USA As Represented by Secretary of the Navy

US Government As Represented by the Secretary of the Army

Brian S Bourgeois

Andrew B Martinez

Marlin L Gendron

Marvin W Roe

John R Dubberley

David B Marks

Jeffrey A Russell

Richard R Bedckman

Peter J Alleman

Lewis F Jones, Iii

Jami J Cheramie

John M Gravley

Samantha J Zambo

Richard R Beckman

Michael M Harris

Systems and methods are provided for compression of 3 dimensional (3D) geophysical (e.g., air temp, water temp, wind, current, humidity, salinity, etc.) datasets that contain regions of NaNs (IEEE standard representation for Not a Number) that represent land, i.e. geographic positions that do not have valid data. Embodiments of the present disclosure allow constraint of the error magnitude by a user specified threshold, where compression and error are inherent tradeoffs.

Grid retaining irregular network in 3D

System and method for generating vehicle position fixes for an underwater vehicle based on images of a target object on the seafloor. The position of the target object is estimated based on a selected pixel on the target. For each image of the target, there is a different selected pixel, and a different uncertainty associated with the target location based on the selected pixel. Vehicle position fixes for the underwater vehicle are computed based on an analysis of the selected pixels for each target, the uncertainties of the selected pixel positions, the location and uncertainty of location of the vehicle collecting the pixel positions, and other information collected about the target.

System and method for automated bottom feature navigator

System and method for rapidly determining the geographic areas where spatial overlap of arbitrarily oriented (i.e. not just parallel) swath sensor data meets a pre-selected specified percentage of swath width.

System and method for swath overlap detection

System and method for providing an automated method of importing NetCDF formatted data from a variety of sources that contain a variety of internal datasets. Options for processing and analysis can be provided and can occur simultaneously as the data are being processed. Storage and organization options provide efficient viewing and analysis of NetCDF datasets.

System and method for importing NetCDF data

System and method for using forecast ocean currents to improve the prediction of an underwater vessel's trajectory as compared to using a simple dead reckoned path determined by vessel commanded heading and speed through the water. System and method include a motion model specific to underwater gliders that incorporates 4d forecast currents.

System and method for underwater vehicle simulation

A system for the accurate determination of the position of an underwater vehicle comprising a system observer subsystem having a state velocity update module, a terrain matching module, means for generating a prediction of the terrain matching module's performance and a constrained extended Kalman filter subsystem. The constrained extended Kalman filter subsystem includes a steady state extended Kalman filter, a non-linear constraint module, and a state predictor. The system observer integrates bathymetry data corresponding to the area of the submersible vehicle, with the vessel's measured ocean depth, the vessel's predicted state, the vessel's measured velocity into a terrain based state estimate, a final predicted state, the Kalman filter takes the terrain based state estimate, the final predicted state, the measured slant range and the location of the known point and computes the final estimate of the vessel's position and a prediction of the vessel's position at the next time step. A method for the accurate determination of the position of at least one underwater vehicle comprising the steps of (1) acoustically coupling at least one underwater vehicle to a sea borne position marker having a known position; (2) predicting the at least one underwater vehicle's position, based on a past estimate of the underwater vehicle's position, and an estimate of its velocity over the sea bottom; (3) estimating the underwater vehicle's position utilizing measured ocean depth at the underwater vehicle's position, bathymetry data and the underwater vehicle's predicted position in a single point terrain match; (4) computing a estimate of the underwater vehicle's position based on the prediction of the at least one underwater vehicle's position based on vehicle dynamics and the estimated underwater vehicles position based on ocean depth and bathymetry data; and (5) computing a corrected estimate of the at least one submersible vehicle's position that utilizes the estimate of the underwater vehicle's position and a measured slant range from the at least one submersible vehicle to the sea borne position marker whose position is known.

LOST 2&mdash;a positioning system for under water vessels

The shipboard wave measurement system (SWMS) makes measurements as a function of time of vehicle position, range from the vehicle to the water's surface, and vehicle heave, pitch and roll to compute the height, direction, period and wavelength of the principal ocean wave component. Since the vehicle is moving, the wave heights measured are at different spatial locations, as well as at different times, and the observed wave height signal is Doppler shifted. The SWMS is composed of a positioning device, a timing device, a wave height estimator (WHE), a Doppler Integrator (DI) and a computer. The positioning device measures the vehicle's position, the timing device provides accurate time referencing for the vehicle position and wave height measurements. The wave height estimator measures range to the water's surface from the vehicle and vehicle vertical acceleration, pitch and roll and generates wave height at specific instants of time. The Doppler integrator receives the time referenced wave height signal from storage and generates the frequency and height of the principal wave component, both as a function of time. Wave direction, period and wavelength are determined from the wave frequency and vehicle position data using a least-squares approach.

Shipboard wave measurement system

The autonomous survey system (AutoSurvey) is used to automatically maximize area coverage with swath sensors and to minimize survey time while ensuring the collected data meets specified quality constraints. The autonomous survey system (AutoSurvey) evaluates the effects of the environment and system performance on the collected survey data by modulizing the data collection into a series of modules&mdash;data collection and error detection, data georectification, data quality validation, swath-edge fit, next-line way point generation, and the autopilot. All of these processes are implemented in near real-time, allowing unfettered survey progress. The data is applied directly between processes, providing operator independent system operation; the autosurvey system directly controls the survey vessel via the autopilot. Through the real-time data acquisition the system provides automation of the operator quality and coverage assessment tasks and also provides quantified data assessment. The operator is able to adjust the system operating parameters to compensate for ambient conditions and to determine subsequent navigation way points as a function of the specified survey criteria.

Autonomous survey system (auto survey)

The location of a submerged tow vehicle (LOST) system provides a device for accurately determining a position of an underwater vehicle towed by a surface craft or aircraft, such as a helicopter. The LOST system utilizes five sources of input data to compute a best estimate of the towed vehicle's position. These are (1) high resolution bathymetry data in an area of the towed vehicle's transit, (2) ocean depth at a position of the towed vehicle, (3) the towed vehicle's velocity over sea bottom, (4) a slant range from the towed vehicle to a known reference point, and (5) a position and course of the towing vehicle. The LOST system is comprised of a slant range updater, a maximum likelihood estimator, a constrained adaptive tracker and a slant range corrector.

Localization of a submerged tow vehicle (lost)

The depthimeter comprises a heave sensor, a mean path compensator and a combiner. The mean path compensator comprises a ranging device which measures the instantaneous distance of the vehicle from a fixed point on the vehicle to ocean surface as a function of time; a range compensator to compensate for signal dropouts in the ranging devices data, for sensor offset angle, and vehicle pitch and roll, thereby providing a signal that contains the vehicles vertical motion and the vertical motion of the sea surface. A low-pass filter within the mean path compensator eliminates the components of the resulting signal due to the motion of the sea surface and the high frequency components of the vehicle's vertical motion, thereby producing a signal that is the mean path of the vehicle, referenced to mean sea level. The combiner merges the mean path signal from the mean path compensator and a heave signal generated by the heave sensor to generate a signal that is a surface vehicle's draft relative to mean sea level or a submerged vehicle's depth relative to mean sea level. This signal is also the vehicle's vertical displacement with time relative to mean sea level.

Growing community of inventors

Slidell, LA, United States of America

Brian S Bourgeois