Abstract: A method is provided for determining a mobility status of a target object located in an environment of a sensor configured to monitor a surrounding environment of a vehicle. According to the method, a detection angle of the target object is determined with respect to the sensor based on data acquired by the sensor, and an ideal beam vector for a stationary object is predicted based on the detection angle. The ideal beam vector and a measured beam vector obtained from the data acquired by the sensor are normalized, and a correlation of the normalized ideal beam vector and the normalized measured beam vector is determined. A score is determined based on the correlation of the normalized ideal and measured beam vectors and indicates whether the target object is stationary or moving.

Abstract: A computer implemented method for determining an angle of a detection comprises the following steps carried out by computer hardware components: acquiring a range rate of the detection; determining a pair of candidate angles of the detection based on the range rate; acquiring a beamvector of the detection; determining a correlation between the beamvector and a reference vector; and determining the angle of the detection based on the pair of candidate angles and based on the correlation.

Abstract: A method is provided for determining a mobility status of a target object located in an environment of a sensor configured to monitor a surrounding environment of a vehicle. According to the method, a detection angle of the target object is determined with respect to the sensor based on data acquired by the sensor, and an ideal beam vector for a stationary object is predicted based on the detection angle. The ideal beam vector and a measured beam vector obtained from the data acquired by the sensor are normalized, and a correlation of the normalized ideal beam vector and the normalized measured beam vector is determined. A score is determined based on the correlation of the normalized ideal and measured beam vectors and indicates whether the target object is stationary or moving.

Abstract: A computer-implemented method for determining an initial ego-pose for initialization of self-localization includes providing a plurality of particles in a map; grouping the particles in a plurality of clusters, each cluster comprising a respective subset of the plurality of particles; during particle filtering, injecting particles based on the plurality of clusters; and determining an initial ego-pose based on the particle filtering.

Abstract: A computer implemented method for determining a position, and/or an acceleration, and/or an angular rate and/or an orientation of a vehicle includes the following steps carried out by computer hardware components: determining first measurement data using a first sensor; determining a preliminary position and/or a preliminary orientation based on the first measurement data; determining second measurement data using a second sensor, wherein the second sensor includes a radar sensor and/or a LIDAR sensor and/or a camera; determining a preliminary acceleration and/or a preliminary angular rate based on the second measurement data; and determining a final position, and/or a final acceleration, and/or a final angular rate and/or a final orientation based on the preliminary acceleration and/or the preliminary angular rate, and the preliminary position and/or the preliminary orientation.

Abstract: A computer implemented method for determining the position of a vehicle, wherein the method comprises: determining at least one scan comprising a plurality of detection points, wherein each detection point is evaluated from a signal received at the at least one sensor and representing a location in the vehicle environment; determining, from a database, a predefined map, wherein the map comprises a plurality of elements in a map environment, each of the elements representing a respective one of a plurality of static landmarks in the vehicle environment, and the map environment representing the vehicle environment; matching the plurality of detection points and the plurality of elements of the map; determining the position of the vehicle based on the matching; wherein the predefined map further comprises a spatial assignment of a plurality of parts of the map environment to the plurality of elements, and wherein the spatial assignment is used for the matching.

Abstract: A method for fusing a first occupancy map and a second occupancy map comprises: determining at least one fusion parameter representing a potential dissimilarity between the first occupancy map and the second occupancy map and determining a fused occupancy map representing free and occupied space around the vehicle. The fused occupancy map is determined based on the first occupancy map, the second occupancy map, and a fusion rule. The fusion rule is configured to control the influence of the first occupancy map and/or the second occupancy map on the fused occupancy map based on the at least one fusion parameter.

Abstract: A computer implemented method for determining the position of a vehicle, wherein the method comprises: determining at least one scan comprising a plurality of detection points, wherein each detection point is evaluated from a signal received at the at least one sensor and representing a location in the vehicle environment; determining, from a database, a predefined map, wherein the map comprises a plurality of elements in a map environment, each of the elements representing a respective one of a plurality of static landmarks in the vehicle environment, and the map environment representing the vehicle environment; matching the plurality of detection points and the plurality of elements of the map; determining the position of the vehicle based on the matching; wherein the predefined map further comprises a spatial assignment of a plurality of parts of the map environment to the plurality of elements, and wherein the spatial assignment is used for the matching.

Abstract: A method is described for determining the position of a vehicle equipped with a radar system that includes at least one radar sensor adapted to receive radar signals emitted from at least one radar emitter of the radar system and reflected the radar sensor. The method comprises: acquiring at least one radar scan comprising a plurality of radar detection points, wherein each radar detection point is evaluated from a radar signal received at the radar sensor and representing a location in the vicinity of the vehicle; determining, from a database, a predefined map, wherein the map comprises at least one element representing a static landmark in the vicinity of the vehicle; matching at least a subset of the plurality of radar detection points of the at least one scan and the at least one element of the map; deter-mining the position of the vehicle based on the matching.

Abstract: A method is provided for estimating an angle of an object with respect to a vehicle. A transformation of reflected radar signals is calculated, wherein the result of the transformation depends on a range with respect to the vehicle. A long beam vector is generated for respective range bins provided by the transformation by rearranging the result of the transformation such that the respective long beam vector comprises elements of the transformation from radar all receiver elements for each range bin. A reference vector is calculated for each range bin based on a signal model which depends on the motion of the target object relative to the vehicle and which is parameterized regarding the angle of the target object. The long beam vector and the reference vector are correlated, and the angle of the target object is determined based on the correlation result.

