Intrusion Detection

NRL researchers have developed an intrusion detection system for undersea pipelines that detect intruding objects as well as leakage effects from the pipelines.

Actively Controlled Curvature Robotic Pectoral Fin

The Naval Research Laboratory (NRL) has developed an actively controlled curvature robotic fin based on the pectoral fin of a coral reef fish, the bird wrasse (Gomphosus varius). This fin, which generates 3D vectored thrust through actuation of fin and fin rib stroke angles, has been integrated onto a man-portable, unmanned underwater vehicle called WANDA – Wrasse-inspired Agile Near-shore Deformable-fin Automaton.

The image above right demonstrates the efficacy of the NRL’s innovative algorithm to effectively de-glint imagery in a variety of applications, including shallow water. The original, uncorrected image is above left. Sun Glint Correction for Shallow Water, High Resolution, and WorldView-2 and WorldView3 Imagery

NRL has developed and tested a patent-pending algorithm and software to correct remotely sensed imagery for specular reflection, also known as sun glint. The NRL technique offers three key benefits: The first is the ability to accurately correct for glint in shallow water locations where the bottom contributes to reflection in a manner that most traditional correction methods cannot accurately handle. The second is the ability to compensate for specular reflection before or after atmospheric correction—techniques using sensor radiance spectra to estimate atmospheric variable parameters may result in incorrect or inconsistent removal of the atmospheric component of the signal in glinted areas. The final benefit, specific to imagery from the WorldView-2 and WorldView-3 sensors, is the ability to effectively correct images while taking into consideration the 0.2 second time gap between data collection for the two 4-band multi-spectral arrays.

The US Navy has developed an innovative combination of water pixels (top) and water edge pixels (middle) to create accurate water boundaries (bottom) from a wide range of imagery sources Shoreline Extraction Algorithm

NRL has developed an algorithm and software to quickly and easily extract shoreline data from remotely sensed imagery. The Navy’s innovative approach extracts water and non-water point pixels, and employs a unique interrelation between the two in order to generate highly accurate boundaries that are properly ordered and oriented for GIS applications.

Bathymetry contours exhibiting 10x reduction in original size with 1% and 10m user specified thresholds.  Original data set shown (A), GRIN processed data (B). Grid Retaining Irregular Networks (GRIN): High Fidelity Geospatial Grid Data Compression

The US Naval Research Laboratory detachment at Stennis Space Center has developed GRIN, a fast, flexible, and highly efficient means of compressing geospatial datasets by thinning points while maintaining a high degree of accuracy for the remaining data points. GRIN is a new algorithm for calculating Right Triangulated Irregular Networks (RTINs) that preserves the positional integrity of the remaining original grid points. GRIN is designed for charting, navigation, and other high-precision applications.

Coastal Ocean Prediction Software

NRL has developed an automated coastal ocean prediction software system that is capable making of high-resolution water levels and currents predictions in coastal areas. The system has been tested and validated in various geographic regions and can be configured rapidly and run on either single processor or multi-processor parallel computers.

Zero-Power Bathythermograph Sensors

The Zero Power Ballast Control (ZPBC) is a technology that relies on microbial energy harvesting developments to enable unsupervised underwater sensing with subsequent surfacing and reporting capabilities. With an ultimate goal of producing simple, small, power- efficient data harvesting nodes with varia-ble buoyancy, the device will be able to monitor ocean temperatures with a stay time ranging from weeks to months and eventually years, providing a longer term than other mechanisms such as the Expendable Bathythermograph (XBT).

Fig. I. Examples of cloud shadow detection using the CSDI technique. Left panel: HICO image acquired over Virgin Islands on December 20, 2009 (image size: 270 x 400 pixels); (a) true color image, (b) corresponding IV image, and (c) corresponding CSDI image. Right panel: HICO image acquired over Samoa on October 2, 2010 ' (image size: 260 x 260 pixels); (d) true color image, (e) corresponding IV image and (f) corresponding CSDI image. The clouds are shown in white on both CSDI and IV images, the shadows are Cloud Shadow Detection Index (CSDI)

A cloud shadow detection technique called the Cloud Shadow Detection Index (CSDI) for optical imageries acquired over water by satellite/airborne sensors. This technique does not require any angular information (viewing or solar), or any estimation of clouds vertical heights. It is entirely based on measurements in the optical channels. This approach is for homogeneous water bodies such as deep waters where shadow detection is very challenging due to the relatively small differences in the brightness values of the shadows and neighboring sunlit or some other regions.

Environmental Cell Nano/Micro Mechanical Environmental Test Cell

NRL has developed a tool to facilitate the quantification of compressive strength of soft materials, such as clays, biopolymer-clay mixtures, food items, tissues, cells and similar materials. The specific goal of this device is to facilitate compressive tests for biopolymers (i.e. natural or synthetic compounds that consist of large molecules made of many chemically bonded smaller identical molecules, e.g. starch and nylon, produced in living organisms) and sediments.

The US Navy has developed and tested BOPPERS for the repeated unattended collection and reporting of environmental data from the entire water column from depths of 100m or less. BOPPERS: Autonomous Underwater Environmental Monitoring System

NRL has developed a shallow water environmental profiler the autonomously measures physical and optical properties of the water column at periodic, user-specified intervals over an extended time period (weeks to months). Data are collected and stored on-board, and can be transmitted in near-real-time to a land station when the profiler surfaces. The patent-pending NRL system, equipped with advanced instrumentation, includes the capability to simultaneously collect measurements of physical and bio-optical properties.

River Simulation Tool

NRL has developed a river simulation tool (RST) that performs automated extraction of riverine features from imagery. The extractions include water/land edge locations, water point locations, and obstacle and hazard locations. Processing within the RST also includes processing of shoreline and bathymetry data for mesh generation as well as automated configuration of an unstructured mesh of the river using image-derived data.

Hydrographic Unmanned Semi-Submersible (HUSS)

NRL and its industry partner have developed the Hydrographic Unmanned Semi-Submersible (HUSS), customized for port, harbor, channel, and near-shore surveying. Its unique design combines the key benefits of both a small surface craft (speed, endurance, maneuverability, navigation safety, real-time communications, command and control, sensor payload, navigation accuracy) and an Unmanned Underwater Vehicle (UUV) (stability for sensors, easy launch and recovery, autonomy, energy efficiency, human safety) while yielding a threefold or better increase in productivity than either a small surface craft or a UUV.

ADCIRC Toolset

The Naval Research Laboratory (NRL) has developed the NUMCAT™ suite of powerful, easy-to-use tools to support application of the open source ADvanced CIRCulation (ADCIRC) model. ADCIRC simulates currents, water level, storm surges, temperature, and salinity in the coastal ocean including regions of shallow shelf waters, estuaries, and rivers. The NUMCAT™ tools can be modified to support other finite element based models. The NUMCAT™ toolset is currently in use by the Naval Oceanographic Office to support prediction of coastal currents and water levels.

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