Detection and parameter estimation of multicomponent LFM signals based on GST
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Affiliation:

1.College of Electrical and Information Engineering, Hunan University, Changsha 410082,China; 2.School of Electrical Engineering, Wuhan University, Wuhan 430072, China

Clc Number:

TN911.23

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    Abstract:

    In order to solve some problems that the signal is undetected in the low signaltonoise ratio(SNR), and the accuracy is not high of parameter estimation, the singular value decomposition (SVD) filtering is proposed on the basis of generalized S transform (GST) for multicomponent chirp signal (MLFM). On the basis of S transform, the generalized Stransform and inverse transformation formula are derived in the paper. The singular value of the generalized Stransform matrix is obtained by discrete singular value, and the multicomponent signal Timefrequency filtering is realized by selecting the appropriate singular value. The simulation results show that the method can effectively filter out the noise in the low SNR, and avoids the phenomenon of missed detection when the amplitude of each component signal is quite difference, the accuracy of the signal parameter estimation is optimized.

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  • Received:
  • Revised:
  • Adopted:
  • Online: January 24,2018
  • Published: