, 39(10): 2413–2420 doi: 10.11999/JEIT161397

JIN Yan, WU Yanfeng, and JI Hongbing. Parameter estimation of FH Signals based on a stable noise sparsity and optimal match[J]. Journal of Electronics&Information Technology, 2017, 39(10): 2413–2420 doi: 10.11999/JEIT161397

李兵兵, 马洪帅, 刘明骞. Alpha稳定分布噪声下时频重叠信号的载波频率估计方法[J]. 电子与信息学报, 2014, 36(4): 868–874 doi: 10.3724/SP.J.1146.2013.00827

LI Bingbing, MA Hongshuai, and LIU Mingqian. Carrier frequency estimation method of time-frequency overlapped signals with alpha-stable noise[J]. Journal of Electronics&Information Technology, 2014, 36(4): 868–874 doi: 10.3724/SP.J.1146.2013.00827

金艳, 高舵, 姬红兵. 复杂噪声下基于同步压缩Chirplet变换的LFM信号参数估计[J]. 电子与信息学报, 2017, 39(8): 1906–1912 doi: 10.11999/JEIT161222

JIN Yan, GAO Duo, and JI Hongbing. Parameter estimation of LFM signals based on synchrosqueezing Chirplet transform in complicated noise[J]. Journal of Electronics&Information Technology, 2017, 39(8): 1906–1912 doi: 10.11999/JEIT161222

HUANG Zhonglai, ZHANG Jianzhong, ZHAO Tiehu, et al. Synchrosqueezing S-transform and its application in seismic spectral decomposition[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(2): 817–825 doi: 10.1109/TGRS.2015.2466660

Relative Articles

Supplements(0)

Cited By

Proportional views