Acoustic target recognition algorithm based on particle swarm neural network
Yalei Liu, GU Xiao-hui · IOP Conference Series Materials Science and Engineering · 2020
Abstract In order to improve the automatic recognition rate of acoustic targets, this paper conducts research on acoustic target recognition algorithms based on particle swarm neural network. Firstly, the mathematical description of the particle swarm optimization algorithm is described, and the initial parameters and algorithm flow of the particle swarm optimization algorithm in the experiments in this paper are given. Second, the design includes the central processor, power supply, signal conditioner, filter, trigger circuit, and state. Acoustic target recognition prototypes of display circuit, memory, target type indication circuit, serial port, crystal circuit, microphone and hardware interface circuit, etc. Finally, using the collected acoustic signals of tanks and helicopters, a semi-physical simulation experiment was designed to carry out target recognition. Experimental research and experimental results verify the effectiveness and stability of the acoustic target recognition system in this paper.