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Frequency estimation algorithm based on non-orthogonal decomposition

WANG Jian-ying YIN Zhong-ke CHEN lei(School of Information Science & Technology,Southwest Jiaotong University,Chengdu Sichuan 610031,China)  
A new algorithm is proposed to achieve high-resolution frequency estimation which is intensively studied and has been widely applied to many areas in signal processing.In this paper,the idea of sparse decomposition,which is a non-orthogonal decomposition of signals,is introduced into high-resolution frequency estimation study.Since the choice of dictionaries is not limited,the sparse decomposition provides extremely flexible signal representations.The sparse decomposition is implemented by matching pursuit(MP)in the proposed algorithm.Frequency estimation can be then achieved according to the parameters of the decomposition atoms.The new algorithm can obtain higher frequency estimation resolution than most frequency estimation methods based on DFT,especially in the circumstance of lower signal to noise ratio.It is also applicable in the circumstance of under sampling.Theoretic analysis as well as experimental results illustrates the properties of the proposed algorithm.
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