USA As Represented by Secretary of the Navy

John Stastny

Bryan D Bagnall

Heidi L Buck

Sparta Cheung

Daniel F Garcia

Elan Sharghi

Vladimir Y Matveyev

Stephen L Hobbs

Erin Joslin

Corey A Lane

Jason Cole

Michael R Hughes

Eric C Hallenborg

Lynne A Tablewski

Keith Pifko

Joshua S Li

Chessa Guilas

Brian Schalcosky

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 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

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.

Method for detecting and mapping fires using features extracted from overhead imagery

Methods for processing overhead imagery of a vessel include the step of determining an initial classification and classification probability based on the vessel length and length-to-width ratio. Next, mutually exclusive deck features can be extracted from the image. For several embodiments, the extracted deck features that can be spherical tanks, hatches and containers that are stored on deck. The initial classification probability is then weighted using the results of the deck feature extraction step to yield a posterior classification probability for the ship image. If the posterior classification probability is above a predetermined value, the image is assigned a posterior classification. If the posterior probability is below the predetermined value, the vessel image is classified as unknown, and the gross tonnage of the vessel is calculated using the length and width of the vessel.

Method for classifying vessels using features extracted from overhead imagery

Methods for automatic detection of ships in overhead images of bodies of water are disclosed. The image is initially analyzed to determine if land is present, and the portions of the overhead image where land is present are masked and not processed further. The methods include the steps of chipping the unmasked portions of the overhead image into a series of tiles, discriminating and removing clouds from the tiles using two-dimensional Fourier transforms, and characterizing tile background noise from the water's surface. Different ship detection algorithms are used, according to the level of background noise detected. Detected ships are output into a format that is easily interpreted by the user. The formatted output can also include a confidence rating, or a calculation of the certainty that the detected object in an output file is actually a ship.

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San Diego, CA, United States of America

John Stastny