Abstract: This disclosure describes a radar system configured to estimate a yaw-rate and an over-the-ground (OTG) velocity of extended targets in real-time based on raw radar detections. This disclosure further describes techniques for determining instantaneous values of lateral velocity, longitudinal velocity, and yaw rate of points of a rigid body in a radar field-of-view (FOV) of the radar system.

Abstract: This disclosure describes a radar system configured to estimate a yaw-rate and an over-the-ground (OTG) velocity of extended targets in real-time based on raw radar detections. This disclosure further describes techniques for determining instantaneous values of lateral velocity, longitudinal velocity, and yaw rate of points of a rigid body in a radar field-of-view (FOV) of the radar system.

Abstract: This disclosure describes a radar system configured to estimate a yaw-rate and an over-the-ground (OTG) velocity of extended targets in real-time based on raw radar detections. This disclosure further describes techniques for determining instantaneous values of lateral velocity, longitudinal velocity, and yaw rate of points of a rigid body in a radar field-of-view (FOV) of the radar system.

Abstract: A computer-implemented method and system for calibrating an occupancy grid mapping a vehicle environment are disclosed. An example method includes identifying a feature of an occupancy grid that maps a vehicle environment in which the occupancy grid provides a primary representation of the feature. The example method also includes determining a quality level of the primary representation of the feature and determining if the quality level satisfies a quality criterion. The example method further includes adjusting a calibration of the occupancy grid if the quality level fails to satisfy the quality criterion. The adjustment of the calibration of the occupancy grid can include adjusting at least one parameter used to generate the occupancy grid to cause the quality level to satisfy the quality criterion.

Abstract: A method is provided for arranging a grid with respect to a vehicle position. An initial position and a state of movement of the vehicle are determined. A physical grid specifying a spatial location of grid cells with respect to an earth-fixed coordinate system and a logical grid representing the cells within a memory are defined. An initial arrangement of the physical grid is determined with respect to the initial vehicle position. A mapping is defined between the physical and logical grids, and a torus interconnection is defined between margins of the logical grid. A modification of the vehicle position is determined based on the state of movement of the vehicle. By applying the torus interconnection, a revised logical grid is determined based on the modification of the vehicle position. A current arrangement of the physical grid is determined by mapping the revised logical grid.

Abstract: A computer-implemented method for occupancy state detection in an area for a pre-determined point in time. In aspects, the computer-implemented method includes operations carried out by computer hardware components. The operations include determining a probability distribution over a list of possible occupancy states of the area at a previous point in time, determining measurement data related to the area at the pre-determined point in time, and determining a probability distribution over the list of possible occupancy states of the area at the pre-determined point in time based on the measurement data and the probability distribution over the list of possible occupancy states of the area at the previous point in time.

Abstract: A computer-implemented method and device for mapping a vehicle environment of a vehicle are disclosed. The method comprises determining an occupancy grid representing the vehicle environment, including occupancy probability information of a first set of object detections. The occupancy probability information is determined from first positioning information obtained from a first sensor system. Semantic information and second positioning information associated with the semantic information from one or more semantic information sources is obtained. The semantic information comprises object classification information of a second set of object detections and the second positioning system indicates one or more positions of the second set of object detections with respect to the vehicle. The object classification information of the second set of object detections is combined with the occupancy probability information of the occupancy grid to generate a classified occupancy grid.

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.

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: Methods and systems are described that enable vehicle routing based on availability of radar-localization objects. A request to navigate to a destination is received, and at least two possible routes to the destination are determined. Availabilities of radar-localization objects for the possible routes are determined, and a route is selected based on the availabilities of the radar-localization objects. Furthermore, while traveling along a route, the vehicle is localized based on radar detections of radar-localization objects. A radar-localization quality of the localizing is monitored, and a determination is made that the radar-localization quality has dropped or will drop. Based on the radar-localization quality dropping, the route is modified and/or an operation of a radar module is adjusted. In this way, availabilities of radar-localization objects may be used to select an optimal route and to adjust a current navigation along a route to minimize driver takeover.

Abstract: Provided is a computer-implemented method for mapping a vehicle environment, the method comprising: a) defining a first grid in the earth frame of reference having a first coordinate system; b) initializing a position of the vehicle in the first grid and a first set of cell occupancy values of the first grid; c) receiving sensor data of the surroundings of the vehicle from one or more sensors on the vehicle; d) updating the first grid with a second set of occupancy values calculated at least in part from the sensor data; and e) calculating one or more absolute velocities of one or more objects in the earth frame of reference from the change in cell occupancy values of the first grid.

