| Signal parameter estimation has been widely used in many fields,such as military,communication,power system and voice processing.In practical detection engineering,the acquisition,acquisition and transmission of signals are unavoidable to be affected by various noises,and the actual research signals are all limited length signals.Therefore,it is of great value to study the parameter detection method of short-time signal under low signal-to-noise ratio.In this paper,the theory of maximum likelihood estimation,autocorrelation,parameter model,discrete Fourier transform and MUSIC algorithm are deeply studied,and the performance of the algorithm is compared through simulation experiments.On the basis of sufficiently summarizing the algorithms,this paper proposes an improved algorithm based on DFT algorithm and MUSIC algorithm to solve the problem of inadequate estimation accuracy of sinusoidal signal parameters under low signal-to-noise ratio(SNR).The main research work is as follows:A single-frequency sinusoidal signal parameter estimation algorithm based on double-threshold synthesis interpolation of DFT algorithm is proposed.The frequency estimation of DFT is corrected by interpolation method.The simulation results show that the estimation accuracy of the algorithm is improved obviously,the performance of the algorithm is closer to the CRB bound,the frequency estimation can be more accurate,and the amplitude estimation can be more accurate.A kind ofA multi-frequency sinusoidal signal parameter estimation algorithm based on MUSIC algorithm and quasi-Newton iteration is proposed.The peak search is optimized by quasi-Newton iteration algorithm,and the signal amplitude is estimated by least squares algorithm.The simulation results show that the computational complexity of the algorithm is significantly lower than that of MUSIC algorithm,and the estimation accuracy of the frequency and amplitude of the signal is improved under the condition of low signal-to-noise ratio. |
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