USA As Represented by Secretary of the Navy

Bryan D Bagnall

John Stastny

Heidi L Buck

Sparta Cheung

Elan Sharghi

Shibin Parameswaran

Vladimir Y Matveyev

Corey A Lane

Daniel F Garcia

Joshua Harguess

Eric C Hallenborg

Michael R Hughes

Martin Thomas Jaszewski

Joshua S Li

Lynne A Tablewski

Gracie Bay Young

Bo Fitzsimmons

Keith Pifko

A communication terminal for addressed messaging within an Automated Identification System (AIS) arrangement includes a user interface and an Aid to Navigation (AtoN) transponder. The user interface facilitates the addressed messaging, which includes one or more of: chat messaging addressed between the communication terminal and a participant terminal of the AIS arrangement, automatic position messaging addressed from the communication terminal to a monitoring terminal of the AIS arrangement, or situational report messaging addressed from the communication terminal to a situational awareness terminal of the AIS arrangement. The AtoN transponder of the communication terminal of the AIS arrangement is coupled to the user interface for transmitting and receiving that achieves the addressed messaging. For the situational report messaging, the situational awareness terminal reformats and exchanges the addressed messaging with a web-based situational awareness tool via the internet.

Communication terminal for addressed messaging within an automated identification system arrangement using aid to navigation transponder

An Automatic Identification System (AIS) transponder and method for transmitting vessel AIS data can include an onboard processor and database, a VHF AIS transceiver and cellular modem connected to the processor, and a navigation sub-system for providing position inputs to the processor. The processor can include written instructions for transmitting only single sentence AIS messages when the transponder is within Rof a satellite but outside range Rof a terrestrial AIS base station, and switching to the base station when the vessel is within Rbut outside of cellular modem range, R. While transmitting to the AIS satellite or AIS base station, portions of the vessel AIS are recorded to the database as historical data. Once within R, the transponder can switch to transmission via cellular modem to an AIS architecture server. Historical data can also be downloaded to complete and update the vessel AIS data profile within AIS.

Systems and methods for transmitting ship positions and tracks over multiple communications channels

A system comprising a radar subsystem including a radar transmitter and a radar receiver, and an encoder subsystem including a computer connected to a transmitter and two antennas. The computer is configured to encode and transmit a custom payload AIS Type 8 message. A second computer connected to a receiver and antenna receives the message. The custom payload AIS Type 8 message contains target longitude, latitude fields, range, and bearing fields. A method for transmitting and receiving the radar track of a target ship including: receiving the radar signal at the own ship; encoding the target ship longitude, latitude, speed, and course into a custom payload AIS Type 8 message; transmitting the custom message to a receiver ship; decoding and displaying the target ship longitude, latitude, course, and speed at the receiver ship.

System and method for transmitting and receiving radar data using the automatic identification system

A method for displaying off-screen target indicators in motion video comprising the steps of receiving motion video containing a series of individual video frames, selecting a target object within a selected video frame by choosing selected target object pixel space coordinates, and determining whether the selected target object pixel space coordinates are within the selected video frame. Upon determining that the selected target object pixel space coordinates are within the selected video frame, the method updates a dynamical system model with the target object geographical coordinates, longitudinal target object speed, and latitudinal target object speed. Upon determining that the selected target object pixel space coordinates are not within the selected video frame, the method calculates estimated target object geographical coordinates at time t using the dynamical system model. The method then calculates final values in the video field of view at which to draw a target indicator.

Method for displaying off-screen target indicators in motion video

Methods for detecting a horizon in an image with a plurality of pixels can include the step of blurring the image with a noise filter, then dividing the image into an M&#xd7;N matrix of sub-blocks S. For each sub-block S, horizon features can be coarse-extracted by defining an r-dimensional vector having P feature values for each sub-block S and clustering each r-dimensional vectors into two clusters using a k-means statistical analysis. The corresponding sub-blocks S corresponding to the two clusters can be masked with a binary mask. The methods can further include the step of fine-extracting the horizon features at a pixel level for each sub-block Sand sub-block Swhen the binary mask changes value from sub-block Sto said sub-block S, for i=1 to M and j=1 to N.

Systems and methods for real-time horizon detection in images

A method and system are provided for processing maritime video data to improve processing time and reduce the risk of false detection. Video data input may be received from satellites, aircrafts, UAVs and other aerial vehicles. The method and system create annotated video output files indicating the location of tracked anomalies. The method and system perform an anomaly detection function on each data frame within the video input, identify anomalous regions within each data frame, and identify clusters. The method and system then perform an algorithm to discard clusters which do not meet threshold criteria to reduce the risk of false detection, as well as employ a horizon detection algorithm to eliminate superfluous image data unrelated to tracking maritime targets.

System for tracking maritime domain targets from full motion video

Systems and methods for automatic detection of disaster relief assets from a satellite image can include a satellite and a processor, which can contain non-transitory written directions that perform a method, which includes the step of defining spectra of interest (SOI). A reference spectral profile that is based on the SOI is built. The reference spectral profile can extend into the near infrared range to eliminate false positive indications. A satellite image of the spatial region of interest (ROI) is taken. For each pixel in the ROI, test spectra of the spatial region can be extracted and compared to the reference spectral profile using a spectral angle mapper (SAM) tool. When the comparison meets predetermined parameters, that pixel of the ROI can be deemed to be indicative of a disaster relief asset, and the geo-reference data for that pixel can be transmitted to a remote user.

Automatic asset detection for disaster relief using satellite imagery

A method involves adapting a vessel detection algorithm based upon received synthetic aperture radar (SAR) image data and associated metadata, detecting one or more vessels within an image tile of the SAR image data by iteratively applying the adapted vessel detection algorithm to successive portions of the image tile, discarding a detected vessel if a false alarm is determined, extracting one or more features from the detected vessels that are not discarded, and generating one or more output products based upon the extracted features.

Adaptive automated synthetic aperture radar vessel detection method with false alarm mitigation

A method for automatically detecting and mapping fires based on information extracted from commercial overhead EO/IR imagery, creating geo-referenced files which can be opened in most common geographic information system (GIS) software packages. The method creates a shapefile (*.shp & *.shx) and a Google Earth file (*.kmz) which contain the outlines of the areas from the image being processed with active fire in them, which types of files are typically very small compared to the size of the image file being processed. The method utilizes algorithms designed to process information contained in multi-spectral electro-optical imagery to classify pixels as 'fire' or 'non-fire'. The method also has the ability to identify the approximate length, width, and area of the fires detected.

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San Diego, CA, United States of America

Bryan D Bagnall