This PDF file contains the front matter associated with SPIE Proceedings Volume 10186 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

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We present an investigation of the optical property of orbital angular momentum (OAM) for use in the detection of objects obscured by a turbid underwater channel. In our experiment, a target is illuminated by a Gaussian beam. An optical vortex is formed by passing the object-reflected and backscattered light through a diffractive spiral phase plate at the receiver, which allows for the spatial separation of coherent and non-coherent light. This provides a method for discriminating target from environment. Initial laboratory results show that the ballistic target return can be detected 2-3 orders of magnitude below the backscatter clutter level. Furthermore, the detection of this coherent component is accomplished with the use of a complicated optical heterodyning scheme. The results suggest new optical sensing techniques for underwater imaging or LIDAR.

Optical methods to communicate or sense in the ocean environment can be effected inhomogeneities in the index of refraction called optical turbulence. Beam wander introduced by optical turbulence is of particular interest for optical means relying on the propagation of a well-defined laser beam such as free space communication and laser line scan. Here we present a comprehensive study of beam propagation simulations, lab experiments, and field measurements of laser beams propagating through varying degrees of optical turbulence. For the computational part of the investigation a true end to end simulation was performed. Starting with a CFD simulation of Rayleigh–Bénard convection the temperature fields where converted to index of refraction phase screens which then where used to simulate the propagation of a focused Gaussian laser beam via the split-step Fourier method. Lab experiments where conducted using the same parameters as in the simulation using a good quality TEM00 beam and a CCD camera to record data. For the field experiments a Telescoping Ridged Underwater Sensor Structure (TRUSS) was equipped with a transmitter and a receiver capable of analyzing a multitude of laser beams simultaneously. The TRUSS was deployed in the Bahamas to record beam wander under weak optical turbulence conditions above and stronger optical turbulence conditions inside the thermocline. The data from the experimental and lab experiments are compared and the strength of the optical turbulence in terms of the structure parameter Cn2 are extracted. We also extract Cn2 from the TRUSS experiments and in doing so provide, for the first time, a quantitative estimate for the strength of optical turbulence in the ocean.

Optical propagation through the ocean encounters significant absorption and scattering; the impact is exponential signal attenuation and temporal broadening, limiting the maximum link range and the achievable data rate, respectively. MIT Lincoln Laboratory is developing narrow-beam lasercom for the undersea environment, where a collimated transmit beam is precisely pointed to the receive terminal. This approach directly contrasts with the more commonly demonstrated approach, where the transmit light is sent over a wide angle, avoiding precise pointing requirements but reducing the achievable range and data rate. Two advantages of narrow-beam lasercom are the maximization of light collected at the receiver and the ability to mitigate the impact of background light by spatial filtering. Precision pointing will be accomplished by bi-directional transmission and tracking loops on each terminal, a methodology used to great effect in atmospheric and space lasercom systems. By solving the pointing and tracking problem, we can extend the link range and increase the data throughput.

This effort develops and tests algorithms and a user-portable optical system designed to autonomously optimize the laser communication wavelength in open and coastal oceans. In situ optical meteorology and oceanography (METOC) data gathered and analyzed as part of the auto-selection process can be stored and forwarded. The system performs closedloop optimization of three visible-band lasers within one minute by probing the water column via passive retroreflector and polarization optics, selecting the ideal wavelength, and enabling high-speed communication. Backscattered and stray light is selectively blocked by employing polarizers and wave plates, thus increasing the signal-to-noise ratio. As an advancement in instrumentation, we present autonomy software and portable hardware, and demonstrate this new system in two environments: ocean bay seawater and outdoor test pool freshwater. The next generation design is also presented. Once fully miniaturized, the optical payload and software will be ready for deployment on manned and unmanned platforms such as buoys and vehicles. Gathering timely and accurate ocean sensing data in situ will dramatically increase the knowledge base and capabilities for environmental sensing, defense, and industrial applications. Furthermore, communicating on the optimal channel increases transfer rates, propagation range, and mission length, all while reducing power consumption in undersea platforms.

