A method of identifying target-type vehicle through radar based blind spot warning (BSW) system of a host vehicle, comprising: detecting a first radar reflection point reflected by an object, said first radar reflection point being outside the BSW zone of the BSW system; setting an object area based on the distribution of groups of the first radar reflection point; assuming the object to be other vehicle based on the positional relationship between the object area and the BSW zone; detecting a second radar reflection point inside the BSW zone; and determining the other vehicle to be the target-type vehicle based on the detected second radar reflection point. The target-type vehicle is trailer or coach.

The present invention provides a system for tracking a creature body. The system includes an image capturing device, a radio frequency transceiver device, and a computing device. The image capturing device is configured to capture an image of a target creature. The radio frequency transceiver device is configured to transmit a radio signal to the target creature and receive a plurality of reflected signals from the target creature. The computing device includes an image tracking module, a creature feature value database, and a comparison module. The image tracking module is configured to track the target creature according to the captured image, and the comparison module is configured to compare the reflected signals with the creature feature value, to find out a registered identity of the target creature, so that the image tracking module keeps tracking the target creature. The present invention also provides a method for tracking a creature body.

A signal processing system according to the present disclosure includes a difference calculation unit and a determination unit. The difference calculation unit uses a sensor signal at a reference timing and a plurality of the sensor signals at a plurality of comparative timings shifted from the reference timing. The difference calculation unit generates a plurality of differential signals as respective differences between the sensor signal at the reference timing and the plurality of the sensor signals at the plurality of comparative timings and obtains respective magnitudes of the plurality of differential signals as a plurality of differential values. The determination unit obtains an evaluation value based on the plurality of differential values and determines a property of the object by using the evaluation value.

This surveillance system is provided with: a radar device which generates information indicating the reflection positions of radiated radio waves; and a surveillance device which, on the basis of the information indicating the reflection positions, detects a moving body in a radiation range of the radio waves, and determines whether an occlusion region, which is a region in the radiation range that cannot be reached by the radio waves, has arisen, and which generates surveillance information including information indicating the result of the moving body detection, and information indicating whether an occlusion region has arisen.

A light distribution control device including: an acquirer acquiring information representing a running status of an assistance operation performed for driving assistance from a driving assistance device performing driving assistance of a subject vehicle based on a recognition result of objects disposed in front of the subject vehicle recognized based on detection results acquired by a plurality of sensors including an optical sensor; and a light distribution controller performing light distribution control including change of an output level of a headlight of the subject vehicle, in which the light distribution controller gently performs change of the output level of the headlight in accordance with running of the assistance operation in the light distribution control.

The present disclosure relates to a system (100) for determining occupancy state of objects in a vehicle, the system includes a processor (106) operatively coupled to one or more sensors (102), to process the received set of signals to generate a point-cloud dataset of the received set of signals. A feature generation unit (120) extracts a set of features from the point-cloud dataset and a plurality of classifiers (122) operatively coupled to the feature generation unit to receive the extracted set of features and classify the extracted set of features by cancellation of noise signal generated from the objects within the vehicle, the classification pertaining to any or a combination of existence attributes, occupancy attributes, class attributes and position attributes of living objects to determine the occupancy state of living objects left unattended in one or more zones within the vehicle.

A distributed microwave radar imaging method includes obtaining a first echo signal received by a first microwave radar, where the first microwave radar is disposed at a first height; obtaining a second echo signal received by a second microwave radar, where the second microwave radar is disposed at a second height, and the first height is lower than the second height; determining a first radar imaging result image of a detected target based on the first echo signal; determining a second radar imaging result image of the detected target based on the second echo signal; fusing the first radar imaging result image and the second radar imaging result image to obtain a target fused image; and determining outline information of the detected target based on the target fused image.

A method for monitoring the interior of a vehicle including emitting electromagnetic waves of at least one frequency or at least one frequency band towards at least one seat arranged in the interior of the vehicle by means of an electromagnetic radiator, receiving reflected electromagnetic waves by means of a sensor, detecting a living object on the seat from the received reflected electromagnetic waves by means of a detection device, determining a volume of the detected object from the received reflected electromagnetic waves by means of the detection device, determining a weight characteristic of the detected object on the basis of the determined volume of the object by means of the detection device, outputting a detection signal representing the weight characteristic by way of the detection device, and actuating a safety system to make the interior safe in accordance with the detection signal.

Tracking aircraft in and near a ramp area is described herein. One method includes receiving camera image data of an aircraft while the aircraft is approaching or in the ramp area, receiving LIDAR/Radar sensor data of an aircraft while the aircraft is approaching or in the ramp area, merging the camera image data and the LIDAR/Radar sensor data into a merged data set, and wherein the merged data set includes at least one of: data for determining the position and orientation of the aircraft relative to the position and orientation of the ramp area, data for determining speed of the aircraft, data for determining direction of the aircraft, data for determining proximity of the aircraft to a particular object within the ramp area, and data for forming a three dimensional virtual model of at least a portion of the aircraft from the merged data.

Techniques are discussed herein for analyzing radar data to determine that radar noise from one or more target detections potentially conceals additional objects near the target detection. Determining whether an object may be concealed can be based at least in part on a radar noise level based on a target detection, as well as distributions of radar cross sections and/or doppler data associated with particular object types. For a location near a target detection, a radar system may determine estimated noise levels, and compare the estimated noise levels to radar cross section probabilities associated with object types to determine the likelihood that an object of the object type could be concealed at the location. Based on the analysis, the system may determine a vehicle trajectory or otherwise may control a vehicle based on the likelihood that an object may be concealed at the location.