A Blind Estimation Algorithm for Frequency Hopping Signal Parameters Based on Time-Frequency Optimization STFT-CA

In this paper, the problem of blind parameter estimation of frequency hopping signals is studied. The existing estimation algorithms have an impractical computational burden, and in response to this situation, the paper proposes a blind estimation algorithm STFT-CA algorithm based on time-frequency optimization and short-time Fourier transform of the hopping signal parameters. The algorithm preprocesses the frequency hopping signal by short-time Fourier transform (STFT), and then estimates the energy centers of the signal in the time and frequency components respectively, reassigns the components to achieve the correction and refinement of the spectral map, and subsequently obtains the parameter estimates by STFT correlation analysis and frequency splitting of the signal. The proposed method in the paper reduces the complexity of the traditional algorithm, and it is verified by experimental simulation that the method still has high accuracy of estimation at lower signal-to-noise ratio.