A method for identifying and classifying objects in the surroundings of a motor vehicle, which method uses merely a single sensor for object detection. The method is characterized in that this single sensor moves in space while the object is being detected. In this case, during the measurement, the single sensor would act to a certain extent like a second sensor. The echo signals, reflected by the object, of different measurement cycles can be used to determine the differential speed, distance and angle. The method provides the possibility of being able to classify, by means of a single sensor, objects and items in the surroundings of a motor vehicle in terms of their size.

A vehicle generates a city-scale map. The vehicle includes one or more Lidar sensors configured to obtain point clouds at different positions, orientations, and times, one or more processors, and a memory storing instructions that, when executed by the one or more processors, cause the system to perform registering, in pairs, a subset of the point clouds based on respective surface normals of each of the point clouds; determining loop closures based on the registered subset of point clouds; determining a position and an orientation of each of the subset of the point clouds based on constraints associated with the determined loop closures; and generating a map based on the determined position and the orientation of each of the subset of the point clouds.

A method of determining an uncertainty estimate of an estimated velocity of an object includes, determining the uncertainty with respect to a first estimated coefficient and a second estimated coefficient of the velocity profile equation of the object. The first estimated coefficient being assigned to a first spatial dimension of the estimated velocity and the second estimated coefficient being assigned to a second spatial dimension of the estimated velocity. The velocity profile equation represents the estimated velocity in dependence of the first estimated coefficient and the second estimated coefficient. The method also includes determining the uncertainty with respect to an angular velocity of the object, a first coordinate of the object in the second spatial dimension, and a second coordinate of the object in the first spatial dimension.

A radar anti-spoofing system for an autonomous vehicle includes a plurality of radar sensors that generate a plurality of input detection points representing radio frequency (RF) signals reflected from objects and a controller in electronic communication with the plurality of radar sensors. The one or more controllers execute instructions to determine a signal to noise ratio (SNR) distance ratio for the input detection points generated by the plurality of radar sensors, where a value of the SNR distance ratio is indicative of an object being a ghost vehicle. The one or more controllers also determine an effective particle number indicating a degree of particle degradation for the importance sampling for each variable that is part of the state variable. In response to determining the effective particle number is equal to or less than a predetermined threshold, the one or more controllers estimate a ghost position for the ghost vehicle.

Vehicles can include systems and apparatus for performing signal processing on sensor data from radar(s) and LiDAR(s) located on the vehicles. A method includes obtaining and filtering radar point cloud data of an area in an environment in which a vehicle is operating on a road to obtain filtered radar point cloud data; obtaining a light detection and ranging point cloud data of at least some of the area, where the light detection and ranging point cloud data include information about a bounding box that surrounds an object on the road; determining a set of radar point cloud data that are associated with the bounding box that surrounds the object; and causing the vehicle to operate based on one or more characteristics of the object determined from the set of radar point cloud data.

A RADAR system and associated methods are used to detect obstacles obscured from view when backing a trailer. An autonomous tractor is equipped with a rear facing RADAR device that has a field-of-view under the trailer and is configured to output RADAR returns from reflections. A controller of the tractor classifies RADAR returns from the RADAR device according to a number of reflections by a dock wall and a trailer face (e.g., a back end of the trailer) of a corresponding RADAR beam. The RADAR returns are correlated based on distance, and distance of a RADAR return from an obstacle is corrected based on the number of reflections. Advantageously, by processing RADAR returns from both direct and reflected RADAR beams, the controller is able to detect obstacles hidden behind the trailer and flag the obstacles as a hazard.

Provided is an antenna apparatus which is capable of improving a gain in a specific direction, reducing an unnecessary gain in an angle range, and reducing its height. A radome 220 is formed such that a central portion positioned above a patch array antenna 130 is formed in different shapes in an outer wall and an inner wall. The central portion of the outer wall of the radome 220 is formed in a flat shape, and thus the height of the radome 120 is reduced. On the other hand, the center portion of the inner wall of the radome 220 is formed such that a radome thickness at a position of the radome 220 in directions in which an angle θ is about −45° and about +45° when viewed from the center of the patch array antenna 130 changes stepwise.

A vehicle security method includes: acquiring an input signal from a sensor unit equipped in a vehicle; setting a detection mode to a heart rate detection mode, in response to a security release operation being started, setting a radar sensor of the sensor unit to detect a target, and detecting heart rate information on the target; determining whether the heart rate information matches pre-stored heart rate information; setting the detection mode to a general detection mode, in response to the heart rate information matching the pre-stored heart rate information, measuring a distance, an azimuth, and/or an elevation angle between the vehicle and the target, and detecting body shape information of the target; determining whether the body shape information matches pre-stored body shape information; and releasing a security of a security device, in response to the body shape information matching the pre-stored body shape information.

A heater for vehicular sensors is configured to pass sensing energy and thereby permit placement of the heater directly over the sensing area in the path of the sensed energy. In this way, direct heating of the sensing area is provided minimizing the energy necessary to prevent icing and improving deicing speed.

A system for enhancing driver situation awareness and environment perception around a transportation vehicle. The system incorporates a plurality of object detecting sensors. The sensors are arranged for monitoring at least one critical zone around the vehicle. A plurality of addressable light-emitting diodes are operatively associated with the object detecting sensors. The addressable light-emitting diodes are located on the vehicle for visual display to the driver. When a given sensor detects an object in the critical zone, a detection signal is transmitted to a LED controller. Upon receiving the detection signal, the LED controller transmits a control signal to selectively activate only those addressable light-emitting diodes which are associated with the given sensor, such that the activated light-emitting diodes visually communicate to the driver a location of the detected object in the critical zone.