An Improved Central Frequency Estimation Method for Frequency-Hopping Signal

A New Frequency Hopping Signal Detection of Civil UAV Based on Improved K-Means Clustering Algorithm

“…FH signal detection methods are mainly frequency domain and time domain detection. Common frequency domain analysis methods include Fourier transform [16], wavelet analysis [17][18], Wigner-Ville distribution [19], spectrogram, etc. [20][21][22].…”

“…The paper in [14] propose an improved channelized MWC scheme for non-cooperative detection and frequency estimation of FHSS signals, by adjusting the channel weighting factor, it can better adapt to the single hop width, greatly reduce the amount of calculation, and achieve good results compared to the traditional method, but only based on theoretical analysis and numerical simulations, and not real implementation of channelized MWC. In [15][16] [19] papers, a novel method based on sparse linear regression to solve the problem of computation burden in parameters estimate, which the results are only better on hop timing estimation, the estimation performance of other parameters is general.An approach based on frequency difference and one-dimensional non-linear filter has been proposed in [18], which the robustness against white Gaussian noise has been enhanced but need SNR is greater than 13 dB which is an extremely harsh precondition, and is also reflected in [20], the author propose a detection scheme based on the Neyman-Pearson test, and the results shows better than method of autocorrelation-based when the hopping period is short, and so on. the front papers methods almost set a harsh precondition, or manual parameter, and also not make a real environment experiment within multiple frequency hopping signals active, lacking of persuasion of practical application.…”