论文部分内容阅读
针对无线传感器网络在地面目标声振信号识别方面的应用需求,在分析现有算法缺点的基础上,提出了基于粒子群优化(particle swarm optimization,PSO)方法的目标识别算法。利用粒子群算法优化基于模糊逻辑规则的分类器(fuzzy logic rule based classifier,FLRBC),分析了算法中各个参数的设置对算法性能的影响。基于实地采集到的信号的仿真实验表明,该方法在一定程度上提高了目标识别的正确率和稳定性,平衡了分类性能,改善了收敛性质。
Aiming at the application requirements of WSN on ground target acoustic signal recognition, this paper proposes a target recognition algorithm based on particle swarm optimization (PSO) based on the analysis of the disadvantages of the existing algorithms. Particle swarm optimization (PSO) is used to optimize the fuzzy logic rule based classifier (FLRBC), and the influence of the setting of each parameter on the performance of the algorithm is analyzed. The simulation experiments based on the collected signals show that this method improves the accuracy and stability of target recognition to a certain extent, balances the classification performance and improves the convergence property.