The optical images quality in dark underwater background is usually degraded, influencing the results of accurate identification, terrain mapping and seabed exploration. Thus, the super-resolution methods for dark underwater optical images attract extensive research interest. In this work, the SwinIR model is provided for dark underwater optical images super-resolution. Here, the EUVP DARK dataset with dark underwater background is employed, which clusters 5500 paired images. The SwinIR networks has high speed of process with large-size image capability and plentiful image detail. Compared with the traditional SRGAN method, the super-resolution reconstruction speed increases about 18.3%, and the peak pignal-to-noise ratio (PSNR) and structural similarity (SSIM) of SwinIR test results on the EUVP DARK dataset increase by 14.4% and 15.8% respectively, the results illustrate that our method improving the accuracy and quality of reconstruction. In conclusion, the hierarchical structure of SwinIR and self-attention mechanism adaptive attention weights in generated to the image, enabling precise adjustment and control of detail and texture. This method provides an efficient approach to dark underwater image quality enhancement.
Underwater optical images are affected by light attenuation, scattering, noise, etc., resulting in low image quality. Therefore, it is extremely significant to improve image quality and optimize network detection performance for underwater target detection. In this work, a YOLOv8-based underwater target detection method via image enhancement is provided, making full utilization of its advantages in large-scale feature learning. To address the issue of insufficient detection accuracy of the YOLOv8 algorithm on the original optical underwater target dataset, we employ an image fusion-based image enhancement method to improve underwater optical image quality. Combining different weights and scales, this method fuses multiple enhanced images to eliminate scattering and color bias, which enhances target features significantly. The results illustrate that the designed YOLOv8-based algorithm via image enhancement improves the precision by 20.5% and exhibits better performance in small, multiple and overlapping targets scenarios, where this algorithm gives a promising way for underwater optics target detection.
This paper reports a compact yet highly sensitive all-optical acoustic pressure sensor which is designed to operate under a pre-designed resonant mode, targeting to achieve ultra-high sensitivity for underwater applications. It consists of a micro-opto-mechanical silicon cantilever beam which is fabricated by a CMOS-compatible process flow based on a silicon-on-insulator (SOI) substrate, and integrated with a rib waveguide located on the top of the cantilever beam. Two grooves are created on the same substrate and aligned in line with the rib waveguide. Two optical fibers are then fixed into the pre-aligned two grooves on both sides of the rib waveguide, separately, for optical signal coupling in and out. The deflection of the cantilever beam caused by the acoustic waves is transferred to a variation of the output optical intensity from the optical fiber due to the fiber-to-waveguide end coupling strategy. For proof of concept, a silicon cantilever beam with a length of 9.5 mm, a width of 2.5 mm and a thickness of 10 μm is fabricated to provide an ultra highly sensitive acoustic sensor operating at the frequency of 150 Hz. The results show that an acoustic pressure detection sensitivity of 8.34 V/Pa with the minimum detectable acoustic pressures of 35 nPa/Hz1/2 at the designed frequency is successfully demonstrated. The proposed acoustic pressure sensor may be useful in particular applications such as defense and security equipment, as it is different from most existing acoustic pressure sensors which pursue a compromise between high sensitivity and wide working bandwidth.
A sonobuoy system based on a fiber optic vector hydrophone (FOVH) is demonstrated. Phase Generated Carrier– Arctangent (PGC-ATAN) demodulation algorithm was used to acquire real-time underwater acoustic signals. After the optimal design of the laser configuration, the background noise of the FOVH is -104.3dB re rad √ Hz at 1 kHz, with an acceleration sensitivity of 41.5dB re rad/g which allows the system detecting signals at DSS0. The theoretical derivation of FOVH directivity is proposed and the design criterion is discussed. The ratio of the minimum to the maximum amplitude of the FOVH directivity is -35dB by symmetrical structure design of the FOVH. A lake trial shows that the maximum detection range of the sonobuoy system is more than 15km for an acoustic signal of 210dB re μPa, and the bearing of a moving target can be estimated.
In asymmetrical suspension systems, triaxial signals' phase differences of fiber optic vector hydrophones are nonzero, which is a serious problem for direction of arrival (DOA) estimations of underwater acoustic signals. In this paper, an asymmetrical suspension system is described. Dynamics analysis of the suspension system is performed by using the analytic geometry method. Triaxial resonant frequencies of the suspension system are gotten, phase delays between the outer signals and the hydrophone's triaxial signals are derived, and influence of the suspension system on phase differences in low frequency zone is theoretically explained and simulated. Then frequency responses of the hydrophone in four suspension states are tested in a standing wave tube. The results indicate that both phase differences of xy axes and zy axes are large at resonant frequencies of the suspension system, which is approximately coincided with the theoretical analysis. Phase difference of zy axes at frequency higher than 500 Hz is obvious, which results from resonant responses of the fiber optic vector hydrophone. It proves that symmetry of the suspension system has great influence on phase differences of the fiber optic vector hydrophones.
Deflections of the vertical (DOV) are normally ignored in the gravity compensation procedure, which become one of the primary error sources in inertial navigation. In a single-axis rotation INS/GPS system, bias of the gyro and the accelerometer can be ignored, the attitude error is mainly affected by DOV. In this paper, the ideal system assumption is abandoned and the influence of DOV on the attitude is comprehensively discussed, which can be divided into two parts i.e. the direct influence and the indirect influence. The attitude error tracks the DOV along the trajectory belongs to the former. A relatively fixed delay between the attitude error and the DOV belongs to the latter. The delay is essentially induced by the weak observability of the system to the violent DOV. Factors which affect the delay are carefully analyzed. The simulation results show that the delay is mainly affected by accuracies of the inertial sensors and the GPS. It decreases with the GPS accuracy increasing, but increases with the inertial sensor accuracy increasing. The process noise covariance matrix Q plays an important role. With analysis of the characteristics of the delay, influence of the DOV on attitude is studied further, which is necessary for the attitude correction in future.
A distributed optical fiber vibration sensing system based on compensating interferometer is established and a distributed
optical fiber vibration waveform detecting technology based on a MZ compensating interferometer and compensating
interference of Rayleigh backscattering lights in adjacent areas is put forward. In laboratory experiment, the sensing fiber
is a 2500m SM fiber. By exerting 500Hz PZT vibration signals on the fiber at 40m, 430m, and 2500m, the locations of
the signals are obtained by phase demodulation. But there is a crosstalk at 40m because of multiple scatterings. The
spatial resolution is 40m and the SNR is 18dB.
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