Time-frequency analysis of frequency hopping signal based on partial reconstruction

The existing frequency hopping (FH) signal analysis methods have the disadvantages of poor time-frequency resolution and low noise suppression ability. Because of the large bandwidth feature of the FH signal, the time-frequency analysis methods are confined to the high sampling rate. In order to solve these problems, the compressive sensing (CS) is applied to the time-frequency analysis of FH signals. Firstly, according to the FH signal model, the sparse feature of the FH signal is analyzed and the sparse dictionary is constructed. Then, the time-frequency analysis algorithm of FH signal is proposed using the partial reconstruction algorithm proposed in this paper, the principle of the method is analyzed. Finally, the effectiveness of the proposed method is demonstrated by numerical simulation. The numerical experiment results show that the method can obtain the time-frequency analysis results of FH signals effectively. The time-frequency analysis results have the advantage of high time-frequency resolution and simple calculation under the condition that the sampling rate of the FH signal is greatly reduced.