级联随机共振线谱检测粒子群优化算法

Cascaded Stochastic Resonance Line Spectrum Detection Based on Particle Swarm Optimization Algorithm

针对水声探测领域中对低信噪比水下目标进行线谱检测这一难点,提出一种基于粒子群算法的级联型随机共振系统检测方法。利用粒子群算法自适应地调整系统参数,解决了随机共振系统检测未知频率的低信噪比水下目标时参数选取困难的问题,并通过系统级联有效提高了目标信噪比。经仿真验证,该方法能够自适应地调整随机共振系统至最优状态,可以有效对-20 dB的目标信号进行线谱检测。该方法可以使随机共振系统的效果充分发挥,保证水下目标探测工作的可行性和可靠性。

For the difficulty to line spectrum detection of the low SNR underwater target in the field of underwater acoustic detection,this paper proposed a cascaded stochastic resonance based on particle swarm optimization algorithm and this method was tested in line spectrum detection.Using particle swarm optimization to adjust system parameters adaptively solved the difficulty of parameters selection problem when the stochastic resonance system detected the low SNR underwater target with unknown frequency,and through the cascaded system effectively improved the SNR.Simulation results showed that this method could adaptively adjust the stochastic resonance system to the optimal state,and could effectively detect the line spectrum of the-20 dB target signal.This method could give full play to the effect of the stochastic resonance system and ensured the feasibility and reliability of underwater target detection.