Optical communication/detection systems have potential to get around some limitations of current acoustic communications and detection systems especially increased fleet and port security in noisy littoral waters. Identification of environmental effects on underwater optical transmission is the key to the success of using optics for underwater communication and detection. This paper is to answer the question “What are the transfer and correlation functions that relate measurements of hydrographic to optical parameters?” Hydrographic and optical data have been collected from the Naval Oceanographic Office survey ships with the High Intake Defined Excitation (HIDEX) photometer and sea gliders with optical back scattering sensor in various Navy interested areas such as the Arabian Gulf, Gulf of Oman, east Asian marginal seas, and Adriatic Sea. The data include temperature, salinity, bioluminescence, chlorophyll-a fluorescence, transmissivity at two different wavelengths (T_Red at 670 nm, T_Blue at 490 nm), and back scattering coefficient (b_Red at 700 nm, b_Blue at 470 nm). Transfer and correlation functions between the hydrographic and optical parameters are obtained. Bioluminescence and fluorescence maxima, transmissivity minimum with their corresponding depths, red and blue laser beam peak attenuation coefficients are identified from the optical profiles. Evident correlations are found between the ocean mixed layer depth and the blue and red laser beam peak attenuation coefficients, bioluminescence and fluorescence maxima in the Adriatic Sea, Arabian Gulf, Gulf of Oman, and Philippine Sea. Based on the observational data, an effective algorithm is recommended for solving the radiative transfer equation (RTE) for predicting underwater laser radiance.

Traditional artificial reef structures are designed with uniform cellular architectures and topologies and do not mimic natural reef forms. Strings and ropes are a proven, common fisheries and mariculture construction element throughout the world and using them as artificial reef scaffolding can enable a diversity of ocean sensing, communications systems including the goal of sentinel reefs. The architecture and packaging of electronics is key to enabling such structures and systems. The distributed sensor reef concept leads toward a demonstrable science-engineering-informed framework for 3D smart habitat designs critical to stock fish development and coastal monitoring and protection. These ‘nature-inspired’ reef infrastructures, can enable novel instrumented ‘reef observatories’ capable of collecting real-time ecosystem data. Embedding lighting and electronic elements into artificial reef systems are the first systems conceptualized. This approach of bringing spatial light to the underwater world for optical sensing, communication and even a new breed of underwater robotic vehicle is an interdisciplinary research activity which integrates principles of electronic packaging, and ocean technology with art/design.

In this paper we introduce a software tool for image based computer simulation of an underwater gated viewing system. This development is helpful as a tool for the discussion of a possible engagement of a gated viewing camera for underwater imagery. We show the modular structure of implemented input parameter sets for camera, laser and environment description and application examples of the software tool. The whole simulation includes the scene illumination through a laser pulse with its energy pulse form and length as well as the propagation of the light through the open water taking into account complex optical properties of the environment. The scene is modeled as a geometric shape with diverse reflective areas and optical surface properties submerged in the open water. The software is based on a camera model including image degradation due to diffraction, lens transmission, detector efficiency and image enhancement by digital signal processing. We will show simulation results on some example configurations. Finally we will discuss the limits of our method and give an outlook to future development.

Field experiments with the goal of characterizing aquatic particle properties, including size distributions and orientations in their natural environment, were conducted using a submersible holographic imaging system (HOLOCAM). Digital holography is a non-intrusive technique that allows particle fields to be mapped within a 3-D sampling volume at high resolution. The HOLOCAM was deployed at East Sound, a fjord in the US Pacific Northwest, and Lake Erie over three separate deployments from 2013 to 2015. A database of more than a million particles in the 100-10000 µm size range of varying shape and orientation was created after processing < 50,000 holograms. Furthermore, simultaneous, co-located acoustic Doppler velocimeter measurements of small-scale shear and turbulence structure were used to study the effects of the ambient flow field on particle orientation. Several interesting features presented themselves, with a Microcystis bloom dominating the surface layer of Lake Erie, while ‘thin layers’ of high particle concentrations dominated by colonial diatoms were seen in East Sound. Particle size distribution (PSD) slopes in the 50-250 µm size range were ~1.7-1.9, while for particles < 250 µm, the slopes were significantly higher. Clear evidence of ubiquitous particle alignment to the horizontal flow field in regions of low shear and turbulent dissipation was seen. This result, obtained under flow conditions representative of coastal and open oceans, can have significant consequences to ocean optics as random particle orientation is inherently assumed in theory and models. Preferential alignment can increase/decrease optical properties such as backscattering and attenuation relative to random distributions.

