Submarine navigation systems currently use small-aperture magnetron X-band radars due to their ability to image longer distances while occupying a much smaller footprint. Though magnetrons are powerful and space saving, they inherently transmit incoherent radiation, making high resolution imaging challenging.
FTL’s SharpScan is an improved-angular-resolution magnetron-based radar that is coherent-on-receive through the implementation of very high speed data acquisition and new Field Programmable Gate Array (FPGA) based beam-sharpening. SharpScan’s coherent radar processing is an enabling technology that provides higher Signal to Noise Ratio (SNR), reduces target uncertainty, and allows for advanced DSP techniques like beam sharpening and Moving Target Indication (MTI) to reduce the influence of static clutter and provide more information on each target compared to incoherent returns. SharpScan achieves more than twice the image sharpening capabilities over what Commercial Off The Shelf (COTS) magnetron marine radars on the market today can achieve, while still fitting in the small footprint required on submarines and maintaining the superior output power and range associated with magnetron systems.
“DroneDraft” from FTL Labs Corporation is a fully autonomous, man-portable measurement, data collection, analysis, and display system for draft measurements during vessel evaluations, either prior to delivery or as part of in-service availabilities.
DroneDraft performs autonomous vessel draft evaluations that are required to ensure vessel stability and safety, and test performance can critically impact vessel delivery schedules. It replaces the existing test method, which requires a manned small boat to collect draft readings at four locations using a draft tube method that is primitive, subjective, inconsistent, non-standardized, and dangerous.
DroneDraft determines the draft of a vessel while reducing set-up time, minimizing equipment needed, streamlining the process, reducing costs, mitigating schedule risks, and eliminating safety hazards to personnel. It will determine a vessel’s draft to 1/16” in various weather conditions and with various hull forms to support on-time delivery of ships and submarines. The system can operate in several feet of chop and wind, and can determine draft on various hull forms including flared or tumble homed hulls and draft marks. Additionally, DroneDraft provides data analytics to provide a statistical evaluation and digital record, and will integrate easily into standard operating procedures and standards to enable fleet-wide use
DroneDraft is a shippable UAV draft measurement system (a) that enables rapid ship surveying (b), and draft-marking imaging (c). FTL has demonstrated autonomous flight and data acquisition (d) along with a cascaded neural network processing pipeline capable of extracting draft markings from effects due to hull curvature, perspective, weather, and lighting to reach a precision of 1/8” in field testing (e).
FTL’s SpearFish system leverages JPL’s CARACaS autonomy architecture in a new enabling technology for Patrol boat sensing, perception, and Command-and-Control (C2). SpearFish applies advanced high-bandwidth sensor fusion to enable unmanned patrol boats that will reduce risks and enable new operational capabilities within the Maritime Expeditionary Security Force (MESF). SpearFish includes sensor, perception, and Command-and-Control modules to enable MESF-specific autonomous behaviors. It indicates all high-level behaviors being executed and allows dynamic tasking/re-tasking from human operators. Additionally, SpearFish conforms to a Size, Weight, Power and Cost (SWaP-C) appropriate for current 40 PB platforms and leverages available COTS technologies to enable rapid development to on-water testing of system performance.
SpearFish requires little or no additional external sensor hardware beyond what is already in the 40 PB specification, plus one half-rack SpearFish computer/electronics module (1U ½ rack). SpearFish electronics enable very high speed (kHz) tracking and intercept behaviors with no ship modifications, while FTL’s neural-network systems enable situational awareness and threat recognition.
FTL’s TYFUN ocean and vessel simulation system can rapidly implement and test autonomy behaviors to ensure that each behavior has benefited from thousands of trial runs prior to ever being tested on the water.
Spearfish uses the existing sensors with additional fixed cameras to provide sensing to a swarm of patrol boats (A) to create a real-time sensor fusion Local World Model (b). Applying machine learning algorithms, threats are identified (C) and reaction behaviors (D) are enabled in a high-speed Spearfish autonomy framework (E) or existing CARACaS autonomy framework (f).
Unmanned Surface Vessels (USV’s) are anticipated to play an important role in future Naval systems. These vary from very small systems deployed by hand from boats, to very large vessels, as large as a manned battleship, but operated entirely remotely.
FTL has ongoing work with the Navy to develop state-of-the-art shipboard sensor systems including sea-surface radar, inertial measurement with accelerometers and gyroscopes, and night-vision thermal cameras, to provide situational awareness to the navigation systems of the USV. In addition, this data informs a comprehensive model of the ocean surface and how approaching waves will adversely affect the stability and safety of the USV. The resulting “BotSwain” system can take control of the USV to ensure vessel safety and uses cutting-edge artificial intelligence and ship simulation.
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FTL’s BotSwain work draws upon years of experience modeling and visualizing the ocean surface based on meteorological, geographic, and bathymetric inputs. In particular, FTL personnel worked with the Office of Naval Research (ONR) to develop a comprehensive near-shore wave modeling software tool called “Simulated Wave Visualizer” or “SWAV”. This software used ocean wave-modeling techniques developed for computer generated special effects in Hollywood to provide a realistic experience of offshore waves for training operators of amphibious vessels and to provide situational awareness for beach operations. This has involved understanding meteorological and bathymetric drivers of breaking waves, including wave directional wave spectra, and detailed, dynamic 3D models of overspilling and tubular breaking waves.
FTL has extensive experience developing payload systems for Unmanned Underwater Vehicles (UUVs) including extensive fluid modeling of the flow and mixed-phase environment surrounding a moving submarine. This has included unique calculations, models, and experimental testing of large bubble plumes in pipes, pools, and open ocean. In particular, FTL has investigated the existence and use of pressure effects from bubble plumes and moving vessels detected by custom undersea pressure sensor arrays, and verified through computational fluid dynamics calculations.
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