Frequency hopping signal detection based on time-frequency spectral entropy

To realize the detection of Frequency hopping (FH) signal in low signal-to-noise ratio (SNR) environment and the presence of fixed-frequency interference, this paper proposes a FH signal detection algorithm based on time-frequency spectral entropy. The proposed algorithm employs a time-frequency matrix to compute the entropy value of each frequency component of the signal. Thereby obtaining the time-frequency spectral entropy of the signal. Subsequently, the algorithm enables the blind detection of the FH signal by leveraging the differences in the time-frequency spectral entropy between the FH signal, fixed-frequency signal and Gaussian white noise. Simulation results show that the proposed algorithm is capable of effectively detecting FH signal in low SNR, even in the presence of fixed-frequency interference signals, the detection probability for FH signal reaches 97% at a SNR of -20 dB. Furthermore, the detection performance of the proposed algorithm surpasses that of the comparative algorithms.