In order to overcome the long learning time caused by searching optimal basic function data based on greedy strategy from a redundant basis function dictionary for the Intuitionistic Fuzzy Kernel Matching Pursuit(IFKMP)

the particle swarm optimization algorithm with powerful ability of global search and quick convergence rate is applied to speed up searching optimal basic function data in function dictionary.And the approach of intuitionistic fuzzy kernel matching pursuit based on particle swarm optimization algorithm

namely PS-IFKMP

is proposed.This algorithm is applied to the aero target recognition

which requires real-time ability.Simulation results show that

compared with the conventional approaches

the proposed algorithm can decrease training time and improve calculation efficiency obviously leaving the classification accuracy almost unchanged

while the model has better sparsity and generalization.It is also demonstrated that this approach is much suitable to the application requiring both accuracy and efficiency.