The accuracy of time delay estimation seriously affects the accuracy of sound source localization. In order to improve the accuracy of time delay estimation under the condition of low SNR, a delay estimation optimization algorithm based on singular value decomposition and improved GCC-PHAT weighting (GCC-PHAT-$\rho \gamma$ weighting) is proposed. Firstly, the acoustic signal collected by the acoustic sensor array is subjected to singular value decomposition and noise reduction processing to improve the signal-to-noise ratio of the signal; then, the cross-correlation operation is performed, and the cross-correlation function is processed by the GCC-PHAT-$\rho \gamma$ weighting method to obtain the cross-power spectrum; finally, the inverse transformation is performed to obtain the generalized correlation time domain function, and the peak detection is performed to obtain the delay difference. The experiment was carried out in a large outdoor pool, and the experimental data were processed to compare the time delay estimation performance of three methods: GCC-PHAT weighting, SVD-GCC-PHAT weighting (meaning: GCC-PHAT weighting based on singular value decomposition) and SVD-GCC-PHAT-$\rho \gamma$ weighting (meaning: GCC-PHAT-$\rho \gamma$ weighting based on singular value decomposition). The results show that the delay estimation optimization algorithm based on SVD-GCC-PHAT-$\rho \gamma$ improves the delay estimation accuracy by at least 37.95% compared with the other two methods. The new optimization algorithm has good delay estimation performance.

The accuracy of underwater sound source localization depends on the preprocessing effect of signal denoising and delay estimation performance. In order to meet the needs of high-precision underwater positioning, this article studies a time delay estimation method based on nonlocal mean-enforced mean empirical mode decomposition (NLM-EEMD) autocorrelation denoising preprocessing and fuzzy C-means clustering (FCM)-generalized quadratic for underwater sound source localization technology. The theories such as NLM, EEMD, FCM, and generalized quadratic correlation delay estimation are studied in detail, and the speech signal of the test library in the TIMIT standard library is selected for simulation analysis, which verifies the correctness of the delay estimation method. Experiments were carried out in a larger outdoor pool. The analysis results show that the NLM-EEMD adaptive denoising method effectively reduces noise interference and improves the quality of EEMD decomposition and the FCM-generalized quadratic correlation method increases the correlation between two signals. The time delay estimation accuracy is improved, and the positioning accuracy is 48.66% higher than that of the direct generalized cross-correlation method.

With the increasingly complex marine environment, the propagation of underwater acoustic signals is often severely interfered by complex background noise, which seriously affects the signal quality and subsequently affects the detection and recognition ability of sensors for underwater targets. Regarding this challenge, this paper proposes a novel method called DBO–VMD–SVD. This method utilizes the Dung Beetle Optimization (DBO) algorithm to optimize Variational Mode Decomposition (VMD) and combines it with Singular Value Decomposition (SVD). First, the DBO method is used to optimize the VMD parameters and obtain several modal components. Second, the adaptive threshold is calculated by comprehensively considering the correlation coefficient and the multivariate permutation entropy, and it is used as the basis for selecting effective modal components and reconstructing the signal. Finally, the obtained signal is further processed using the SVD method. The innovation of the method proposed in this article is mainly reflected in (1) using the DBO algorithm to avoid manually setting VMD parameters based on experience, (2) using adaptive threshold to select intrinsic mode function (IMF) components, and (3) combining the VMD method with the SVD method. In an effort to verify the performance of the DBO–VMD–SVD method, it was used to denoise Lorenz signals at different signal-to-noise ratios (SNRs) and compared with methods such as VMD and VMD–SVD. The results show that our proposed method has a more significant denoising effect, exhibiting certain advantages in evaluation indicators, such as SNR and root mean square error. After processing with this method, the geometric structure of the signal becomes more regular. Moreover, it was applied to the noise reduction of real underwater acoustic signals. The simulation results show that after processing by this method, noise intensity, correlation dimension, and permutation entropy all decreased. Taking signal-1 as an example, the three evaluation indicators decreased by 14.5%, 14.7%, and 41.1%, respectively. In addition, the phase diagram became more regular, more clearly restoring the topological structure of the chaotic attractor. This paper provides a novel approach for improving underwater target detection and recognition capabilities, optimizing underwater acoustic communication quality, and other related research.

A piezoelectric flextensional transducer was designed using the finite element method (FEM) for the passive detection of underwater frogmen. By studying the main performance parameters of sonar transducers for the detection of frogmen around the world, this paper presents the advantages of active and passive sonar in this task and proposes a passive method for the detection of frogmen. Subsequently, a Cymbal transducer was selected considering the needs of the research. After introducing the principles and methods of the FEM analysis, the acoustic and electromechanical characteristics of the Cymbal transducer were verified under the influence of structural dimensions, e.g., resonance frequency, conductance, and susceptance. The electromechanical performance of the Cymbal transducer was simulated with a FEM to study how it is affected by static water pressure and processing errors and to demonstrate the feasible application of the Cymbal transducer in practical applications. In the end, a Cymbal prototype was tested to verify that the designed Cymbal transducer performs in compliance with the requirements and can be used for the passive detection of underwater frogmen with open-circuit breathing.

A multi-resonance Cymbal hydrophone for detection of the open-circuit self-contained underwater breathing apparatus (scuba) diver was designed and fabricated in this work, which has the advantages of multi-resonant frequency, high sensitivity, and narrow bandwidth. By using standard hydrophones, the underwater acoustic signal of the open-circuit scuba diver in the pool was collected and the characteristics of the signal were analyzed: the signal was mainly distributed in high frequency and low frequency. According to this characteristic, a Cymbal hydrophone with multi-resonance frequencies was designed in the finite element method, and the resonant frequency, receiving sensitivity, and bandwidth of the hydrophone were calculated. The accuracy of the calculation was verified with the performance test of the prototypes fabricated in this work. Finally, the underwater acoustic signal of an open-circuit scuba diver in the pool was tested by the prototype to demonstrate that the multi-resonance Cymbal hydrophone developed in this paper can be used for open-circuit scuba diver detection.

In order to keep the angular velocity output of unmanned aerial vehicle (UAV) swarm consistent, a solution is proposed in this paper. Firstly, a reasonable simplified modeling is carried out for UAV, and its linear part is selected to set the output consistency controller. Then, based on graph theory and lyapunov stability theorem, the asymptotic stability conditions of the designed controller are given. Finally, the effectiveness of the proposed method is verified by simulation. The results show that the designed controller can quickly keep the output angular velocity of UAV swarm consistent.