A Weak Acoustic Signal Line-Spectrum Detection Method Based on Stochastic Resonance

With the technology development of ship damping and noise reduction, the received underwater target signal energy becomes smaller, and the traditional detection method is difficult to extract the characteristic line spectrum from the low signal-to-noise ratio environment. Stochastic resonance, as a nonlinear weak signal detection method, can improve the signal-to-noise ratio of the system output signal by making full use of noise rather than eliminating or reducing it and is an effective way to break through the low signal-to-noise ratio limitation of line spectrum detection. This paper proposes a double population genetic algorithm based multi-parameter simultaneous optimized twice sampling stochastic resonance line spectrum detection algorithm. The double population genetic algorithm has both strong local search ability and global search ability. The signal-to-noise ratio of the output signal of the system is taken as the fitness function of the double population genetic algorithm to realize synchronous adaptive selection of multiple parameters of the stochastic resonance system, while the twice sampling algorithm is introduced to realize stochastic resonance under large parameter environment, and the received signal is input to the optimized stochastic resonance system to realize the target feature enhancement and line spectrum detection. It is verified through simulation that the proposed method can achieve effective line spectrum detection under low signal-to-noise ratio environment, which has good application prospects and research value.