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This paper aims to solve the problem that strong noise interference seriously affects the direction of arrival (DOA) estimation in complex underwater acoustic environment. In this paper, a combined noise reduction algorithm and micro-electro-mechanical system (MEMS) vector hydrophone DOA estimation algorithm based on singular value decomposition (SVD), variational mode decomposition (VMD) and wavelet threshold denoising (WTD) is proposed.

Firstly, the parameters of VMD are determined by SVD, and the VMD method can decompose the signal into multiple intrinsic mode functions (IMFs). Secondly, the effective IMF component is determined according to the correlation coefficient criterion and the IMF less than the threshold is processed by WTD. Then, reconstruction is carried out to achieve the purpose of denoising and calibration baseline drift. Finally, DOA estimation is achieved by the combined directional algorithm of preprocessed signal.

Simulation and field experiments results show that the algorithm has good noise reduction and baseline drift correction effects for nonstationary underwater signals, and high-precision azimuth estimation is realized.

This research provides the basis for MEMS hydrophone detection and positioning and has great engineering significance in underwater detection system.

The purpose of this paper is to examine the current farm economic downturn and credit restructuring by comparing it with the 1920s and 1980s farm crises from both economic and regulatory perspectives.

This paper closely compares critical economic and regulatory aspects of the current farm downturn with two previous farm crises in the 1920s and 1980s, and equally importantly, the golden eras that occurred before them. This study compares key aggregate statistics in land value, agricultural credit, lending regulations, and also evaluates the situations and impacts on individual farmer households by using three representative case studies.

The authors argue that there are at least three economic and regulatory reasons why the current farm downturn is unlikely to slide into a sudden collapse of the agricultural markets: strong, real income; growth in the 2000s, historically low interest rates; and more prudent agricultural lending practices. The current farm downturn is more likely a liquidity and working capital problem, as opposed to a solvency and balance sheet problem for the overall agricultural sector. The authors argue that the trajectory of the current farm downturn will likely be a gradual, drawn-out one like that of the 1920s farm crisis, as opposed to a sudden collapse as in the 1980s farm crisis.

The review provides empirical evidence for cautious optimism of the future trajectory of the current downturn, and argues that the current downturn is much more similar to the 1920s pattern than the 1980s crisis.

This study aims to simulate and test the performance of a transmitting and receiving capacitive micro-machined ultrasonic transducer (CMUT). Aimed at detecting demand of the CMUT, a matched integrated adjustment circuit was designed through analyzing processing methods of transducer’s weak echo signal.

Based on the analysis of CMUT array structure and work principle, the CMUT units are designed and the dynamic performance analysis of SIMULINK is given according to the demand of underwater detecting. A transceiver isolation circuit is used to make transmission mode and receiving mode separate. A detection circuit is designed based on the transimpedance amplifier to achieve extraction of high-frequency and weak signal.

Through experimentation, the effectiveness of the CMUT performance simulation and the transceiver integrated adjustment circuit were verified. In addition, the test showed that CMUT with 400 kHz frequency has wider bandwidth and better dynamic characteristics than other similar transducers.

This paper provides a theoretical basis and design reference for the development and application of CMUT technology.

This paper aims to address the challenges in hydroacoustic signal detection, signal distortion and target localization caused by baseline drift. The authors propose a combined algorithm that integrates short-time Fourier transform (STFT) detection, smoothness priors approach (SPA), attitude calibration and direction of arrival (DOA) estimation for micro-electro-mechanical system vector hydrophones.

Initially, STFT method screens target signals with baseline drift in low signal-to-noise ratio environments, facilitating easier subsequent processing. Next, SPA is applied to the screened target signal, effectively removing the baseline drift, and combined with filtering to improve the signal-to-noise ratio. Then, vector channel amplitudes are corrected using attitude correction with 2D compass data. Finally, the absolute target azimuth is estimated using the minimum variance distortion-free response beamformer.

Simulation and experimental results demonstrate that the SPA outperforms high-pass filtering in removing baseline drift and is comparable to the effectiveness of variational mode decomposition, with significantly shorter processing times, making it more suitable for real-time applications. The detection performance of the STFT method is superior to instantaneous correlation detection and sample entropy methods. The final DOA estimation achieves an accuracy within 2°, enabling precise target azimuth estimation.

To the best of the authors’ knowledge, this study is the first to apply SPA to baseline drift removal in hydroacoustic signals, significantly enhancing the efficiency and accuracy of signal processing. It demonstrates the method’s outstanding performance in the field of underwater signal processing. In addition, it confirms the reliability and feasibility of STFT for signal detection in the presence of baseline drift.

Ciliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed.

Based on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference.

The three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized.

This algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

Human-induced marine environmental noise, such as commercial shipping and seismic exploration, is concentrated in the low-frequency range. Meanwhile, low-frequency sound signals can achieve long-distance propagation in water. To meet the requirements of long-distance underwater detection and communication, this paper aims to propose an micro-electro-mechanical system (MEMS) flexible conformal hydrophone for low-frequency underwater acoustic signals. The substrate of the proposed hydrophone is polyimide, with silicon as the piezoresistive unit.

This paper proposes a MEMS heterojunction integration process for preparing flexible conformal hydrophones. In addition, sensors prepared based on this process are non-contact flexible sensors that can detect weak signals or small deformations.

