Parameter estimation of Fh data link signal based on time-frequency ridge

Abstract

To solve the problem of low estimation accuracy of FH data link signal parameters based on traditional time-frequency ridge method under low SNR, a time-frequency clustering estimation method based on GA optimization is proposed. Firstly, genetic algorithm is used to extract the time-frequency interval of STFT time-frequency diagram of data link signal; then the time-frequency ridge is extracted; finally, K-means clustering algorithm is used to estimate the frequency hopping frequency by classifying the time-frequency ridge with a cluster number of 6. Experimental results show that this method can accurately estimate the frequency hopping frequency under SNR =−18dB, and effectively improve the accuracy of parameter estimation under low signal-to-noise ratio compared with the traditional time-frequency ridge parameter estimation method.