This work presents a new statistical signal processing approach to reduce the effects of forward scatter on range accuracy for an underwater modulated pulse lidar. Lidar sensors offer the potential for high-resolution, high-accuracy ranging in the underwater environment. For the modulated pulse lidar rangefinder, performance is limited in turbid waters primarily due to forward scatter, which causes decreased range resolution and accuracy. This work presents simulated and experimental results demonstrating the ability of statistical signal processing to reduce range error for systems operating in these turbid conditions. Experimental results demonstrated 60% reduction in range error compared to a baseline approach.

Blue-green laser systems are being developed for optical imaging and ranging in the underwater environment. The imaging application requires high range resolution to distinguish between multiple targets in the scene or between multiple target features, while the ranging application benefits from measurements with high range accuracy. The group at the Naval Air Warfare Center Aircraft Division (NAWCAD) in Patuxent River, MD has been investigating the merging of wideband radar modulation schemes with a pulsed laser system for underwater imaging and ranging applications. For the imaging application, the narrow peak produced by pulse compression at the receiver offers enhanced range resolution relative to traditional short pulse approaches. For ranging, the selection of modulation frequency bands approaching 1GHz provides backscatter and forward scatter suppression and enhanced range accuracy. Both passband and baseband digital processing have been applied to data collected in laboratory water tank experiments. The results have shown that the choice of processing scheme has a significant impact on optimizing the performance of modulated pulse laser systems for either imaging or ranging applications. These different processing schemes will be discussed, and results showing the effect of the processing schemes for imaging and ranging will be presented.

Adaptive filtering and channel estimation techniques are applied to laser based ranging systems that utilize wide-band intensity modulation to measure the range and reflectivity of underwater objects. The proposed method aims to iteratively learn the frequency dependent characteristics of the underwater environment using a frequency domain adaptive filter, which results in an estimate for the channels optical impulse response. This work presents the application of the frequency domain adaptive filter to simulated and experimental data, and shows it is possible to iteratively learn the underwater optical channel impulse response while using Hybrid Lidar/Radar techniques.

Compressive Line Sensing (CLS) imaging system is a compressive sensing (CS) based imaging system with the goal of developing a compact and resource efficient imaging system for the degraded visual environment. In the CLS system, each line segment is sensed independently; however, the correlation among the adjacent lines (sources) is exploited via the joint sparsity in the distributed compressing sensing model during signal reconstruction. Several different CLS prototypes have been developed. This paper discusses the development of a pulsed CLS system. Initial experimental results using this system in a turbid water environment are presented.

Improved understanding of coastal hydrodynamics and morphology will lead to more effective mitigation measures that reduce fatalities and property damage caused by natural disasters such as hurricanes. We investigated sediment transport under oscillatory flow over flat and rippled beds with phase-separated stereoscopic Particle Image Velocimetry (PIV). Standard PIV techniques severely limit measurements at the fluid-sediment interface and do not allow for the observation of separate phases in multi-phase flow (e.g. sand grains in water). We have implemented phase-separated Particle Image Velocimetry by adding fluorescent tracer particles to the fluid in order to observe fluid flow and sediment transport simultaneously. While sand grains scatter 532 nm wavelength laser light, the fluorescent particles absorb 532 nm laser light and re-emit light at a wavelength of 584 nm. Optical long-pass filters with a cut-on wavelength of 550 nm were installed on two cameras configured to perform stereoscopic PIV to capture only the light emitted by the fluorescent tracer particles. A third high-speed camera was used to capture the light scattered by the sand grains allowing for sediment particle tracking via particle tracking velocimetry (PTV). Together, these overlapping, simultaneously recorded images provided sediment particle and fluid velocities at high temporal and spatial resolution (100 Hz sampling with 0.8 mm vector spacing for the 2D-3C fluid velocity field). Measurements were made under a wide range of oscillatory flows over flat and rippled sand beds. The set of observations allow for the investigation of the relative importance of pressure gradients and shear stresses on sediment transport.