Abstract: A method of determining ego-motion information of a vehicle comprising a radar sensor having a plurality of antenna elements, comprising: acquiring motion spectrum comprising a plurality of data elements, each calculated for a respective one of a plurality of Doppler bin indices and for a respective one of a plurality of spatial bin indices, each spatial bin index indicating a respective angle-of-arrival of a radar return signal at the radar sensor; and determining the ego-motion information by solving a motion equation system comprising equations of motion generated using the motion spectrum data and each relating a respective value indicating a radial velocity, a respective value indicating an angular displacement, and a variable indicating a velocity of the vehicle.

Abstract: Described is a way to process radar data for a radar sensor mounted on a vehicle to generate motion spectrum data for estimating ego-motion information of the vehicle. Data samples of each of a plurality of radar return signals received at each antenna element of the radar sensor are generated for each antenna element. Respective Doppler-processed data including a plurality of data values is calculated for each Doppler bin index. In generating a set of motion spectrum data, which comprises a plurality of data elements each calculated for a respective Doppler bin index and a respective spatial bin index, data values of the Doppler-processed data calculated for the Doppler bin index are selected to calculate a covariance matrix. A spectral estimation algorithm, which uses the covariance matrix, can determine a spatial spectrum value for each spatial bin index.

Abstract: A computer implemented method for determining an angle of a detection comprises the following steps carried out by computer hardware components: acquiring a range rate of the detection; determining a pair of candidate angles of the detection based on the range rate; acquiring a beamvector of the detection; determining a correlation between the beamvector and a reference vector; and determining the angle of the detection based on the pair of candidate angles and based on the correlation.

Abstract: A method for increasing the reliability of determining the position of a vehicle on the basis of a plurality of detection points is described, the plurality of detection points being acquired using a radio-based and/or an optical sensor system, in particular a radar system, of a vehicle receiving electromagnetic signals from a vicinity of the vehicle, and each of the plurality of detection point representing a location in the vicinity of the vehicle, wherein the method comprises for each detection point of at least a subset of the plurality of detection points: determining at least one geometrical object associated with the detection point; determining at least one group of detection points from the subset sharing the at least one geometrical object; determining a quantity of detection points in the at least one group; evaluating a weight which represents the quantity of detection points in the at least one group on a predefined scale, and processing the detection point with respect to the weight.

Abstract: A method of determining an alignment error of an antenna is described, wherein the antenna is installed at a vehicle and in cooperation with a detection device, and wherein the detection device is configured to determine a plurality of detections. Determining the plurality of detections comprises emitting a first portion of electromagnetic radiation through the antenna, receiving a second portion of electromagnetic radiation through the antenna, and evaluating the second portion of electromagnetic radiation in dependence of the first portion of electromagnetic radiation in order to localize areas of reflection of the first portion of electromagnetic radiation in the vicinity of the antenna. The method comprises determining a first detection and at least a second detection by using the detection device, and determining the alignment error by means of a joint evaluation of the first detection and the second detection.

Abstract: A computer implemented method for detection of objects in a vicinity of a vehicle comprises the following steps carried out by computer hardware components: acquiring radar data from a radar sensor; determining a plurality of features based on the radar data; providing the plurality of features to a single detection head; and determining a plurality of properties of an object based on an output of the single detection head.

Abstract: A method is described for determining the position of a vehicle equipped with a radar system that includes at least one radar sensor adapted to receive radar signals emitted from at least one radar emitter of the radar system and reflected the radar sensor. The method comprises: acquiring at least one radar scan comprising a plurality of radar detection points, wherein each radar detection point is evaluated from a radar signal received at the radar sensor and representing a location in the vicinity of the vehicle; determining, from a database, a predefined map, wherein the map comprises at least one element representing a static landmark in the vicinity of the vehicle; matching at least a subset of the plurality of radar detection points of the at least one scan and the at least one element of the map; deter-mining the position of the vehicle based on the matching.

Abstract: A computer-implemented method for determining an initial ego-pose for initialization of self-localization includes providing a plurality of particles in a map; grouping the particles in a plurality of clusters, each cluster comprising a respective subset of the plurality of particles; during particle filtering, injecting particles based on the plurality of clusters; and determining an initial ego-pose based on the particle filtering.

Abstract: A computer implemented method for determining an initial ego-pose for initialization of self-localization comprises the following steps carried out by computer hardware components: providing a plurality of particles in a map; grouping the particles in a plurality of clusters; performing particle filtering individually for each of the clusters; and determining an initial ego-pose based on the particle filtering.

Abstract: A computer implemented method for determining the position of a vehicle, wherein the method comprises: determining at least one scan comprising a plurality of detection points, wherein each detection point is evaluated from a signal received at the at least one sensor and representing a location in the vehicle environment; determining, from a database, a predefined map, wherein the map comprises a plurality of elements in a map environment, each of the elements representing a respective one of a plurality of static landmarks in the vehicle environment, and the map environment representing the vehicle environment; matching the plurality of detection points and the plurality of elements of the map; determining the position of the vehicle based on the matching; wherein the predefined map further comprises a spatial assignment of a plurality of parts of the map environment to the plurality of elements, and wherein the spatial assignment is used for the matching.