Acoustic superlens provides a way to overcome the diffraction limit with respect to the wavelength of the bulk wave in air. However, the operating frequency range of subwavelength imaging is quite narrow. Here, an acoustic superlens is designed using Helmholtz-resonator-based metamaterials to broaden the bandwidth of super-resolution. An experiment is carried out to verify subwavelength imaging of double slits, the imaging of which can be well resolved in the frequency range from 570 to 650 Hz. Different from previous works based on the Fabry-Pérot resonance, the corresponding mechanism of subwavelength imaging is the Fano resonance, and the strong coupling between the neighbouring Helmholtz resonators separated at the subwavelength interval leads to the enhanced sound transmission over a relatively wide frequency range.
Measurements along two ship tracks were obtained in an experiment to investigate the properties of acoustic propagation over the continental slope in the South China Sea. The measured data show a notable difference in transmission loss about 35 dB as sound crosses different geodesic paths. Numerical simulations indicate that the range and azimuth-dependent geological properties control the level of the transmission loss and lead to this large transmission loss fluctuation. In addition, the model also suggests some small-scale features of horizontal refraction effect caused by irregular topography, but they are not observed in the measured data.
It has been demonstrated that an estimate of an empirical Green's function (EGF) can be extracted from the ocean ambient noise cross-correlation functions, which can provide an alternative method for ocean acoustic tomography. However, the requirement for a long recording time to obtain EGFs with a high signal-to-noise ratio limits the application. This article focuses on using array signal processing to accelerate the convergence rate of EGFs between two horizontally separated arrays. With the extracted EGFs and data assimilation, ocean sound speed profiles (SSPs) can be inverted every 2 h in shallow water. The experimental results indicate that the variation in ocean SSPs can be reconstructed with reasonable agreement using an average variance of 1.14 m/s over three months.
Ambient noise was recorded continuously for 9 months by two horizontal arrays deployed in shallow water with a horizontal separation of approximately 0.5 km. Stable empirical Green's functions (EGFs) were extracted from ambient noise correlations between the two arrays. The EGFs have three distinct envelopes which correspond to the head waves, direct waves, and surface-reflected waves. The arrival time of the head wave was almost constant with season. Corresponding simulations were carried out, and implied that the relatively small penetration depth of heat flow is the main reason for the seasonally-invariant head wave speed.
The acoustic pressure field in many underwater environments is well described by a superposition of normal modes. The normal modes can be used for source localization and environmental inversion. However, the wavenumber resolution of traditional normal mode filtering methods for a small-aperture horizontal array is usually not sufficient to identify individual modes in a shallow water waveguide. This paper proposes an original method of normal mode energy estimation to remove the energy leakage between modes. The modal energy is defined as the square of the modal amplitude. This method is to reconstruct the incoherent beamformed outputs in wavenumber domain for a horizontally moving source. The adaptive beamforming is used to suppress interference and improve output signal-to-noise ratio. The uncertainty of modal phase velocity has also been considered in this method. The proposed method can provide more accurate estimates of modal energy for a small-aperture horizontal array than the traditional mode filtering methods, such as the matched filter, the least squares mode filter, the regularized-least squares mode filter, and the maximum a posteriori mode filter, in simulations and experiments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.