Particle image velocimetry (PIV) is a well-established tool to collect high-resolution velocity and turbulence data in the laboratory. PIV measurements are based on using a laser sheet to illuminate a flow seeded with small particles and taking quick successive images or image pairs of the illuminated particle field with a CCD or CMOS camera. The movement of the particles between images can be used to infer flow field velocities over an image area. During experiments at the Simulated Turbulence and Turbidity Environment (SiTTE) laboratory tank, we observed a marked influence of optical turbulence, i.e. strong temperature gradients leading to changes in the index of refraction, on particle imaging in PIV. The particles look blurred and have a “shooting star” appearance. PIV is routinely used in flows with very high temperature gradients, such as nuclear reactor cooling rods, but the optical path length is typically very short (on the order of cm), and no such effect is generally considered for measurements in liquids. We investigated the effect of optical turbulence on PIV imaging for various optical path lengths (0.5m to 2m) and turbulence strengths. Velocities from the PIV measurements were calculated using the algorithms provided within Dantec’s Dynamic Studio and compared to velocities from concurrent velocity point measurements with a Laser Doppler Velocimetry system. The results indicate that optical turbulence can affect PIV measurements in liquids, and that depending on the strength of the optical turbulence and path length, care needs to be taken to mediate this effect using appropriate post-processing techniques when inferring velocities from PIV data.

In this research, we focus on vessel detection using the satellite imagery of day/night band (DNB) on Suomi NPP in order to monitor the change of vessel activity on the region of South China Sea. In this paper, we consider the relation between the temporal change of vessel activities and the events on maritime environment based on the vessel traffic density estimation using DNB. DNB is a moderate resolution (350-700m) satellite imagery but can detect the fishing light of fishery boats in night time for every day. The advantage of DNB is the continuous monitoring on wide area compared to another vessel detection and locating system. However, DNB gave strong influence of cloud and lunar refection. Therefore, we additionally used Brightness Temperature at 3.7μm(BT3.7) for cloud information. In our previous research, we construct an empirical vessel detection model that based on the DNB contrast and the estimation of cloud condition using BT3.7. Moreover, we proposed a vessel traffic density estimation method based on empirical model. In this paper, we construct the time temporal density estimation map on South China Sea and East China Sea in order to extract the knowledge from vessel activities change.

Preliminary results of previous work had shown a Neural Network (NN) technique developed by us as effective in detecting Karenia brevis Harmful Algal Blooms (KB HABs) plaguing West Florida Shelf (WFS) from VIIRS satellite observations. We extend comparisons of NN retrievals against a data set of near simultaneous in-situ measurements in the WFS spanning the 2012-2016 period for which there was available VIIRS data. Specifically we looked for match ups where the overlap time windows between satellite observations and in-situ measurements were 15 minutes and 100 minutes. We then compare the accuracy of the NN retrievals against the in-situ measurements, with the accuracies achieved with similar of retrievals using OC3, GIOP, QAA and RGCI algorithms. The NN technique exhibited the best retrieval accuracy statistics. The retrievals for all the algorithms very clearly showed the impact of temporal variations of the KB HABS on retrieval accuracies. Thus, retrievals using a 15 minutes overlap window between satellite observations and in-situ measurements yielded much higher accuracies than those with the 100 minutes overlap window. Temporal variabilities were also studied, using consecutive overlapping VIIRS images. These variabilities, as well as the patchiness of KB blooms were also confirmed by a set of in-situ measurements near Sarasota, FL.

