Described herein are methods and devices for improved location of any and all underwater structures or equipment installed underwater. In particular, systems are disclosed that combine optical and acoustic metrology for locating objects in underwater environments. The systems allow for relative positions of objects to be determined with great accuracy using optical techniques, and support enhanced location of devices that utilize acoustic location techniques. In addition, location information can be provided by the system even in conditions that make optical metrology techniques impossible or impractical.

Described herein are methods and devices for improved location of any and all underwater structures or equipment installed underwater. In particular, systems are disclosed that combine optical and acoustic metrology for locating objects in underwater environments. The systems allow for relative positions of objects to be determined with great accuracy using optical techniques, and support enhanced location of devices that utilize acoustic location techniques. In addition, location information can be provided by the system even in conditions that make optical metrology techniques impossible or impractical.

Apparatus and associated methods relate to a self-contained ocean data and acquisition module (SCODAM) configured to mount to a floating body and having a sensor array, geospatial locating engine, wave measurement engine, communication engine to transmit collected data to a remote device, an energy conversion module adapted to convert ambient energy inputs into electrical energy, and an energy storage module configured to receive the converted electrical energy and to supply operating power to the SCODAM. In an illustrative example, the SCODAM may be configured to generate a transfer function based on motion characterization data obtained in a training mode corresponding to motion of the floating body in response to perturbation in a predetermined sequence and to apply the transfer function data obtained by the wave measurement engine to determine wave motion. Various embodiments may advantageously facilitate use of an existing floating body as an ocean data acquisition system (ODAS).

The present disclosure relates to a method for measuring a water level by using a UAV and virtual water control points and a method for generating 3D water surface spatial information, and a UAV used therefor. According to an embodiment, an UAV for a water surface survey includes: a position measurement unit configured to receive a GPS signal and to obtain position information of the UAV; a distance measurement unit including a plurality of laser measurement devices configured to project lasers toward the water surface; and a controller configured to calculate a moving distance of the UAV, based on measurement values of the position measurement unit and the distance measurement unit.

Aquatic environment monitoring devices, systems and methods are provided. An aquatic vehicle includes a body supporting a drive sub-system configured to drive the aquatic vehicle along a travel path, at least one sensor configured to obtain a plurality of sensor data points at a plurality of different locations along the travel path, a GPS module configured to track movement of the aquatic vehicle along the travel path, and a microcontroller configured to compile the sensor data points with GPS location data corresponding to a location where each of the sensor data points was obtained. A remote computer is configured to receive the compiled data from the microcontroller and, based thereon, provide an output correlating the sensor data points with the GPS location data.

Aquatic environment monitoring devices, systems and methods are provided. An aquatic vehicle includes a body supporting a drive sub-system configured to drive the aquatic vehicle along a travel path, at least one sensor configured to obtain a plurality of sensor data points at a plurality of different locations along the travel path, a GPS module configured to track movement of the aquatic vehicle along the travel path, and a microcontroller configured to compile the sensor data points with GPS location data corresponding to a location where each of the sensor data points was obtained. A remote computer is configured to receive the compiled data from the microcontroller and, based thereon, provide an output correlating the sensor data points with the GPS location data.

The present disclosure provides a system and a method for measuring water capacity of polar lakes, and relates to the technical field of lake water capacity measurement. The method comprises the steps: controlling an unmanned aerial vehicle to move along with an unmanned underwater vehicle at a preset height right above the unmanned underwater vehicle by utilizing an ADRC algorithm; obtaining lake surface point cloud data, under-lake point cloud data and under-lake single-beam ranging data so as to construct a water three-dimensional topographic map, a lake coastal three-dimensional topographic map and a lake bottom three-dimensional topographic map under the same coordinate system, and then determining the lake water capacity. By arranging the unmanned underwater vehicle, an unmanned underwater vehicle-mounted module, the unmanned aerial vehicle and an unmanned aerial vehicle-mounted module, lake elevation and lake underwater terrain data are automatically measured, so that the observation precision of polar lakes is improved.

The present disclosure discloses a tropical instability wave early warning method based on temporal-spatial cross-scale attention fusion, including performing cross-scale spatial map fusion on the multi-scale feature maps by a bilateral local attention mechanism, calculating a prediction loss by the global feature description map, and combining the prediction loss and the regularization loss for optimization training of neural networks; predicting a sea surface temperature at a moment T based on the optimally trained neural networks, selecting data at K moments before the moment T and inputting the data into the optimally trained neural networks, outputting a predicted value of tropical instability waves by the optimally trained neural networks, and drawing a temporal-spatial image of the tropical instability waves by associating the predicted value with coordinates, so as to achieve early warning of the tropical instability waves. The device includes a processor and a memory.

An improved sensor fish with robust design and enhanced measurement capabilities. This sensor fish contains sensors for acceleration, rotation, magnetic field intensity, pressure, and temperature. A low-power microcontroller collects data from the sensors and stores up to 5 minutes of data on a non-volatile flash memory. A rechargeable battery supplies power to the sensor fish. A recovery system helps locating sensor fish. The package, when ready for use is nearly neutrally buoyant and thus mimics the behavior of an actual fish.

A multi-node data synchronous acquisition system and a method for real-time monitoring of underwater surface deformation. The system includes at least four sensor arrays, where each of the sensor array consists of a plurality of ribbon-like rigid substrates connected by movable joints. On each section of rigid substrate, three sensor units are respectively connected to a slave station data acquisition unit through cables. The slave station data acquisition unit is connected with a central controller through a cable. The central controller includes a compressive cabin outside and an embedded controller and a power supply inside. Each slave station data acquisition unit acquires data from an MEMS attitude sensor and then transmits it to the embedded controller. The present invention may realize synchronous acquisition of underwater or even underwater multi-node data, implement three-dimensional surface reconstruction, and may be used for improving the ocean observation capability.