Abstract
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.
Reference13 articles.
1. Research on depression detection algorithm combine acoustic rhythm with sparse face recognition [J];Zhao;Cluster Computing: The Journal of Networks, Software Tools and Applications,2019
2. Automatic Detection System for Cough Sounds as a Symptom of Abnormal Health Condition [J];Shin;IEEE Transactions on Information Technology in Biomedicine,2009
3. Robust automatic target recognition using learning classifier systems [J];Ravichandran;Information Fusion,2007
4. Acoustic system for aircraft detection and tracking based on passive microphones arrays;Gaetano