基于SS过程的分数低阶时频自回归滑动平均模型参数估计及时频分布

龙俊波; 汪海滨

doi:10.11999/JEIT151066

基于SS过程的分数低阶时频自回归滑动平均模型参数估计及时频分布

doi: 10.11999/JEIT151066

龙俊波¹,
汪海滨²

1.
(九江学院电子工程学院九江 332005) ②(九江学院信息科学与技术学院九江 332005)

基金项目:

国家自然科学基金(61261046, 61362038)，江西省自然科学基金(20142BAB207006)，江西省教育厅科技基金(GJJ14738, GJJ14739)

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- 被引次数: 0
出版历程
- 收稿日期: 2015-09-21
- 修回日期: 2016-04-28
- 刊出日期: 2016-07-19

Parameter Estimation and Time-frequency Distribution of Fractional Lower Order Time-frequency Auto-regressive Moving Average Model Algorithm Based on SS Process

LONG Junbo¹,
WANG Haibin²

1.
(College of Electronic and Engineering, Jiujiang University, Jiujiang 332005, China)
2.
(College of Information Science and Technology, Jiujiang University, Jiujiang 332005, China)

Funds:

The National Natural Science Foundation of China (61261046, 61362038), The Natural Science Foundation of Jiangxi Province (20142BAB207006), The Research Foundation of Education Bureau of Jiangxi Province (GJJ14738, GJJ14739)

摘要

摘要: 针对SS过程下时频自回归滑动平均(TFARMA)模型分析方法的退化，该文用分数低阶共变取代二阶相关提出了分数低阶时频自回归滑动平均(FLO-TFARMA)模型的概念，并推导了模型参数的求解方法。在此基础上，给出了FLO- TFARMA模型时频谱估计算法，和已有的TFARMA模型时频谱算法进行了详细的比较。计算机仿真结果表明，在SS过程环境下，所提出的FLO-TFARMA时频谱明显优于TFARMA时频谱，尤其是当参数较小时，FLO-TFARMA时频谱优势更明显。
- 信号处理 /
- 信号处理 /
- 稳定分布 /
- 非平稳信号 /
- 时频分布 /
- 自回归滑动平均 /
- 尤拉沃克方程
Abstract: The performances of Time-Frequency Auto-Regressive Moving Average (TFARMA) model method degenerate underSS distribution environment. Hence, Fractional Lower Order Time-Frequency Auto- Regressive Moving Average (FLO-TFARMA) model algorithm based on fractional lower order covariant is proposed, the parameters estimation of FLO-TFARMA model is introduced, time-frequency distribution based on FLO-TFARMA model is given, FLO-TFARMA model algorithm are compared with the existing TFARMA algorithm in detail. The simulation results show that FLO-TFARMA model method have better performance than TFARMA model method underSS distribution environment, and the time-frequency spectrum of FLO- TFARMA method is more obvious when the parameter is smaller.
- Signal processing /
- stable distribution /
- Non-stationary signal /
- Time-frequency distribution /
- Auto- Regressive Moving Average (ARMA) /
- Yule-Walker equations /

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参考文献(24)

JACHAN M, MATZ G, and HLAWATSCH F. Least-squares and maximum-likelihood TFAR parameter estimation for nonstarionary processes[C]. IEEE ICASSP-2006, Toulouse, France, 2006: 492-495.

JACHAN M, MATZ G, and HLAWATSCH F. Time- frequency autoregressive random processes: Modeling and fast parameter estimation[C]. IEEE ICASSP-2003, Hong Kong, China, 2003: 125-128.

JACHAN M, MATZ G, and HLAWATSCH F. Vector time- frequency AR Models for nonstationary multivariate random processes[J]. IEEE Transactions on Signal Processing, 2009, 57(12): 4646-4658.

JACHAN M, MATZ G, and HLAWATSCH F. Time- frequency-moving-average processes: Principles and cepstral methods for paramerer estimation[C]. IEEE ICASSP-2004, Quebec, Canada, 2004: 757-760.

GRENIER Y. Time-dependent ARMA modeling of nonstationary signals[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1983, 31(4): 899-911.

SPIRIDONAKOS M D and FASSOIS S D. Non-stationary random vibration modelling and analysis via functional series time-dependent ARMA (FS-TARMA) models-a critical survey[J]. Mechanical Systems Signal Processing, 2014, 47(3): 175-224.

JACHAN M, MATZ G, and HLAWATSCH F. Time- frequency ARMA models and parameter estimators for underspread nonstationary random processes[J]. IEEE Transactions on Signal Processing, 2007, 55(9): 4366-4380.

FENG Z P, LIANG M, and CHU F L. Recent advances in time-frequency analysis methods for machinery fault diagnosis: A review with application examples[J]. Mechanical Systems and Signal Processing, 2013, 3(38): 165-205.

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.

KOMATY A, BOUDRA A O, and NOLAN J P. On the behavior of EMD and MEMD in presence of symmetric-stable noise[J]. IEEE Signal Processing Letters, 2015, 22(7): 818-822.

龙俊波, 汪海滨, 查代奉. 无限方差噪声环境下的分数低阶空间时频盲源分离[J]. 信号处理, 2014, 30(10): 1150-1156.

LONG Junbo, WANG Haibin, and ZHA Daifeng. Fractional lower order spatial time-frequency blind source separation in infinite variance noise environment[J]. Journal of Signal Processing, 2014, 30(10): 1150-1156.

PELE D T. A approach for estimating the parameters of an alpha-stable distribution[C]. International Conference on Applied Statistics (ICAS), Chamonix, France, 2014: 68-77.

赵新明, 金艳, 姬红兵. 稳定分布噪声下基于Merid 滤波的跳频信号参数估计[J]. 电子与信息学报, 2014, 36(8): 1878-1883. doi: 10.3724/SP.J.1146.2013.01436.

ZHAO Xinming, JIN Yan, and JI Hongbing. Parameter estimation of frequency-hopping signals based on merid filter in a stable noise environment[J]. Journal of Electronics Information Technology, 2014, 36(8): 1878-1883. doi: 10. 3724/SP.J.1146.2013.01436.

王首勇, 朱晓波, 李旭涛, 等. 基于分数低阶协方差的AR 模型谱估计[J]. 电子学报, 2007, 35(9): 1637-1641.

WANG Shouyong, ZHU Xiaobo, LI Xutao, et al. - spectrum estimation for AR processes based on FLOC[J]. Acta Electronica Sinica, 2007, 35(9): 1637-1641.

王首勇, 朱晓波. 基于FLOC的ARMA 模型谱估计方法[J]. 通信学报, 2007, 28(7): 98-103.

WANG Shouyong and ZHU Xiaobo. -spectrum estimation method for ARMA process based on FLOC[J]. Journal on Communications, 2007, 28(7): 98-103.

WANG H B, LONG J B, and ZHA D F. Pseudo cohen time- frequency distributions in infinite variance noise environment [J]. Applied Mechanics and Materials, 2014, 475/476: 253-258.

龙俊波, 汪海滨, 查代奉. 基于稳定分布噪声的分数低阶自适应时频分布[J]. 计算机工程, 2011, 37(18): 81-83.

LONG Junbo, WANG Haibin, and ZHA Daifeng. Fractional low-order adaptive time-frequency distribution based on stable distribution noise[J]. Computer Engineering, 2011, 37(18): 81-83.

MA X Y and NIKIAS C L. Parameter estimation and blind channel identification in impulsive signal environments[J]. IEEE Transactions on Signal Processing, 1995, 43(12): 2884-2897.

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