Mixing Matrix Estimation of Frequency Hopping Signals Based on Single Source Points Detection

To improve the mixing matrix estimation performance of frequency hopping (Fit) signals under the underdetermined blind source separation (UBSS) model, a new estimation method is proposed in this paper. First, time frequency (TF) analysis is utilized to obtain sparse TF data. Then, remove the low-energy TF points to avoid the effect of noises and reduce the amount of calculation. Next, detect the single source points (SSPs) with the derived formula. Finally, the dynamic data field clustering method is utilized to estimate the mixing matrix. The results of simulation experiments indicate that the proposed algorithm has better performance than the compared algorithms.