The experimental results indicate that making devices with this process cannot only achieve heterogeneous integration of silicon film, metal wire and polyimide, but also allow for customized positions of the silicon film as needed. The success rate of silicon film transfer printing is over 95%. When a stress of 1 Pa is applied on the x-axis or y-axis, the maximum stress on Si as a pie-zoresistive material is above, and the average stress on the Si film is around.

The flexible conformal vector hydrophone prepared by heterogeneous integration technology provides ideas for underwater acoustic communication and signal acquisition of biomimetic flexible robotic fish.

The problem of port and starboard ambiguity will exist when only utilize the vector or scalar parameters. Meanwhile, the amplitude-phase error between the vector and scalar can also cause this problem. In this paper, a compound MEMS vector hydrophone which contains cilia vector microstructure and piezoelectric ceramic tube has been presented to solve the problem. Compared with traditional MEMS vector hydrophone, the compound MEMS vector hydrophone can realize the measurement of sound pressure and vibration velocity simultaneously.

A compound MEMS vector hydrophone has been presented. The unipolar directivity of the combined signal which combine the acoustic pressure and vibration velocity is used to achieve the direction of arrival (DOA). This paper introduced the working principle and the target detection mechanism of the compound vector hydrophone. The amplitude and phase error are analyzed and corrected in the standing wave tube. After that, the authors use beam-forming algorithm to estimate the DOA.

The experimental results in the standing wave tube and the external field verified the vector hydrophone's directional accuracy up to 1 and 5 degrees, respectively.

The research of compound vector hydrophone plays an important role in marine acoustic exploration and engineering applications.

This research provides a basis for MEMS hydrophone directivity theory. The compound vector hydrophone has been applied in the underwater location, with a huge market potential in underwater detection systems.

Based on the micro-electro-mechanical system (MEMS) technology, acoustic emission sensors have gained popularity owing to their small size, consistency, affordability and easy integration. This study aims to provide direction for the advancement of MEMS acoustic emission sensors and predict their future potential for structural health detection of microprecision instruments.

This paper summarizes the recent research progress of three MEMS acoustic emission sensors, compares their individual strengths and weaknesses, analyzes their research focus and predicts their development trend in the future.

Piezoresistive, piezoelectric and capacitive MEMS acoustic emission sensors are the three main streams of MEMS acoustic emission sensors, which have their own advantages and disadvantages. The existing research has not been applied in practice, and MEMS acoustic emission sensor still needs further research in the aspects of wide frequency/high sensitivity, good robustness and integration with complementary metal oxide semiconductor. MEMS acoustic emission sensor has great development potential.

In this paper, the existing research achievements of MEMS acoustic emission sensors are described systematically, and the further development direction of MEMS acoustic emission sensors in the future research field is pointed out. It provides an important reference value for the actual weak acoustic emission signal detection in narrow structures.

Because of the small size and high integration of capacitive micromachined ultrasonic transducer (CMUT) component, it can be made into large-scale array, but this lead to high hardware complexity, so the purpose of this paper is to use less elements to achieve better imaging results. In this research, an optimized sparse array is studied, which can suppress the side lobe and reduce the imaging artifacts compared with the equispaced sparse array with the same number of elements.

Genetic algorithm is used to sparse the CMUT linear array, and Kaiser window apodization is added to reduce imaging artifacts, the beam pattern and peak-to-side lobe ratio are calculated, point targets imaging comparisons are performed. Furthermore, a 256-elements CMUT linear array is used to carry out the imaging experiment of embedded mass and forearm blood vessel, and the imaging results are compared quantitatively.

Through the imaging comparison of embedded mass and forearm blood vessel, the feasibility of optimized sparse array of CMUT is verified, and the purpose of reducing the hardware complexity is achieved.

This research provides a basis for the large-scale CMUT array to reduce the hardware complexity and the amount of calculation. At present, the CMUT array has been used in medical ultrasound imaging and has huge market potential.

In acoustic detection technology, optical microcavities offer higher detection bandwidth and sensitivity than traditional acoustic sensors. However, research on acoustic detection technologies involving optical microcavities has not yet been reported. Therefore, this paper aims to design and construct an underwater acoustic detection system based on optical microcavities and study its acoustic detection technology to improve its performance.

Based on the principles of optical microcavity acoustic sensors, a signal-detection circuit was designed to form a detection system in conjunction with a laser, an optical waveguide resonator and an oscilloscope. This circuit consists of two modules: a photodetection module and a filter amplification module.

The photodetection module features a baseline noise of −106.499 dBm and can detect device spectral line depths of up to 2410 mV. The gain stability of the filter amplification module was 58 dB ± 1 dB with a noise gain of −107.626 dBm. This design allows the acoustic detection system to detect signals with high sensitivity within the 10 Hz−1.2 MHz frequency band, achieving a maximum sensitivity of −126 dB re 1 V/µPa at 800 Hz and a minimum detectable pressure (MDP) of 0.37 mPa/Hz^1/2, corresponding to a noise equivalent pressure (NEP) of 51.36 dB re 1 V/µPa.

This study designs and constructs a broadband underwater acoustic detection system specifically for optical waveguide resonators based on the sensing principles of silicon dioxide optical waveguide resonators. Experiments demonstrated that the signal detection module improves the sensitivity of underwater acoustic detection based on optical waveguides.