Classification of Underwater Target Echoes Based on Auditory Perception Characteristics

In underwater target detection, the bottom reverberation has some of the same properties as the target echo, which has a great impact on the performance. It is essential to study the difference between target echo and reverberation. In this paper, based on the unique advantage of human listening ability on objects distinction, the Gammatone filter is taken as the auditory model. In addition, time-frequency perception features and auditory spectral features are extracted for active sonar target echo and bottom reverberation separation. The features of the experimental data have good concentration characteristics in the same class and have a large amount of differences between different classes, which shows that this method can effectively distinguish between the target echo and reverberation.

Morphological Research on Geometrical Scattering Waves of an Underwater Target

In this paper, a new method based on morphologic research named reconstruction cross-component removal （RCCR） is developed to analyze geometrical scattering waves of an underwater target. Combining the origin of the cross-component in Wigner-ViUe distribution, the highlight model of target echoes and time-frequency features of linear frequency-modulated signal can remove cross-components produced by multiple component signals in Wigner-Ville distribution and recover the auto-components of output signals. This method is used in experimental data processing, which can strengthen the real geometric highlights, and restrain the cross components. It is demonstrated that this method is helpful to analyze the geometrical scattering waves, providing an effective solution to underwater target detection and recognition.

Line spectrum detection algorithm based on the phase feature of target radiated noise

In order to improve the performance of line spectrum detection,according to the feature that the underwater target radiated noise containing stable line spectrum,the differences of the phase difference between line spectrum and background noise,a weighted line spectrum detection algorithm based on the phase variance is proposed in frequency domain.After phase difference alignment,the phase variance of line spectrum and the phase of background noise,respectively,are small and big in frequency domain,this method utilizes the weighted statistical algorithm to cumulate the frequency spectrum based on the phase variance,which can restrain the background noise disturbance,and enhance the signal to noise ratio（SNR）.The theory analysis and experimental results both verify that the proposed method can well enhance the energy of line spectrum,restrain the energy of background noise,and have better detection performance under lower SNR.

Signal waveform design to detect an underwater high-speed small target

The problem of sonar signal waveform design to detect a high-speed small target in an underwater environment is discussed. From theoretical analysis, time-frequency hop signal is regarded as the most suitable signal waveform in this application. To get precise target parameter estimation ability, the signal should have high range-Doppler resolution performance. The results of signal analysis show that hop signal with frequency serial coding as Costas array has sharp ambiguity characteristic, so it can be used in an active sonar system to detect a high speed small target. A scheme of frequency coding is also presented.