Three-dimensional omnidirectional acoustic illusion

Acoustic waves are ubiquitous in human everyday experience, therefore, precise control over the deformation of acoustic waves is always extremely desirable, which can be used, for example, to transform or hide objects from incident waves. Acoustic illusion devices are generally implemented by transformation acoustics, which can deceive ears or sonar systems. Challenges remain, the complexed and extreme material parameters prescribed by coordinate transformation theory make the implementations particularly difficult, even with the help of acoustic metamaterials. Here, a novel method based on Fabry-Perot resonances offers a feasible solution for achieve three-dimensional (3D) omnidirectional passive acoustic illusion. We theoretically demonstrated perfect 3D acoustic illusion via Mie theory, reduced version is further designed numerically and implemented experimentally. In the future, our work opens new possibilities for the implementation of modern acoustic illusion devices, such as camouflage for anti-sonar detection.

Code Optimisation Framework for Multicode Sonar Systems

<p>The ocean is a temporally and spatially varying environment, the characteristics of which pose significant challenges to the development of effective underwater wireless communications and sensing systems. An underwater sensing system such as a sonar detects the presence of a known signal through correlation. It is advantageous to use multiple transducers to increase surveying area with reduced surveying costs and time. Each transducers is assigned a dedicated code. When using multiple codes, the sidelobes of auto- and crosscorrelations are restricted to theoretical limits known as bounds. Sets of codes must be optimised in order to achieve optimal correlation properties, and, achieve Sidelobe Level (SLL)s as low as possible. In this thesis, we present a novel code-optimisation method to optimise code-sets with any number of codes and up to any length of each code. We optimise code-sets for a matched filter for application in a multi-code sonar system. We first present our gradient-descent based algorithm to optimise sets of codes for flat and low crosscorrelations and autocorrelation sidelobes, including conformance of the magnitude of the samples of the codes to a target power profile. We incorporate the transducer frequency response and the channel effects into the optimisation algorithm. We compare the correlations of our optimised codes with the well-known Welch bound. We then present a method to widen the autocorrelation mainlobe and impose monotonicity. In many cases, we are able to achieve SLLs beyond the Welch bound. We study the Signal to Noise Ratio (SNR) improvement of the optimised codes for an Underwater Acoustic (UWA) channel. During its propagation, the acoustic wave suffers non-constant transmission loss which is compensated by the application of an appropriate Time Variable Gain (TVG). The effect of the TVG modifies the noise received with the signal. We show that in most cases, the matched filter is still the optimum filter. We also show that the accuracy in timing is very important in the application of the TVG to the received signal. We then incorporate Doppler tolerance into the existing optimisation algorithm. Our proposed method is able to optimise sets of codes for multiple Doppler scaling factors and non-integer delays in the arrival of the reflection, while still conforming to other constraints. We suggest designing mismatched filters to further reduce the SLLs, firstly using an existing Quadratically Constrained Qaudratic Program (QCQP) formulation and secondly, as a local optimisation problem, modifying our basic optimisation algorithm.</p>

Code Optimisation Framework for Multicode Sonar Systems

<p>The ocean is a temporally and spatially varying environment, the characteristics of which pose significant challenges to the development of effective underwater wireless communications and sensing systems. An underwater sensing system such as a sonar detects the presence of a known signal through correlation. It is advantageous to use multiple transducers to increase surveying area with reduced surveying costs and time. Each transducers is assigned a dedicated code. When using multiple codes, the sidelobes of auto- and crosscorrelations are restricted to theoretical limits known as bounds. Sets of codes must be optimised in order to achieve optimal correlation properties, and, achieve Sidelobe Level (SLL)s as low as possible. In this thesis, we present a novel code-optimisation method to optimise code-sets with any number of codes and up to any length of each code. We optimise code-sets for a matched filter for application in a multi-code sonar system. We first present our gradient-descent based algorithm to optimise sets of codes for flat and low crosscorrelations and autocorrelation sidelobes, including conformance of the magnitude of the samples of the codes to a target power profile. We incorporate the transducer frequency response and the channel effects into the optimisation algorithm. We compare the correlations of our optimised codes with the well-known Welch bound. We then present a method to widen the autocorrelation mainlobe and impose monotonicity. In many cases, we are able to achieve SLLs beyond the Welch bound. We study the Signal to Noise Ratio (SNR) improvement of the optimised codes for an Underwater Acoustic (UWA) channel. During its propagation, the acoustic wave suffers non-constant transmission loss which is compensated by the application of an appropriate Time Variable Gain (TVG). The effect of the TVG modifies the noise received with the signal. We show that in most cases, the matched filter is still the optimum filter. We also show that the accuracy in timing is very important in the application of the TVG to the received signal. We then incorporate Doppler tolerance into the existing optimisation algorithm. Our proposed method is able to optimise sets of codes for multiple Doppler scaling factors and non-integer delays in the arrival of the reflection, while still conforming to other constraints. We suggest designing mismatched filters to further reduce the SLLs, firstly using an existing Quadratically Constrained Qaudratic Program (QCQP) formulation and secondly, as a local optimisation problem, modifying our basic optimisation algorithm.</p>

