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.

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.

A mechanism is provided for estimating mounting orientation yaw and pitch of a radar sensor without need of prior knowledge or information from any other sensor on an automobile. Embodiments estimate the sensor heading (e.g., azimuth) due to movement of the automobile from radial relative velocities and azimuths of radar target detections. This can be performed at every system cycle, when a new radar detection occurs. Embodiments then can estimate the sensor mounting orientation (e.g., yaw) from multiple sensor heading estimations. For further accuracy, embodiments can also take into account target elevation measurements to either more accurately determine sensor azimuth and yaw or to also determine mounting pitch orientation.

A mechanism is provided for estimating mounting orientation yaw and pitch of a radar sensor without need of prior knowledge or information from any other sensor on an automobile. Embodiments estimate the sensor heading (e.g., azimuth) due to movement of the automobile from radial relative velocities and azimuths of radar target detections. This can be performed at every system cycle, when a new radar detection occurs. Embodiments then can estimate the sensor mounting orientation (e.g., yaw) from multiple sensor heading estimations. For further accuracy, embodiments can also take into account target elevation measurements to either more accurately determine sensor azimuth and yaw or to also determine mounting pitch orientation.

Data from a radar sensor moving through a static environment may be smoothed and used to generate range profiles by approximating peaks. A direction of arrival (DOA) can then be determined based on the range profile in order to generate a reprojection map. The reprojection map is used to provide updates to a stored map in a robot.

Data from a radar sensor moving through a static environment may be smoothed and used to generate range profiles by approximating peaks. A direction of arrival (DOA) can then be determined based on the range profile in order to generate a reprojection map. The reprojection map is used to provide updates to a stored map in a robot.

A method of determining kinetic information may include: receiving a plurality of raw information related to a plurality of objects using a radar device provided in a vehicle; obtaining, by analyzing the plurality of raw information, a plurality of candidate kinetic information related to the vehicle; estimating, through spatial filtering, current first kinetic information related to the vehicle from the plurality of candidate kinetic information; and correcting, using a kinetic model, the estimated current first kinetic information based on current first kinetic information, wherein the current first kinetic information is predicted from previous first kinetic information related to the vehicle using a kinetic model.

A method of determining kinetic information may include: receiving a plurality of raw information related to a plurality of objects using a radar device provided in a vehicle; obtaining, by analyzing the plurality of raw information, a plurality of candidate kinetic information related to the vehicle; estimating, through spatial filtering, current first kinetic information related to the vehicle from the plurality of candidate kinetic information; and correcting, using a kinetic model, the estimated current first kinetic information based on current first kinetic information, wherein the current first kinetic information is predicted from previous first kinetic information related to the vehicle using a kinetic model.

A method may involve sending signals with a frequency modulated continuous wave radar, receiving the signals reflected at the radar, and processing the received signals into point cloud data having a plurality of points. The method may involve assigning the plurality of points to a track and determining track information based on the plurality of points assigned to the track. The method may involve comparing track information against debounce criteria, where track information may be flagged as dynamic clutter by using a Kalman filter based algorithm on the track information. The method may include calculating a velocity of the vehicle based on the flagged track information. The method may change an operation of the vehicle in response to the calculated velocity of the vehicle.

A method may involve sending signals with a frequency modulated continuous wave radar, receiving the signals reflected at the radar, and processing the received signals into point cloud data having a plurality of points. The method may involve assigning the plurality of points to a track and determining track information based on the plurality of points assigned to the track. The method may involve comparing track information against debounce criteria, where track information may be flagged as dynamic clutter by using a Kalman filter based algorithm on the track information. The method may include calculating a velocity of the vehicle based on the flagged track information. The method may change an operation of the vehicle in response to the calculated velocity of the vehicle.