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Weak Signal Detection Method of Adaptive Digital Lock-in Amplifier Based on Particle Swarm Optimization Algorithm

机译:基于粒子群优化算法的自适应数字锁放大器弱信号检测方法

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In this paper, an intelligent algorithm--Particle Swarm Optimization (PSO) is applied to adaptively realize weak sinusoidal signal detection of digital lock-in amplifier. Each particle is a reference signal. Using this algorithm PSO first searches the optimum particle of particle swarm, and then estimates the corresponding parameters of input useful signal through the messages of the optimum particle. The algorithm can realize detection of weak signal by modifying its some parameters, so it is more convenient and flexible than the method of traditional lock-in amplifier (LIA) in application. Computer simulation results show that this method can accurately detect multiple useful sinusoidal signals which are inundated by strong noise of-40 dB, and also detect AM signal. Then the effectiveness of this method is verified by AM signal.
机译:本文采用了一种智能算法 - 粒子群优化(PSO)以自适应地实现数字锁定放大器的弱正弦信号检测。每个粒子是参考信号。使用该算法PSO首先搜索粒子群的最佳粒子,然后通过最佳粒子的消息估计输入有用信号的相应参数。该算法通过修改其一些参数,可以实现弱信号的检测,因此它比在应用中的传统锁定放大器(LIA)的方法更方便灵活。计算机仿真结果表明,该方法可以准确地检测多种有用的正弦信号,该信号通过强烈的40dB噪声淹没,并且还检测AM信号。然后AM信号验证该方法的有效性。

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