Abstract: A method and system of determining a relative radial velocity of a radar target by operating a radar sensor having a plurality of multiplexed transmission channels, wherein modulated transmission signals are sent in repeated multiplex sequences in which the transmission signals sent in different transmission channels have a predetermined spread in at least one of a time, frequency, and phase domain, and the velocity of the target is inferred from a Doppler-induced phase progression of the received signals, the method including the steps of: switching between at least two multiplex sequences which differ in the spread between the transmission channels and thereby induce different phase progressions; and inferring the velocity of the target from the differences between said phase progressions.

Abstract: A device and method for determining a classification of an object. A radar spectrum which includes radar reflections is determined as a function of sensor data from a radar sensor. Embeddings of sections from the radar spectrum which include at least one radar reflection are determined and each is assigned to a node of a first graph. Edges are determined as a function of pairwise distances between the embeddings which are assigned to the nodes. For each edge, a feature for the edge is determined as a function of the embeddings of two nodes which are connected to one another by the edge. For each node, a feature for the node is determined as a function of the features for the edges which connect the node to another node. A characteristic quantity is provided for each radar reflection as a function of the sensor data.

Abstract: A system and method for providing classified digital recordings, for a system for automatic machine learning. A first digital recording is captured at a first point in time which includes an object situated at the first point in time at a first distance from the recording unit. A first classification of the object is determined using the data of the first digital recording. At a second point in time, a second digital recording is captured, which includes the object situated at the second point in time at a second distance from the recording unit. A second classification of the object is determined using the data of the second digital recording. A digital recording classified using a result of the second classification is provided, which includes at least a part of the first digital recording when a result of the first classification differs from the result of the second classification.

Abstract: Use of a radar sensor with a waveguide antenna array, having at least two groups of antenna units having a plurality of antenna elements, wherein antenna elements in each antenna unit are arranged next to one another in a first direction, wherein, in a first group, the antenna units are arranged offset with respect to one another in a second direction perpendicular to the first direction, and wherein, in a second group, the antenna units are arranged offset with respect to one another in the first direction, for a method for determining an estimated ego velocity value and an estimated angle value of targets. In the method, using the radar sensor, a distance between the radar sensor and the respective target is in each case measured, and a relative velocity of the respective target is in each case measured using the Doppler effect.

Abstract: A method for reconstructing elevation information from measured data that were recorded with the aid of at least one radar device and include a two-dimensional spatial distribution of at least one physical measured variable. The measured data are fed as input variables to at least one generator module that is designed as a neural network. At least one output variable is retrieved from the generator module that represents a measure of the elevation angles from which radar radiation was reflected to the radar device from at least one object. A method for training a generator module, and a method including a complete active chain up to activating a vehicle, are also described.

Abstract: A method for low-interference operation of a plurality of radar sensors, which are installed in different vehicles and each emit a transmission signal in an operating range, which is characterized by at least one of the following parameters: frequency, coding, activity time window. Each radar sensor is assigned an operating range according to at least one degree of freedom of movement of the vehicle, in which the radar sensor is installed.

Abstract: Radar sensor for motor vehicles. The radar sensor has a high-frequency part, which is configured to transmit sequences of modulated radar pulses and to receive the corresponding radar echoes, and an electronic evaluation part, which is configured to take distance and angle measurements using a synthetic aperture, and includes a scanning module, an FFT module for performing fast Fourier transforms to calculating a two-dimensional distance/velocity radar image, a transform module configured to transform the raw data, while simultaneously correcting migration effects, into a format that can be processed by the FFT module, by applying a transform function defined by a number N of coefficients, and a coefficient module for preparing the coefficients for the transform module. The coefficient module including a memory, in which there is stored an initial set of coefficients comprising fewer than N coefficients, and a recursion module, for recursive calculation of the remaining coefficients.

Abstract: A method and system of determining a relative radial velocity of a radar target by operating a radar sensor having a plurality of multiplexed transmission channels, wherein modulated transmission signals are sent in repeated multiplex sequences in which the transmission signals sent in different transmission channels have a predetermined spread in at least one of a time, frequency, and phase domain, and the velocity of the target is inferred from a Doppler-induced phase progression of the received signals, the method including the steps of: switching between at least two multiplex sequences which differ in the spread between the transmission channels and thereby induce different phase progressions; and inferring the velocity of the target from the differences between said phase progressions.

Abstract: A device, a computer program, a computer-implemented method for generating a data-based model copy and a first sensor. The method includes: transforming specified raw data from a first sensor into data representing raw data of a second sensor; determining a first result with the specified raw data and with a first model designed to predict results based on raw data from the first sensor; determining a second result with the data representing the raw data of the second sensor and with a specified second model designed to predict results based on raw data from the second sensor; determining whether or not the first and second results differ. The method includes the following steps when the first result differs from the second result: determining a training data point including the specified raw data and the second result; training the first model with training data including the training data point.