Analysis of bulk-skin sea surface temperature (SST) difference form the west and east coasts of United States is presented using the data collected from three field experiments. These experiments were conducted at offshore Duck, North Carolina and in the Monterey Bay of the California coastal region. Bulk SST measurements were made using conventional thermistors from a depth of one meter below the sea level. Infrared radiometers were used to measure the surface skin SST. Depending on measurement depth and prevailing conditions, the bulk SST can differ from skin SST by few tenths of a degree to O(1°C). Difference between bulk and skin SST arise from cools skin and warm layer effects. Bulk-skin SST difference (ΔSST) estimated from east coast observations varied from -0.46°C to 1.24°C. Here, the bulk SST was higher than skin SST most of the time during the observations. This indicates cool skin effect was the dominant factor determining the ΔSST in the east coast. For wind speeds less than 4 m s^-1, we also noticed an increase in ΔSST. Additionally, for low winds (<4 m s^-1) ΔSST also varied diurnally with the occurrence of generally higher ΔSST in the nighttime in comparison with daytime. Moreover, increase in downwelling longwave radiation reduced the bulk-skin SST difference. ΔSST calculated from the observation in the Monterey bay varied between ~2.3° and ~-2.3°C. This was higher than the variability ΔSST observed at the east coast. Moreover, ΔSST variability observed at west coast was independent of wind speed.

Polarimetric characteristics of light from ocean water in combination with standard remote sensing reflectance provide important information about water constituents; they are useful in retrieval of additional water parameters like attenuation-to-absorption ratio and attenuation coefficients and/or establishing additional constraints for retrieval algorithms. The Stokes vectors of light above and below the water surface, which fully represent polarimetric characteristics of water leaving radiance, strongly depend on the particle size distribution and related Mueller matrices of water particulates. In this work we investigate the effect of various hydrosol mixtures of chlorophyllous particles on the polarized light field. The Stokes vectors of scattered light and the degree of polarization (DOP) are generated as outputs of vector radiative transfer simulations for various water compositions. Mie theory as well as T-matrix approaches are used for the generation of scattering matrices. The impact of their variability on the Stokes vectors of polarized light is analyzed.

The dynamic bio-optical and physical ocean properties within the Gulf of Mexico (GoM) have been identified by the Ocean Weather Laboratory. Ocean properties from VIIRS satellite (Chlorophyll and Bio-Optics and SST) and ocean-circulation models (currents, SST and salinity) were used to identify regions of dynamic changing properties. The degree of environmental change is defined by the dynamic anomaly of bio-optical and physical environmental properties (DAP). A Mississippi River plume event (Aug 2015) that extended to Key West was used to demonstrate the anomaly products. Locations where normal and abnormal ocean properties occur determine ecological and physical hotspots in the GoM, which can be used for adaptive sampling of ocean processes. Methods are described to characterize the weekly abnormal environmental properties using differences with a previous baseline 8 week mean with a 2 week lag. The intensity of anomaly is quantified using levels of standard deviation of the baseline and can be used to recognize ocean events and provide decision support for adaptive sampling. The similarities of the locations of different environmental property anomalies suggest interaction between the bio-optical and physical properties. A coral bleaching event at the Flower Garden Banks Marine Protected Area is represented by the salinity anomaly. Results identify ocean regions for sampling to reduce data gaps and improve monitoring of bio-optical and physical properties.

