The invention relates to a method for object classification which comprises the following steps for providing an ellipti-cally or circularly polarized transmission signal which is transmitted to the object to be classified: generating a first radar image from the copolarly polarized reflection signal and generating a second radar image from the cross-polarized reflection signal and comparing the first radar image with the second radar image.

A base station of a vehicle includes an angle of arrival (AoA) antenna assembly and a controller. The AoA antenna assembly is positioned at a known location of the vehicle. The AoA antenna assembly includes a pair of antennas on a printed circuit board to detect an angle of arrival of a wireless signal as received by the AoA antenna assembly from a portable remote control. The wireless signal may be a Bluetooth, a Bluetooth low energy (BLE), a Wi-Fi, or an ultra-wideband (UWB) wireless signal. The remote control may be in the form of a phone or a key fob. The controller uses the detected angle and the known location of the AoA antenna assembly to locate the portable remote control relative to the vehicle. The controller may perform a passive entry passive start (PEPS) operation of the vehicle as a function of the location of the remote control.

A polarimetric radar consisting of a transmission arrangement, in which the carrier signals have a circular polarization, wherein all the transmitters of the transmission arrangement are used simultaneously and each transmitter is operated by way of a transmission signal, which is modulated by way of an individual digital phase code, a receiver arrangement, which receives the reflected signals via an antenna arrangement, wherein there are both reception antennas that are configured for left-hand circularly polarized electromagnetic waves and reception antennas that are configured for right-hand circularly polarized electromagnetic waves, wherein the use of a plurality of transmitters and receivers provides an overall arrangement, which is operated in accordance with the multiple-input multiple-output method.

A system includes at least one processor configured to detect, based on point cloud information, portions of a particular object, and determine, based on the detected portions, at least a first portion having a first reflectivity corresponding to a license plate, and at least two additional spaced-apart portions corresponding to locations on the particular object other than a location of the first portion. The at least two additional portions have reflectivity substantially lower than the first reflectivity. The at least one processor is further configured to classify the particular object as a vehicle, based on a spatial relationship and a reflectivity relationship between the first portion and the at least two additional portions.

A radar device, for example for automotive applications, comprises a radar circuit, an antenna device and a signal processing device, wherein the radar circuit is configured to transceive a first antenna signal and a second antenna signal, wherein the first antenna signal occupies a first frequency band and the second antenna signal occupies a second frequency band that is separate from the first frequency band, wherein the antenna device is configured to transduce the first antenna signal via a first antenna of the antenna device and the second antenna signal via a second antenna of the antenna device, and wherein the signal processing device comprises a ranging module that is configured to jointly process the first and second antenna signal to determine a distance to a target object irradiated by the antenna device.

A polarimetric radar system for object classification and road condition estimation includes a radar transmitter unit for transmitting radar waves of different polarizations, a radar receiving unit for receiving radar waves of different polarizations, a radar signal generating unit for generating and providing the radar waves to be transmitted, a signal processing circuitry for processing the generated and received radar waves, and a signal evaluation unit. The signal evaluation unit receives processed signals from the signal processing circuitry, estimates values for a set of predetermined object parameters on the basis of the received processed signals, and selects an object class from a plurality of predetermined object classes upon detecting a match of the estimated values with one out of a plurality of predetermined sets of object parameters. The signal evaluation unit is configured to provide information that is indicative of the at least one classified object.

A LIDAR system for use in a vehicle is provided. The LIDAR system may include at least one processor configured to control at least one light source for illuminating a field of view and scan a field of view by controlling movement of at least one deflector at which the at least one light source is directed. The at least one processor may also be configured to receive, from at least one sensor, reflections signals indicative of light reflected from an object in the field of view. The at least one processor may further be configured to detect at least one temporal distortion in the reflections signals, and determine from the at least one temporal distortion an angular orientation of at least a portion of the object.

A vehicle-assistance system for classifying objects in a vehicle's surroundings is provided. The system may include at least one memory configured to store classification information for classifying a plurality of objects and at least one processor configured to receive, on a pixel-by-pixel basis, a plurality of measurements associated with LIDAR detection results. The measurements may include at least one of: a presence indication, a surface angle, object surface physical composition, and a reflectivity level. The at least one processor may also be configured to receive, on the pixel-by-pixel basis, at least one confidence level associated with each received measurement, and access the classification information. The at least one processor may further be configured to, based on the classification information and the received measurements with the at least one associated confidence level plurality, identify a of pixels as being associated with a particular object.

A LIDAR system for detecting a vehicle may include a processor configured to: scan a field of view (FOV) by controlling movement of at least one deflector at which at least one light source is directed; receive from at least one sensor signals indicative of light reflected from a particular object in the FOV; detect, based on time of flight in the received signals, portions of the particular object in the FOV that are similarly spaced from the light source; determine, based on the detected portions, at least a first portion having a first reflectivity corresponding to a license plate, and at least two additional spaced-apart portions corresponding to locations on the particular object other than a location of the first portion; and based on a spatial relationship and a reflectivity relationship between the first portion and the at least two additional portions, classify the particular object as a vehicle.

Apparatus and associated methods relate to determining, based on a detected portion of a projected pulse of quasi-optical energy backscattered by water particles within a divergent projection volume of a cloud atmosphere, properties of the backscattering water particles. The pulse of quasi-optical energy is projected into the divergent projection volume of the cloud atmosphere. The divergent projection volume is defined by an axis of projection and an angle of projection about the axis of projection. The portion of the projected pulse of optical energy backscattered by water particles within the divergent projection volume of the cloud atmosphere is received and detected. Various properties of the backscattering water particles, which can be determined from the detected portion of the projected pulse backscattered by water particles can include particle density and/or particle size.