Abstract: A device and method for determining a classification of an object. A radar spectrum which includes radar reflections is determined as a function of sensor data from a radar sensor. Embeddings of sections from the radar spectrum which include at least one radar reflection are determined and each is assigned to a node of a first graph. Edges are determined as a function of pairwise distances between the embeddings which are assigned to the nodes. For each edge, a feature for the edge is determined as a function of the embeddings of two nodes which are connected to one another by the edge. For each node, a feature for the node is determined as a function of the features for the edges which connect the node to another node. A characteristic quantity is provided for each radar reflection as a function of the sensor data.

Abstract: An operating method for a LIDAR system. A laser device that includes an optical modulator optically coupled thereto for receiving and modulating the frequency of non-modulated light emitted by the laser device, using a frequency modulation function, and for outputting frequency-modulated light as primary light into a visual field, is used as a light source unit. Secondary light received from the visual field and non-modulated light of the laser device are optically superimposed to form superimposed detection light. The superimposed detection light is photoelectrically detected by generating and outputting a primary electrical detection signal that is representative of the detection light. For the evaluation, the primary electrical detection signal is electrically mixed with an electrical signal that is representative of the frequency modulation function of the optical modulator to form a first evaluation signal, and is assessed.

Abstract: A method and device for determining a classification for an object. The device is designed to provide pixels of a radar image that are assigned to the object, wherein the device is designed to provide a point cloud, wherein the point cloud comprises at least one point that represents a radar reflection assigned to the object, through at least one property assigned to the object, wherein the device is designed to extract first features that characterize the object, from the pixels, to extract second features that characterize the object, from the point cloud, and to determine the classification of the object depending on the first features and the second features.

Abstract: A method for determining an ego-velocity estimated value and an angle estimated value of targets using a synthetic aperture radar sensor. A distance is measured between the synthetic aperture radar sensor and each respective target. A relative velocity of the respective target is measured using the Doppler effect. An angle estimation of an angle estimated value takes place, which characterizes the angle between the direction of the ego-velocity of the synthetic aperture radar and the respective target. An individual ego-velocity estimated value of the synthetic aperture radar sensor is ascertained using the relative velocity and the angle estimated value for each target.

Abstract: A method for training a generator. The generator is supplied with at least one actual signal that includes real or simulated physical measured data from at least one observation of the first area. The actual signal is translated by the generator into a transformed signal that represents the associated synthetic measured data in a second area. Using a cost function, an assessment is made concerning to what extent the transformed signal is consistent with one or multiple setpoint signals, at least one setpoint signal being formed from real or simulated measured data of the second physical observation modality for the situation represented by the actual signal. Trainable parameters that characterize the behavior of the generator are optimized with the objective of obtaining transformed signals that are better assessed by the cost function. A method for operating the generator, and that encompasses the complete process chain are also provided.

Abstract: A MIMO radar system.

Abstract: A method for operating a radar sensor in a motor vehicle, in which in a SAR measuring mode according to the principle of the synthetic aperture, objects, including stationary objects, are located with high angular resolution. The same radar sensor is operated in time-shifted manner or concurrently in the SAR measuring mode and in a Doppler measuring mode, the relative speeds of objects, including moving objects, being measured with a time resolution in the Doppler measuring mode that is greater than the time resolution in the SAR measuring mode.

Abstract: A method for operating a sensor of a motor vehicle. The method includes: ascertaining an ego trajectory of the sensor, generating adaptation signals for adapting at least one operating parameter of the sensor based on the ascertained ego trajectory and outputting the adaptation signals in order to adapt the at least one operating parameter of the sensor based on the adaptation signals. A device, a sensor system, a motor vehicle, a computer program, and a machine-readable memory medium, are also described.

Abstract: A MIMO radar system including a transmitter array, and a receiver array, the antenna distances in one of the transmitter and receiver arrays being above the Nyquist limit for unambiguous angle measurements, but the antenna distances in the combination of the transmitter and receiver arrays being below this Nyquist limit. The system also includes a control and evaluation unit.

Abstract: A method for training a trainable module for evaluating radar signals. The method includes feeding actual radar signals and/or actual representations derived therefrom of a scene observed using the actual radar signals to the trainable module and conversion thereof by this trainable module to processed radar signals and/or to processed representations of the respective scene, and using a cost function to assess to what extent the processed radar signals are suited for reconstructing a movement of objects or to what extent the processed representations contain artifacts of moving objects in the scene. Parameters, which characterize the performance characteristics of a trainable module, are optimized with regard to the cost function. A method is also provided for evaluating moving objects from radar signals.

Abstract: A system and method for providing classified digital recordings, for a system for automatic machine learning. A first digital recording is captured at a first point in time which includes an object situated at the first point in time at a first distance from the recording unit. A first classification of the object is determined using the data of the first digital recording. At a second point in time, a second digital recording is captured, which includes the object situated at the second point in time at a second distance from the recording unit. A second classification of the object is determined using the data of the second digital recording. A digital recording classified using a result of the second classification is provided, which includes at least a part of the first digital recording when a result of the first classification differs from the result of the second classification.