Low Correlation Codes for Sonar Systems

<p>Sonar is a vital technology for the detection of objects in the water. Sonarsystems have been redefined over many decades, but research is still beingconducted into optimal detection methods. Codes, and the filters thatprocess the codes, have been at the forefront of this research. An importantobjective has been the minimization of interference caused by reflections.Matched filters are commonly used in sonar systems. They are equivalent tocorrelation filters, which are bound by the Welch bound. The Welch boundgoverns the minimum peak correlation for points outside of detection.This thesis investigated matched filters and their bounds, and it wasfound that by relaxing the condition for detection, properties beyond theWelch bound could be achieved. By relaxing these conditions, the Welchbound no longer applies, and so a modified Welch bound was developedto accurately investigate the nature of these codes. In this thesis, methodsto generate codes for these new codes were investigated. Generating codesfor a matched filter is a non-convex problem, so gradient based methodswere utilised. Methods to improve correlation and power characteristicswere developed, along with methods for mapping a sequence for use witha digital transmitter having particular limitations. Mis-matched filters wereused to improve signal characteristics that may be lost due to this mapping.The performance of the generated codes was evaluated, and the rela-tionships between input parameters and output properties of the resultingsignal were observed. These performance assessments demonstrate thattradeoffs are required between various properties, and a balance is neededto obtain codes useful for sonar. The optimization was parametrized by anexample set of requirements for sonar. The signals were found to meet the given requirements, and when compared to codes typically used in sonar,the optimized signals were shown to have significantly better correlationproperties. Furthermore, compared to the general bounds for the propertiesof codes, it was found that the new codes had nearly optimal properties,and performed better than equivalent codes bounded by the Welch bound.The performance of codes were also investigated in a water tank toverify their feasibility. There were several additional considerations whichlimit codes that can be tested, and once these are taken into account thetest provided a robust method to verify the design process. Initial testsshowed results that differed from simulations, but after the inclusion ofzero padding before upscaling, the results from empirical testing agreewith simulation.Summarizing the research in this thesis, a new set of codes were devel-oped using a gradient based optimization method. The codes were mappedto a digital transmitter, and the filter adjusted using a mis-matched filter. The optimization was shown to generate near optimal codes which met allthe given sonar system requirements</p>

Low Correlation Codes for Sonar Systems

<p>Sonar is a vital technology for the detection of objects in the water. Sonarsystems have been redefined over many decades, but research is still beingconducted into optimal detection methods. Codes, and the filters thatprocess the codes, have been at the forefront of this research. An importantobjective has been the minimization of interference caused by reflections.Matched filters are commonly used in sonar systems. They are equivalent tocorrelation filters, which are bound by the Welch bound. The Welch boundgoverns the minimum peak correlation for points outside of detection.This thesis investigated matched filters and their bounds, and it wasfound that by relaxing the condition for detection, properties beyond theWelch bound could be achieved. By relaxing these conditions, the Welchbound no longer applies, and so a modified Welch bound was developedto accurately investigate the nature of these codes. In this thesis, methodsto generate codes for these new codes were investigated. Generating codesfor a matched filter is a non-convex problem, so gradient based methodswere utilised. Methods to improve correlation and power characteristicswere developed, along with methods for mapping a sequence for use witha digital transmitter having particular limitations. Mis-matched filters wereused to improve signal characteristics that may be lost due to this mapping.The performance of the generated codes was evaluated, and the rela-tionships between input parameters and output properties of the resultingsignal were observed. These performance assessments demonstrate thattradeoffs are required between various properties, and a balance is neededto obtain codes useful for sonar. The optimization was parametrized by anexample set of requirements for sonar. The signals were found to meet the given requirements, and when compared to codes typically used in sonar,the optimized signals were shown to have significantly better correlationproperties. Furthermore, compared to the general bounds for the propertiesof codes, it was found that the new codes had nearly optimal properties,and performed better than equivalent codes bounded by the Welch bound.The performance of codes were also investigated in a water tank toverify their feasibility. There were several additional considerations whichlimit codes that can be tested, and once these are taken into account thetest provided a robust method to verify the design process. Initial testsshowed results that differed from simulations, but after the inclusion ofzero padding before upscaling, the results from empirical testing agreewith simulation.Summarizing the research in this thesis, a new set of codes were devel-oped using a gradient based optimization method. The codes were mappedto a digital transmitter, and the filter adjusted using a mis-matched filter. The optimization was shown to generate near optimal codes which met allthe given sonar system requirements</p>

