A Parameter Estimation Method of Frequency Hopping Signal Based On Sparse Time-frequency Method

Author(s):  
Yongzhi Wang ◽  
Yun Lin ◽  
Xiuwei Chi
Author(s):  
Zengke Wang ◽  
Yi Li ◽  
Wei Xu

In order to effectively estimate the parameters of the frequency hopping signals under low signal-to-noise ratio (SNR), a blind parameter estimation method based on the modified discrete time Wigner-Ville distribution (MDTWVD) is proposed. We choose a low order Chebyshev polynomial as the kernel function for reducing the cross-term. Then, the parameters of the frequency hopping signals are finally obtained from the MDTWVD. The simulation experiment results show that the method used in this paper can effectively and accurately estimate frequency hopping signals parameters, especially under low SNR condition compared with other estimating methods.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jian-wei Yang ◽  
Man-feng Dou ◽  
Zhi-yong Dai

Taking advantage of the high reliability, multiphase permanent magnet synchronous motors (PMSMs), such as five-phase PMSM and six-phase PMSM, are widely used in fault-tolerant control applications. And one of the important fault-tolerant control problems is fault diagnosis. In most existing literatures, the fault diagnosis problem focuses on the three-phase PMSM. In this paper, compared to the most existing fault diagnosis approaches, a fault diagnosis method for Interturn short circuit (ITSC) fault of five-phase PMSM based on the trust region algorithm is presented. This paper has two contributions. (1) Analyzing the physical parameters of the motor, such as resistances and inductances, a novel mathematic model for ITSC fault of five-phase PMSM is established. (2) Introducing an object function related to the Interturn short circuit ratio, the fault parameters identification problem is reformulated as the extreme seeking problem. A trust region algorithm based parameter estimation method is proposed for tracking the actual Interturn short circuit ratio. The simulation and experimental results have validated the effectiveness of the proposed parameter estimation method.


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