Multi frequency hopping network station sorting based on joint feature clustering in complex environment

Abstract

In order to remove interference from hybrid signals and sort each frequency hopping station signal, a multi frequency hopping network station sorting algorithm based on joint feature clustering was proposed.Firstly, short-time Fourier transform was applied to the sorted hybrid signals to obtain the time-frequency matrix, and adaptive threshold denoising was carried out according to the energy distribution histogram of time-frequency matrix.Secondly, the sweep interference was removed by morphological filtering.Thirdly, the connected domain was labeled, the duration and average energy of each signal were calculated to remove the fixed frequency interference, and the joint feature vector for each frequency hop was formed.Finally, the MeanShift algorithm was used to cluster and analyze the joint feature vectors of each segment of the signal, completing the sorting of each frequency hopping signal.The simulation results show that the proposed algorithm has higher sorting rate, stronger anti-interference ability and wider applicability to hybrid signals compared with the traditional algorithm.

Keywords

• frequency hopping signal;network station sorting;MeanShift;time-frequency analysis;connected domain labeling