Fish Segmentation in Sonar Images by Mask R-CNN on Feature Maps of Conditional Random Fields

Imaging sonar systems are widely used for monitoring fish behavior in turbid or low ambient light waters. For analyzing fish behavior in sonar images, fish segmentation is often required. In this paper, Mask R-CNN is adopted for segmenting fish in sonar images. Sonar images acquired from different shallow waters can be quite different in the contrast between fish and the background. That difference can make Mask R-CNN trained on examples collected from one fish farm ineffective to fish segmentation for the other fish farms. In this paper, a preprocessing convolutional neural network (PreCNN) is proposed to provide “standardized” feature maps for Mask R-CNN and to ease applying Mask R-CNN trained for one fish farm to the others. PreCNN aims at decoupling learning of fish instances from learning of fish-cultured environments. PreCNN is a semantic segmentation network and integrated with conditional random fields. PreCNN can utilize successive sonar images and can be trained by semi-supervised learning to make use of unlabeled information. Experimental results have shown that Mask R-CNN on the output of PreCNN is more accurate than Mask R-CNN directly on sonar images. Applying Mask R-CNN plus PreCNN trained for one fish farm to new fish farms is also more effective.

Predicting subsurface sonar observations with satellite-derived ocean surface data in the California Current Ecosystem

Vessel-based sonar systems that focus on the water column provide valuable information on the distribution of underwater marine organisms, but such data are expensive to collect and limited in their spatiotemporal coverage. Satellite data, however, are widely available across large regions and provide information on surface ocean conditions. If satellite data can be linked to subsurface sonar measurements, it may be possible to predict marine life over broader spatial regions with higher frequency using satellite observations. Here, we use random forest models to evaluate the potential for predicting a sonar-derived proxy for subsurface biomass as a function of satellite imagery in the California Current Ecosystem. We find that satellite data may be useful for prediction under some circumstances, but across a range of sonar frequencies and depths, overall model performance was low. Performance in spatial interpolation tasks exceeded performance in spatial and temporal extrapolation, suggesting that this approach is not yet reliable for forecasting or spatial extrapolation. We conclude with some potential limitations and extensions of this work.

Formulation of technogenic underwater noise problem as a factor of state marine and transport policy

Object and purpose of research. The study addresses the technogenic underwater noise issues with a view to environmental and competitive challenges, as well as the Navy interests. Materials and methods. The issues studied in this investigation are relatively new for the Russian shipbuilding, shipping and marine activities, and the first step to systematic studies should be formulation of a technogenic noise problem as a physical phenomenon, which have to be considered in the state marine and transportation policy. The paper uses results of design studies performed in Krylov State research Centre, as well as information from mass media. The main sources of the technogenic underwater noise are coastal industries and port infrastructure, marine oil & gas structures, transport and ice-breaking vessels. Main results. It is concluded that a special-purpose integrated target program should be formulated and performed, whose result would be systematization of research and design projects aimed at the analysis, regulation and standardization of technogenic underwater noise parameters of various marine technologies. Conclusion. Technogenic underwater noise is directly related to the safety of marine ecosystems. In addition, it is a factor of commercial and large-scale economic competition in the international community. In future the technogenic underwater noise of marine facilities may become an instrument of competition for the opportunity and right to exploit Russian oil & gas deposits, as well as to use Russian Arctic routes. Against the backdrop of these two factors, the Navy interests are obviously to raise the efficiency of fixed and mobile sonar systems in the environment of high technogenic noise produced by civil marine activities.