Lidar remote sensing based on visible wavelength is one of the only way to penetrate the water surface and to obtain range resolved information of the ocean surface mixed layer at the synoptic scale. Accurate measurement of the mixed layer properties is important for ocean weather forecast and to assist the optimal deployment of military assets. Turbulence within the mixed layer also plays an important role in climate variability as it also influences ocean heat storage and algae photosynthesis (Sverdrup 1953, Behrenfeld 2010). As of today, mixed layer depth changes are represented in the models through various parameterizations constrained mostly by surface properties like wind speed, surface salinity and sea surface temperature. However, cooling by wind and rain can create strong gradients (0.5C) of temperature between the submillimeter surface layer and the subsurface layer (Soloviev and Lukas, 1997) which will manifest itself as a low temperature bias in the observations. Temperature and salinity profiles are typically used to characterize the mixed layer variability (de Boyer Montégut et al. 2004) and are both key components of turbulence characterization (Hou 2009). Recently, several research groups have been investigating ocean temperature profiling with laser remote sensing based either on Brillouin (Fry 2012, Rudolf and Walther 2014) or Raman scattering (Artlett and Pask 2015, Lednev et al. 2016). It is the continuity of promising research that started decades ago (Leonard et al. 1979, Guagliardo and Dufilho 1980, Hirschberg et al. 1984) and can benefit from the current state of laser and detector technology. One aspect of this research that has not been overlooked (Artlett and Pask 2012) but has yet to be revisited is the impact of temperature on vibrational Raman polarization (Chang and Young, 1972). The TURBulence Ocean Lidar is an experimental system, aimed at characterizing underwater turbulence by examining various Stokes parameters. Its multispectral capability in both emission (based on an optical parametric oscillator) and detection (optical filters) provide flexibility to measure the polarization signature of both elastic and inelastic scattering. We will present the characteristics of TURBOL and several results from our laboratory and field experiments with an emphasis on temperature profiling capabilities based on vibrational Raman polarization. We will also present other directions of research related to this activity.

Interdisciplinary coastal observations over a two-week period in the northern Gulf of Mexico reveal a complex and dynamic bottom boundary layer (BBL) that is characterized by both biological and suspended sediment (biogeo-) optical signals. Much of the BBL optical variance is concealed from remote sensing by the opacity of the nearly omnipresent surface river plume, however, the BBL physical dynamics and resulting optical excitation are indeed responding to surface wind stress forcing and surface gravity wave-induced turbulence. Here we present a series of numerical modeling efforts and approaches aimed towards resolving and simulating these observed biogeo-physical and –optical processes. First, we examine results from the Tactical Ocean Data System (TODS), which combines daily satellite imagery with numerical circulation model results to render a three-dimensional estimate of the optical field and then execute a reduced-order complexity advection-diffusionreaction model to render hourly forecasts. Whereas the TODS system has the advantage of effectively assimilating both glider data and satellite images, the 3D generation algorithms still have difficulty in the northern Gulf’s complex 3-layered system (surface plume, geostrophic interior, BBL). Second, we present results from the Coupled Ocean-Atmosphere Prediction (COAMPS) system that has been modified to include interactive surface-gravity wave simulations. Results from this complex numerical modeling system suggest that Stokes drift current (SDC) has a potentially major role in determining the physical and kinematic characteristics of the BBL, and will substantially impact model-based estimates of sediment resuspension and transport.

During 2014 exceptionally warm water temperatures developed across a wide area off the California coast and within San Francisco Bay (SFB) and persisted through the middle of 2016. Observations and numerical model output are used to document this warming and its origins. The coastal warming was mostly confined to the upper 100 meters of the ocean and was manifested strongly in the two leading modes of upper ocean (0-100 m) temperature variability in the extra-tropical eastern Pacific. Observations in the suggest that the coastal warming in 2014 propagated into nearshore regions from the west and later indicate a warming influence that propagates from south to north into the region associated with the 2015-16 El Niño event. An analysis of the upper ocean (0-100 m) heat budget in a Regional Ocean Modeling System hindcast simulation confirmed this scenario. The results from a set of sensitivity runs with the model in which the lateral boundary conditions varied supports the conclusions drawn from the heat budget analysis. Concerning the warming in the SFB, an examination of the observations and the heat budget in an unstructured-grid numerical model simulation suggests that the warming during the second half of 2014 and early 2016 originates in the adjacent California coastal ocean and propagates through the Golden Gate into the Bay. The finding that the coastal and Bay warming are due to the relatively slow propagation of signals from remote sources raise the possibility that such warming events may be predictable several months in advance.

