Frequency hopping signal parameter estimation algorithm based on time-frequency point correlation

Abstract

Aiming at the low accuracy of frequency hopping signal parameter estimation under the influence of complex noise and interference, a frequency-hopping signal parameter estimation algorithm based on time-frequency point correlation is proposed. First, we design the kernel function to obtain the time-frequency distribution of the frequency-hopping signal. Then, we use the correlation of the time-frequency points to establish the target transfer relationship model. Besides, the feature quantity combines density screening is used for hierarchical clustering, and ridge queuing methods filter out the interference ridge label. Finally, we perform parameter estimation on the frequency hopping ridge. The simulation results show that the parameter error estimated by the proposed algorithm continues to decrease with the improvement of the signal-to-noise ratio. In the case of −6dB, the error of each parameter is as low as about 0.1. This algorithm can completely extract the frequency hopping ridge under the condition of a low signal-to-noise ratio, achieve an excellent parameter estimation effect, and provide a reference for communication signal parameter estimation.