An underwater detection apparatus that includes a transmission transducer including a plurality of transmission elements to be fixed to a vessel, at least one of the plurality of transmission elements extending in an oblique direction relative to a fore-aft direction of the vessel in a state where the transmission transducer is fixed to the vessel; a reception transducer including a plurality of reception elements; processing circuitry that acquires an attitude information of the vessel; a transmission circuit that drives the plurality of transmission elements based on the attitude information to control the transmission transducer to transmit a transmission wave in a given direction relative to a water surface; and a reception circuit that obtains a reception signal from at least one of the plurality of reception elements based on a reflection wave of the transmission wave.

A method for correcting at least one ultrasound-based measurement of an ultrasonic sensor of a sensor arrangement using a control device. At least one ultrasonic sensor transmits and/or receives sound waves, wherein, based on a time-of-flight measurement of the sound waves, at least one distance to a reflection position along a measurement plane is determined, at least one angle within the measurement plane and/or outside the measurement plane is determined by evaluation of measurement data from transducer elements of at least one ultrasonic sensor array, and a localization error of the at least one determined distance between the ultrasonic sensor and the reflection position is corrected using the determined angle. A sensor arrangement, a control device, a computer program, and a machine-readable storage medium are also described.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for estimating wave properties of a body of water. A computer-implemented system obtains measurement data for a duration of time from an inertial measurement unit (IMU) onboard an underwater device, generates model input data based on at least the measurement data obtained at the plurality of time points, and processes the model input data to generate model output data indicating one or more wave properties using a machine-learning model. The system further determines, based on at least the one or more wave properties, whether the device is safe to be deployed.

Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. In particular, a method may include receiving data associated with a sensor measurement of a perceived object, determining a label associated with the perceived object based on an initial calibration, retrieving log file data associated with the label, determining a calibration parameter associated with the sensor measurement based on the retrieved log file data, and storing the calibration parameter in association with a sensor associated with the sensor measurement. Sensors may be calibrated on the fly while the autonomous vehicle is in operation using one or more other sensors and/or fused data from multiple types of sensors.