Improved de-interleaving algorithm of radar pulses based on dual fuzzy vigilance ART

As a core part of the electronic warfare (EW) system, de-interleaving is used to separate interleaved radar signals. The de-interleaving algorithm based on the fuzzy adaptive resonance theory (fuzzy ART) is plagued by the problems of premature saturation and performance improving dilemma. This study proposes a dual fuzzy vigilance ART (DFV-ART) algorithm to address these problems and make the following improvements. Firstly, a correction method is introduced to prevent the network from prematurely saturating; then, the fuzzy vigilance models (FVM) are constructed to replace the conventional vigilance parameter, reducing the error probability in the overlapping region; finally, a dual vigilance mechanism is introduced to solve the performance improving dilemma. Simulation results show that the proposed algorithm could improve the clustering accuracy (quantization error dropped 60%) and the de-interleaving performance (clustering quality increased by 10%) while suppressing the excessive proliferation of categories.