Abstract:

In order to solve the problem that the time-frequency ridge-based frequency hopping parameter estimation algorithm has large estimation error when the signal-to-noise ratio (SNR) is lower than -5 dB, and the method fails in the case of fixed-frequency interference, an improved algorithm is proposed. On the basis of short-time Fourier transform (STFT), the original time-frequency diagram is denoised by the iterative method. According to the difference of dwell time between the frequency hopping signal and the fixed-frequency interference, the k-means clustering algorithm is used to eliminate the fixed-frequency interference,and extract its time-frequency ridge. Then the singular point of the extracted time-frequency ridge is detected by Haar wavelet, and the frequency hopping period, start time and hopping frequency are estimated. The simulation results show that the proposed algorithm can accurately estimate the frequency hopping parameters under the condition that the SNR is lower than -5 dB and there is strong fixed-frequency interference, and the estimated results are better than the original algorithm.

Key words: time-frequency analysis, parameter estimation, time-frequency ridge, low SNR, fixed-frequency interference