A processor of a sonar system extracts a signal in a predetermined time range from a signal received by an acoustic array, calculates a correlation value for a signal waveform extracted, detects a peak value of the correlation value, calculates an integrated value by performing time-integration of a square of the correlation value, obtains a target velocity based on the peak value and the integrated value, and displays the target velocity on a display apparatus.

A learning SONAR system and method including receiving, at an input, mission parameters including one or more of mission accuracy, mission covertness, learning rate, and training matrix dependency; transmitting pulsed signals; receiving return pulsed signals, for instance, using a tunable acoustic receiver having controllable receiver elements; and determining a number of the controllable receiver elements to generate estimates of altitude and 3D velocity based on a combination of transmit power, signal-to-noise ratio, and altitude range using an adaptive spatial sampler of a learning controller.

A horizontal acoustic sediment and current profiler and methods of use. In one implementation, the horizontal acoustic sediment and current profiler includes a housing that is configured to house a plurality of transducer elements. In some implementations, these plurality of transducer elements include a plurality of rectangular transducer elements that are each configured to form a beam having a beam width of less than one degree; a first transducer element that is configured to form a first beam at a first frequency; a second transducer element that is configured to form a second beam at a second frequency, the second frequency differing from the first frequency; and a vertical transducer element that is oriented substantially orthogonal to the first transducer element and the second transducer element, the vertical transducer element configured to measure a depth of placement of the horizontal acoustic sediment and current profiler with respect to a surface of a fluidic medium.

The disclosure relates to a method and a device for determining relevant variables of an object in the environment of a motor vehicle by means of at least one ultrasonic, the method comprising: acquiring a measurement series of real sensor values for the at least one ultrasonic sensor, which sensor values represent the shortest distance between the object and the motor vehicle, wherein the sensor values are acquired cyclically with a specified time interval, modeling a series of sensor values for the at least one ultrasonic sensor by modeling the object movement using a state vector and a parameter vector, and modeling the distance sensing in accordance with the state vector and the parameter vector, and determining the state vector and the parameter vector by adapting the modeled sensor values to the measured real sensor values of the at least one ultrasonic sensor by means of an optimization method.

The present invention relates to an object trajectory estimation technology. A system for three-dimensional (3D) object trajectory estimation according to an exemplary embodiment of the present invention includes: an infrared sensor frame installed in a target space area; an acoustic sensor module installed in the target space area; and a processing unit configured to estimate a trajectory of an object within the target space area on the basis of pieces of data generated from the infrared sensor frame and pieces of data generated from the acoustic sensor module.

A method for providing training datasets for training an object classification model for object classification in an ultrasonic sensor system is disclosed. The method includes (i) providing one or multiple survey scenarios in which at least one surrounding object within a collection range of the ultrasonic sensor system is moved along a trajectory relative to the ultrasonic sensor system, (ii) collecting the ultrasonic signals reflected at the surrounding object at chronologically successive collection situations and respective identification of collection features depending on reflected ultrasonic signals collected during a respective collection situation, (iii) determining a candidate training dataset for each collection situation by associating a classification vector specified by the survey situation, the elements of which each indicate an object property of at least one surrounding object, with the collection features, and (iv) considering the candidate training dataset of each of the collection situations as a training dataset depending on the relative distance from the at least one surrounding object from the ultrasonic sensor system and the relative distances of the surrounding object from the ultrasonic sensor system during previously measured collection situations of candidate training datasets determined.

An ultrasound imaging system (100) includes a transducer array (102) that emits an ultrasound beam and produces at least one transverse pulse-echo field that oscillates in a direction transverse to the emitted ultrasound beam and that receive echoes produced in response thereto and a spectral velocity estimator (110) that determines a velocity spectrum for flowing structure, which flows at an angle of 90 degrees and flows at angles less than 90 degrees with respect to the emitted ultrasound beam, based on the received echoes.

The invention relates to a method for operating a driver assistance system (110). The method has the steps of: a) receiving (S1) a drive state sensor signal (SIG0(t)), which indicates the drive state, at a number of different points in time (t0-t5), b) receiving (S2) a number of sensor signals (SIG1(t)), which indicate the surroundings (200), at a number of different points in time (t0-t5), c) detecting (S3) a number of objects (210, 211) in the surroundings (200) on the basis of a first number of sensor signals (SIG1(t)), which have been detected at a first point in time, d) ascertaining (S4) a position (POS) and a movement vector (VEC) for a detected object (210, 211) on the basis of the first number of sensor signals (SIG1 (t)) and a second number of sensor signals (SIG1(t)), which have been received at a second point in time following the first point in time, using a plurality of different ascertaining methods (V1, V2), wherein different ascertaining methods (V1, V2) of the plurality have a different degree of computing complexity, and e) outputting (S5) a warning signal if a potential collision with the detected object (210, 211) is ascertained on the basis of the drive state sensor signal (SIG0(t)) received at a specified point in time and the position (POS) and the movement vector (VEC) ascertained for the detected object (210, 211).

A system for analysis of sonar data is provided comprising sonar transducer assembl(ies), processor(s), and a memory. The memory includes computer program code that is configured to, when executed, cause processor(s) to receive sonar data, where an object is represented within sonar data, and additional data from a data source other than the sonar transducer assembl(ies). The processor(s) further determine object characteristic(s) of the object using sonar data and additional data, and determine an estimated object-type for the object represented within sonar data using the object characteristic(s). The processor(s) further generate a sonar image based on sonar data, cause display of the sonar image, and cause provision of an indication of the estimated object-type so that the indication of the estimated object-type is correlated to the object representation in the sonar image.

A method for finding door location in an automated way based on observations of people that are equipped with a device whose position is determined acoustically. By observing positioning transitions across internal structures such as walls, the location of doors can be automatically identified.