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 computer implemented method for calibrating a motion sensor arranged at a vehicle and configured to output a raw motion measurement value indicative of a current motion condition of the vehicle comprises: computing processed motion measurement values by modifying the outputted raw motion measurement value based on a set of different calibration parameters, monitoring the vicinity of the vehicle by means of an environment perception sensor, determining a set of occupancy maps by means of mapping data acquired by the environment perception sensor in accordance with a motion model for the vehicle, wherein each of the processed motion measurement values is used to establish the motion model for one of the occupancy maps, and selecting, based on a comparison of the determined occupancy maps, one of the different calibration parameters for modifying subsequently outputted raw motion measurement values.

Abstract: This document describes methods and systems for vehicle localization based on radar detections. Radar localization starts with building a radar reference map. The radar reference map may be generated and updated using different techniques as described herein. Once a radar reference map is available, real-time localization may be achieved with inexpensive radar sensors and navigation systems. Using the techniques described in this document, the data from the radar sensors and the navigation systems may be processed to identify stationary localization objects, or landmarks, in the vicinity of the vehicle. Comparing the landmark data originating from the onboard sensors and systems of the vehicle with landmark data detailed in the radar reference map may generate an accurate pose of the vehicle in its environment. By using inexpensive radar systems and lower quality navigation systems, a highly accurate vehicle pose may be obtained in a cost-effective manner.

Abstract: Provided is method for determining free space surrounding a device, the method comprising: acquiring radar data regarding each of one or more radar antennas, the acquired radar data comprising range data and range rate data; extracting, from the acquired radar data, a specific set of radar data having values equal to or below a noise-based threshold; and determining a free space around the device based on the extracted specific set of radar data.

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: Methods and systems are described that enable radar reference map generation. A high-definition (HD) map is received and one or more HD map objects within the HD map are determined. Attributes of the respective HD map objects are determined, and, for each HD map object, one or more occupancy cells of a radar occupancy grid are indicated as occupied space based on the attributes of the respective HD map object. By doing so, a radar reference map may be generated without a vehicle traversing through an area corresponding to the radar reference map.

Abstract: A computer-implemented method for determining a position of a vehicle is disclosed, wherein the vehicle is equipped with a sensor for capturing scans of a vicinity of the vehicle, wherein the method comprises at least the following steps carried out by computer-hardware components: capturing at least one scan by means of the sensor with a plurality of sensor data samples given in a sensor data representation; determining, from a database, a predefined map with at least one element is given in a map data representation; determining a transformed map by transforming the at least one element of the predefined map from the map data representation into the sensor data representation; matching at least a subset of the sensor data samples of the at least one scan and the at least one element of the transformed map; and determining the position of the vehicle based on the matching.

Abstract: A computer-implemented method for determining a position of a vehicle is disclosed, wherein the vehicle is equipped with a sensor for capturing scans of a vicinity of the vehicle, wherein the method comprises at least the following steps carried out by computer-hardware components: capturing at least one scan by means of the sensor with a plurality of sensor data samples given in a sensor data representation; determining, from a database, a predefined map with at least one element is given in a map data representation; determining a transformed map by transforming the at least one element of the predefined map from the map data representation into the sensor data representation; matching at least a subset of the sensor data samples of the at least one scan and the at least one element of the transformed map; and determining the position of the vehicle based on the matching.

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 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 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 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: 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: This document describes methods and systems for vehicle localization based on radar detections. Radar localization starts with building a radar reference map. The radar reference map may be generated and updated using different techniques as described herein. Once a radar reference map is available, real-time localization may be achieved with inexpensive radar sensors and navigation systems. Using the techniques described in this document, the data from the radar sensors and the navigation systems may be processed to identify stationary localization objects, or landmarks, in the vicinity of the vehicle. Comparing the landmark data originating from the onboard sensors and systems of the vehicle with landmark data detailed in the radar reference map may generate an accurate pose of the vehicle in its environment. By using inexpensive radar systems and lower quality navigation systems, a highly accurate vehicle pose may be obtained in a cost-effective manner.

Abstract: Methods and systems are described that enable radar reference map generation. A radar occupancy grid is received, and radar attributes are determined from occupancy probabilities within the radar occupancy grid. Radar reference map cells are formed, and the radar attributes are used to determine Gaussians for the radar reference map cells that contain a plurality of the radar attributes. A radar reference map is then generated that includes the Gaussians determined for the radar referenced map cells that contain the plurality of radar attributes. By doing so, the generated radar reference map is accurate while being spatially efficient.