Abstract: A computer implemented method for determining alignment parameters of a radar sensor comprises the following steps carried out by computer hardware components: determining measurement data using the radar sensor, the measurement data comprising a range-rate measurement, an azimuth measurement, and an elevation measurement; determining a velocity of the radar sensor; and determining the misalignment parameters based on the measurement data and the velocity, the misalignment parameters comprising an azimuth misalignment, an elevation misalignment, and a roll misalignment.

Abstract: A method for estimating a velocity of a target using a host vehicle equipped with a radar system includes determining a plurality of radar detection points, determining a compensated range rate, and determining an estimation of a first component of a velocity profile equation of the target and an estimation of a second component of the velocity profile equation of the target by using an iterative methodology comprising at least one iteration. The estimations and of the first and second components and of the velocity profile equation are not determined from a further iteration if at least one statistical measure representing the deviation of an estimated dispersion of the estimations and of the first and second components, and of a current iteration from a previous iteration and/or the deviation of an estimated dispersion of the residual from a predefined dispersion of the range rate meets a threshold condition.

Abstract: A method of determining the de-aliased range rate of a target in a horizontal plane by a host vehicle equipped with a radar system, said radar system including a radar sensor unit adapted to receive signals emitted from said host vehicle and reflected by said target, comprising: emitting a radar signal at a single time-point instance and determining from a plurality (m) of point radar detections measurements therefrom captured from said radar sensor unit, the values for each point detection of, azimuth and range rate; [?i, {dot over (r)}i]; for each point detection determining a range rate compensated value ({dot over (r)}i,cmp); c) determining a plurality (j) of velocity profile hypotheses; for each (j-th) hypothesis determining modified compensated hypothesis range rates ({dot over (r)}i,j,cmp) in respect of each point detection on the target, based on the values of range rate compensated ({dot over (r)}i,cmp); for each j-th hypothesis, determining values of the longitudinal and lateral components of the ra

Abstract: A method for estimating a velocity of a target using a host vehicle equipped with a radar system includes determining a plurality of radar detection points, determining a compensated range rate, and determining an estimation of a first component of a velocity profile equation of the target and an estimation of a second component of the velocity profile equation of the target by using an iterative methodology comprising at least one iteration. The estimations and of the first and second components and of the velocity profile equation are not determined from a further iteration if at least one statistical measure representing the deviation of an estimated dispersion of the estimations and of the first and second components, and of a current iteration from a previous iteration and/or the deviation of an estimated dispersion of the residual from a predefined dispersion of the range rate meets a threshold condition.

Abstract: A method of determining the yaw rate ({circumflex over (?)}t) of a target vehicle in a horizontal plane by a host vehicle equipped with a radar system, said radar system including a radar sensor unit adapted to receive signals emitted from said host vehicle by said target, comprising: emitting a radar signal at a single time-point instance and determining from a plurality (m) of point radar detections measurements captured from said target vehicle by said radar sensor unit in said single radar measurement instance, the values for each point detection of range, azimuth and range rate; [ri, ?i, {dot over (r)}i]; determining the values of the longitudinal and lateral components of the range rate equation of the target (ct, st) from the results ({dot over (r)}i, ?i,) and the sensor unit or host vehicle longitudinal velocity and vs is the sensor unit or host vehicle lateral velocity; determining the orientation angle of the target (?t,scs); determining the target center (xt and yt) from the results (ri, ?i); deter

Abstract: A method of determining the de-aliased range rate of a target in a horizontal plane by a host vehicle equipped with a radar system, said radar system including a radar sensor unit adapted to receive signals emitted from said host vehicle and reflected by said target, comprising: emitting a radar signal at a single time-point instance and determining from a plurality (m) of point radar detections measurements therefrom captured from said radar sensor unit, the values for each point detection of, azimuth and range rate; [?i, {dot over (r)}i]; for each point detection determining a range rate compensated value ({dot over (r)}i,cmp); c) determining a plurality (j) of velocity profile hypotheses; for each (j-th) hypothesis determining modified compensated hypothesis range rates ({dot over (r)}i,j,cmp) in respect of each point detection on the target, based on the values of range rate compensated ({dot over (r)}i,cmp); for each j-th hypothesis, determining values of the longitudinal and lateral components of the ra