Stochastic resonance can detect weak periodic signals from strong background noise without loss of signal energy. However, the classical bistable stochastic resonance has the inherent output saturation defect, which limits the detection performance of system. And it is more difficult to detect signal with strong background noise. In this article, we constructed improved unsaturated bistable stochastic resonance to overcome this shortcoming. The improved bistable potential function makes the output signal more easily oscillate in two potential wells. To improve the stability and the accuracy of the method, we further propose an adaptive improved unsaturated bistable stochastic resonance (AIUBSR) by constructing a synthetic index (SI). The SI combines zero-crossing ratio and structural correlation coefficient, which can measure the periodicity of output signal and the accuracy of detective frequency at the same time. Theoretical analysis and numerical simulations show that the proposed AIUBSR can have good weak signal detection capability in strong background noise.

中文翻译：

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基于弱信号检测的自适应改进非饱和双稳态随机共振方法

随机共振可以在不损失信号能量的情况下从强背景噪声中检测出微弱的周期信号。然而，经典的双稳态随机谐振具有固有的输出饱和缺陷，限制了系统的检测性能。并且背景噪声强的信号更难检测。在本文中，我们构建了改进的不饱和双稳态随机共振来克服这个缺点。改进的双稳态势函数使输出信号更容易在两个势阱中振荡。为了提高方法的稳定性和准确性，我们通过构建合成指数（SI）进一步提出了一种自适应改进的不饱和双稳态随机共振（AIUBSR）。SI 结合了过零比和结构相关系数，可同时测量输出信号的周期性和检测频率的精度。理论分析和数值模拟表明，所提出的AIUBSR在强背景噪声下具有良好的弱信号检测能力。