This paper is to answer the question “How can inter- and intra-annual variability in the ocean be leveraged by the submarine Force?” through quantifying inter- and intra-annual variability in (T, S) fields and in turn underwater acoustic characteristics such as transmission loss, signal excess, and range of detection. The Navy’s Generalized Digital Environmental Model (GDEM) is the climatological monthly mean data and represents mean annual variability. An optimal spectral decomposition method is used to produce a synoptic monthly gridded (SMG) (T, S) dataset for the world oceans with 1° ×1° horizontal resolution, 28 vertical levels (surface to 3,000 m depth), monthly time increment from January 1945 to December 2014 now available at the NOAA/NCEI website: http://data.nodc.noaa.gov/cgibin/iso?id=gov.noaa.nodc:0140938. The sound velocity decreases from 1945 to 1975 and increases afterwards due to global climate change. Effect of the inter- and intra-annual (T, S) variability on acoustic propagation in the Yellow Sea is investigated using a well-developed acoustic model (Bellhop) in frequencies from 3.5 kHz to 5 kHz with sound velocity profile (SVP) calculated from GDEM and SMG datasets, various bottom types (silty clay, fine sand, gravelly mud, sandy mud, and cobble or gravel) from the NAVOCEANO‘s High Frequency Environmental Algorithms (HFEVA), source and receiver depths. Acoustic propagation ranges are extended drastically due to the inter-annual variability in comparison with the climatological SVP (from GDEM). Submarines’ vulnerability of detection as its depth varies and avoidance of short acoustic range due to inter-annual variability are also discussed.

The linear ordered statistic (LOS) is a parameterized ordered statistic (OS) that is a weighted average of a rank-ordered sample. LOS operators are useful generalizations of aggregation as they can represent any linear aggregation, from minimum to maximum, including conventional aggregations, such as mean and median. In the fuzzy logic field, these aggregations are called ordered weighted averages (OWAs). Here, we present a method for learning LOS operators from training data, viz., data for which you know the output of the desired LOS. We then extend the learning process with regularization, such that a lower complexity or sparse LOS can be learned. Hence, we discuss what 'lower complexity' means in this context and how to represent that in the optimization procedure. Finally, we apply our learning methods to the well-known constant-false-alarm-rate (CFAR) detection problem, specifically for the case of background levels modeled by long-tailed distributions, such as the K-distribution. These backgrounds arise in several pertinent imaging problems, including the modeling of clutter in synthetic aperture radar and sonar (SAR and SAS) and in wireless communications.

Currently, wireless hydroacoustic modems are actively being developed, which are used to provide efficient data transmission in the hydroacoustic channel. Such kind of developments are relevant for today, as they are used in various fields of science and fields of activity. An example is the connection with underwater vehicles for scientific, research, search and rescue purposes. Development of this kind of communication systems (modems) is a difficult task, as signal propagation is affected by various factors. As a result, the transfer characteristic changes with time, thereby imposing restrictions on the acoustic communication channel. In this regard, the researchers began the task of further study sonar environment and get a detailed mathematical description of the underwater channel. For this, a huge number of field tests were conducted, aimed at studying the underwater acoustic environment. However, the results of the research are always limited by the conditions in which the test took place. Therefore, it is not always possible to apply these results to the required conditions. All of the above features do not allow you to create some kind of a commonly accepted model for the acoustic channel, as studies based on experiments, collected in localized environments without generalizations. This paper presents, the three-dimensional model of the sonar channel for MIMO systems in the coastal zone, based on the acoustic signal propagation characteristics in the presence of multiple paths, the influence of the Doppler effect (as a result of mobile and / or base station traffic), in terms of signal attenuation, receiver characteristics influence and Transmitting antenna, etc.