A plurality of control points are defined have a known spatial relationship relative to an array of transducers. An amplitude is assigned to each control point. A matrix is produced containing elements which represent, for each of the control points, the effect that producing a modeled acoustic field having the assigned amplitude with a particular phase at the control point has on the consequential amplitude and phase of the modeled acoustic field at the other control points. Eigenvectors of the matrix are determined, each eigenvector representing a set of phases and relative amplitudes of the modeled acoustic field at the control points. One of the sets is selected and the transducer array is operated to cause one or more of the transducers to output an acoustic wave each having an initial amplitude and phase such that the phases and amplitudes of the resultant acoustic field at the control points correspond to the phases and relative amplitudes of the selected set.

An ultrasonic sensor unit for a vehicle. The ultrasonic sensor unit is configured to emit first, second, and third ultrasonic waves. The ultrasonic sensor unit is configured to receive and/or detect a movement path with the ultrasonic sensor unit. The ultrasonic sensor unit is configured to detect first, second, and third reflection, of the first, second, and third ultrasonic wave, of an object. The ultrasonic sensor unit is configured to ascertain a first intersection point between the first reflection and the second reflection, a second intersection point between the second reflection and the third reflection, and a first ellipse based on the first intersection point, the second intersection point and the movement path. The ultrasonic sensor unit is configured to determine a type of the object based on the first ellipse.

Machine learning algorithms can interpret three-dimensional sonar data to provide more precise and accurate determination of seafloor depths and in-water target detection and classification. The models apply architectures for interpreting volumetric data to three-dimensional forward-looking sonar data. A baseline set of training data is generated using traditional image and signal processing techniques, and used to train and evaluate a machine learning model, which is further improved by additional inputs to improve both seafloor and in-water target detection.

Techniques are disclosed for systems and methods to provide high resolution interpolation of arrival direction of echo return signals using an active mills cross arrangement, such as in sonar or other ranging sensor systems. A system may include an active mills cross arrangement with high resolution interpolation of echo returns in two planes. The active mills cross arrangement may include a transmitter configured to emit one or more signals, a first line array including a first plurality of elements defining a first plane, and a second line array including a second plurality of elements defining a second plane orthogonal to the first plane. At least one of the first line array and the second line array may be configured to receive echo returns of the emitted signals from one or more objects or targets.