Abstract:

To satisfy the requirement of application on classification of acousticseismic signals of ground targets in wireless sensor networks, a target classification algorithm based on particle swarm optimization (PSO), which is used to train the fuzzy logic rule based classifier (FLRBC), is proposed after analyzing the shortages of existing algorithms, and effects of parameters on performance are analyzed. Experiments based on real signals indicate that this method can improve the classification rate and stability to a certain extent, balance the classification performance and enhance the convergence quality.