Underwater AUV detection method for adaptive matching stochastic resonance

Abstract

The invention provides an underwater AUV detection method for adaptive matching stochastic resonance, comprising the following steps: whitening a received time domain signal, establishing a second-order nonlinear bistable stochastic resonance system, and implementing the noise matching and frequency matching by optimizing a output signal-to-noise ratio gain measure and synchronous gramer escape rate; according to a set step size, selecting a maximum signal-to-noise ratio as an optimal matching value, and extracting a corresponding signal frequency as a target characteristic line spectrum frequency; and using the work kurtosis as a test statistic to determine whether the signal is present or not. According to the underwater AUV detection method for the adaptive matching stochastic resonance, signal energy and a local signal-to-noise ratio at a target characteristic line spectrum can be greatly improved, and an output of a characteristic signal in completely submerged noise can be obviously enhanced.

Description

technical field [0001] The invention relates to the field of underwater target detection and signal detection, in particular to a weak signal detection method. Background technique [0002] In recent years, research on passive detection of small underwater targets such as surface boats and underwater unmanned vehicles (AUVs) has gradually become a new research hotspot in the field of underwater information at home and abroad. Compared with traditional surface ships and submarines, the new underwater unmanned vehicle has the advantages of small size and low noise. With the advanced acoustic stealth technology and the increasing demand for the detection radius of underwater early warning systems in the new era, the ability of traditional methods to perceive and extract key features of such emerging weak and small targets in water is facing new challenges. [0003] In the field of signal detection, the stochastic resonance weak signal detection method has attracted the attenti...

AI Technical Summary

Problems solved by technology

Scale transformation uses the idea of ​​spectrum shifting to move high-frequency signals to low frequencies, but in the process of processing high-frequency signals, it is necessary to design a suitable filter to preprocess the signal, and the effect of resonance often depends on the design of the filter , poor adaptability to the actual environment

[0007] At present, it is difficult to detect small targets such as underwater AUVs in the marine environment. There are also big problems in introducing the adaptive frequency sweep method into underwater AUV target detection. One is the low signal-to-noise ratio in the marine environment, and the other is the traditional The stochastic resonance frequency sweep method has a large amount of calculation, difficult engineering implementation, and low efficiency

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