Vector hydrophone is the core equipment of underwater acoustic detection. Aiming at the problem of low sensitivity and short detection distance of existing vector hydrophone. In this paper, a hollow mushroom-like cilia sensitive structure is designed to optimize the hydrophone sensitive unit. The optimal size of the hollow mushroom-like cilia MEMS vector hydrophone (MCVH) microstructure was determined by COMSOL5.6 simulation. The hollow structure is adopted, which not only ensures the working bandwidth of the hydrophone is 20Hz-1000Hz, but also improves the sensitivity of the hydrophone by increasing the receiving area of the sound wave. The test results show that the hollow structure has obvious "8" directivity, and the pit depth of the "8" directivity larger than 40dB at 315Hz. Meantime, the sensitivity of MCVH can reach -180.9dB at 1000Hz. Compared with Ciliary MEMS vector hydrophone(CVH), the sensitivity is improved by 16.8dB.

The complex and variable ocean environment introduces complex noise to the signal received by microelectromechanical systems (MEMS) vector hydrophones, which seriously affects target location. To improve the detection efficiency and broaden the application range of vector hydrophone, this paper proposed a novel modified Wavelet packet de-noising method, known as the Wavelet packet energy (WPE) de-noising method. This method utilizes Shannon entropy to determine the optimal decomposition levels of Wavelet packets, and calculates the energy of reconstructed signals in each frequency band to construct feature vectors. The Wavelet packet with the larger energy is selected to reconstruct the signal until the root mean square error of the original signal and the reconstructed signal is minimized. thereby obtaining an optimal solution. The performance of this proposed method is evaluated through both indoor and outdoor experiments. The experimental results demonstrate that the developed method is effective in Direction of Arrival (DOA) estimation of single frequency signals and is feasible in low signal-to-noise ratio situations. The method improves the azimuth discrimination ability of the Minimum Variance Distortionless Response algorithm, and DOA estimation errors are all within 1°. Furthermore, the indoor and outdoor experiments also demonstrate that the WPE de-noising method solves the group delay and distortion of signals caused by conventional filtering.

Ship noise observation is of great significance to marine environment research and national defense security. Acoustic stealth technology makes a variety of ship noise significantly reduced, which is a new challenge for marine noise monitoring. However, there are few high spatial gain detection methods for low-noise ship monitoring. Therefore, a high Signal-to-Noise Ratio (SNR) MEMS noise listener for ship noise detection is developed in this paper. The listener achieves considerable gain by suppressing isotropic noise in the ocean. The working principle and posterior end signal processing method of the listener are introduced in detail. A gain of 10 dB over the sound pressure detector is obtained by detecting the standard sound source. In addition, the traffic vessel noise monitoring experiment verifies that the listener can detect the ship noise. The results show that the listener has a very broad application prospect in the field of low-noise ship observation.

The main frequency band of the radiated signals from ships is 20-500Hz, and also the main working frequency band of the Micro-Electro-Mechanical-System ( MEMS ) vector hydrophone. To improve sensitivity in this frequency band, this paper presents a nested package structure, which encapsulates the sensitive sections of the vector hydrophone with a mesh-like interior support and a sound-transparent cap. By COMSOL Multiphysics 6.0 simulation, the particle acceleration and intrinsic frequency of the hydrophone with different interior supports and sound-transparent cap are compared and analyzed. The simulation results show that the hydrophone encapsulated with nylon interior support and latex acoustic cap has higher acceleration, and its intrinsic frequency is 2285.1 Hz in air and 804.64 Hz underwater. The results of the testing indicate that the nested package hydrophone designed in this paper has a bandwidth of 10-800Hz, meeting the main working frequency band of the hydrophone. Additionally, the sensitivity of the hydrophone with latex encapsulation is increased by 7.8dB@100Hz than polyurethane encapsulation. The depth of the notch at 100Hz and 500Hz is more than 30dB, which indicates that the hydrophone has good dipole directivity. Compared with the traditional polyurethane-packaged hydrophone, the nested package structure can effectively improve the performance of the hydrophone.

Real-time DOA (direction of arrival) estimation of surface or underwater targets is of great significance to the research of marine environment and national security protection. When conducting real-time DOA estimation of underwater targets, it can be difficult to extract the prior characteristics of noise due to the complexity and variability of the marine environment. Therefore, the accuracy of target orientation in the absence of a known noise is significantly reduced, thereby presenting an additional challenge for the DOA estimation of the marine targets in real-time. Aiming at the problem of real-time DOA estimation of acoustic targets in complex environments, this paper applies the MEMS vector hydrophone with a small size and high sensitivity to sense the conditions of the ocean environment and change the structural parameters in the adaptive adjustments system itself to obtain the desired target signal, proposes a signal processing method when the prior characteristics of noise are unknown. Theoretical analysis and experimental verification show that the method can achieve accurate real-time DOA estimation of the target, achieve an error within 3.1° under the SNR (signal-to-noise ratio) of the X channel of −17 dB, and maintain a stable value when the SNR continues to decrease. The results show that this method has a very broad application prospect in the field of ocean monitoring.

Aiming at the problems of low azimuth estimation accuracy and wide beam width of single vector hydrophone in low signal-to-noise ratio (SNR) environment, this paper proposes an azimuth estimation algorithm based on matched filter and adaptive noise residual accumulation of sound pressure vibration frequency deconvolution (MF-FDAC). This method uses the frequency domain output signal of each channel of the MEMS vector hydrophone after matched filtering, and finds that the two velocity components still show the sine and cosine weighting characteristics of the sound pressure propagation direction in the expression. By convoluting the frequency domain signal and using the residual energy difference between the output of the adaptive canceller on the target azimuth and the non-target azimuth, the target azimuth is estimated. The simulation results show that the root mean square error of the proposed algorithm is about 9° and the detection probability is 0.45 when the SNR is −10dB. The experimental results show that the maximum error of DOA estimation is 2° when the SNR is -7dB. In summary, compared with Conventional BeamForming(CBF), Multiple Signal Classification(MUSIC) and other algorithms, the proposed method has higher resolution, lower azimuth estimation error and more robust azimuth estimation ability under low SNR conditions.