Abstract: A feature quantity extraction unit extracts at least one type of feature quantity using at least one of information associated with an instantaneous value generated by an instantaneous value generation unit and information associated with a target object member generated by a connection determination unit. A virtual image determination unit calculate a virtual image probability from a virtual image distribution and a real image probability from a real image distribution for each target object member generated by the connection determination unit using an extraction result related to the target object member of the feature quantity extraction unit. The virtual image determination unit further determines whether or not the target object member is a virtual image according to a result of integrating the calculated virtual image probability and the calculated real image probability.

Abstract: Systems and methods relating to air traffic control and navigational aids for aircraft. An antenna system uses a multi-sector sensor that uses two vertical column antenna arrays per sector. Each pair of vertical column antenna arrays produces two beams that are off a boresight for each pair of antenna arrays. Wide angle monopulse processing is used to determine an azimuth or angle of arrival for an aircraft using at least one pair of the vertical column antenna arrays. Predetermined correction factors are applied to the azimuth for specific elevation values and, for elevation values without predetermined correction factors, interpolation between known predetermined correction values to arrive at the corrector factor to be applied.

Abstract: A method and system to accurately detect a longitudinal velocity of a target by using longitudinal and lateral velocity values calculated by grouping a plurality of Doppler velocities detected from the target by a detection sensor mounted in a vehicle on the basis of the plurality of Doppler velocities.

Abstract: A method for evaluating overlapping targets in a two-dimensional radar spectrum, wherein the following steps are carried out: providing the two-dimensional radar spectrum, selecting at least one region of interest as an input signal from the spectrum, and performing an evaluation of the input signal to determine an information about the overlapping targets, wherein the evaluation is specific for a model order selection method.

Abstract: In a target tracking device, a state quantity estimation unit is configured to, every time a preset repetition period of a processing cycle elapses, estimate, for each of the one or more targets, a current state quantity based on at least either observation information of the one or more targets observed by a sensor or past state quantities of the one or more targets. A model selection unit is configured to, for each of the one or more targets, select one motion model from a plurality of predefined motion models, based on at least either states of the one or more targets or a state of the vehicle. An estimation selection unit is configured to, for each of the one or more targets, cause the state quantity estimation unit to estimate the state quantity of the target with the one motion model selected by the model selection unit.

Abstract: The embodiments of the present disclosure relate to a radar control device and method. Specifically, a radar control device according to the present disclosure may include a receiver for receiving vehicle driving information for a host vehicle from a radar, an APS determiner for determining an angular power spectrum (APS) for a predetermined frequency based on the vehicle driving information if an object is detected in the vehicle driving information, and an object determiner for determining a position of a measurement value based on the determined APS, and determine whether there are a plurality of objects based on the position of the measurement value.

Abstract: A processor-implemented radar data recognition method including generating a plurality of pieces of input data, with respectively different dimension configurations, based on radar data of an object; and outputting a recognition result of the object based on the generated plurality of pieces of input data using a recognition model.

Abstract: The present disclosure generally relates to an object detection system. For example, aspects of the present disclosure relate to systems and techniques for performing object detection using sensor information, such as elevation and/or velocity information from one or more light-based sensors. One example apparatus generally includes one or more processors operably configured to: obtain sensor information indicating at least two objects in an environment; determine at least one of a velocity or an elevation associated with each object of the at least two objects; consolidate the at least two objects into a common object based on the at least one of the velocity or the elevation; and output an indication of the common object.

Abstract: To perform high-speed recognition processing of an image signal acquired by imaging. A recognition processing system of the present disclosure includes: a first sensor device that acquires an image signal by imaging; a second sensor device that performs an object detection process, a selection unit that selects one of a plurality of recognition processes based on information on the object detected by the detection process; and a recognition processing unit that executes the recognition process selected by the selection unit based on the image signal.

Abstract: According to an aspect of the present disclosure, a collision warning apparatus of a vehicle may include an information acquisition device that obtains surrounding object information and vehicle information and a controller that generates collision prediction information of a surrounding object based on the surrounding object information and the vehicle information and provides a warning to an outside of the vehicle or generates control information for controlling braking of the vehicle while providing the warning to the outside of the vehicle based on the collision prediction information.

Abstract: A variety of methods, controllers and algorithms are described for identifying the back of a particular vehicle (e.g., a platoon partner) in a set of distance measurement scenes and/or for tracking the back of such a vehicle. The described techniques can be used in conjunction with a variety of different distance measuring technologies including radar, LIDAR, camera based distance measuring units and others. The described approaches are well suited for use in vehicle platooning and/or vehicle convoying systems including tractor-trailer truck platooning applications. In another aspect, technique are described for fusing sensor data obtained from different vehicles for use in the at least partial automatic control of a particular vehicle. The described techniques are well suited for use in conjunction with a variety of different vehicle control applications including platooning, convoying and other connected driving applications including tractor-trailer truck platooning applications.

Abstract: A feature quantity calculation unit calculates one or more predetermined types of feature quantities using information correlated to respective extracted peaks. An environment determination unit calculates a specific environment probability from a calculation result of the feature quantity calculation unit using the positive distribution and a non-specific environment probability from a calculation result of the feature quantity calculation unit using the negative distribution. The environment determination unit further determines whether the mobile body is in the specific environment or the non-specific environment in accordance with a result of integration of the specific environment probability and the non-specific environment probability which are calculated for respective feature quantities.

Abstract: A radar-enabled device that manages radar interference. In particular, the radar-enabled device detects a radar signal transmitted by a second radar-enabled device, transmits a notification of the detected radar signal, receives localization information associated with the second radar-enabled device, and sets a device location based on the received localization information. Additionally, the radar-enabled device may adjust a timing of radar signal transmissions to avoid subsequent detections of radar signals transmitted by the second radar-enabled device.

Abstract: A system for detecting human entry into a container using electromagnetic imaging to generate image maps of the container. The system includes a door monitor configured to detect an entry door open event associated with the container. The system uses one or more processors and a memory with instructions to generate a baseline image map of the container, detect an entry door open event with the door monitor associated with the container, generate a post entry door open event image map of the container, and compare the baseline image map generated before the entry door open event with image map generated after the entry door open event.

Abstract: An apparatus for assisting driving of a vehicle includes: a radar mounted on the vehicle to have a front field of view of the vehicle and configured to acquire detection data; and a controller including a processor, configured to process the detection data, and configured to identify an estimated collision time between the vehicle and a first preceding vehicle, located in front of the vehicle, based on processing of the detection data, and to control a braking system of the vehicle to brake the vehicle, in response to the estimated collision time being less than a reference time, wherein the controller is configured to increase a reference time for braking the vehicle, based on an acceleration and a travelling speed of the first preceding vehicle and an acceleration and a travelling speed of a second preceding vehicle, located in front of the first preceding vehicle.

Abstract: A radar apparatus includes a radar transmission circuit that transmits a radar signal from a transmission array antenna, and a radar reception circuit that receives, from a reception array antenna, a reflected wave signal that is the radar signal reflected at a target. One of the transmission array antenna and the reception array antenna includes a first antenna element group having m antenna elements arranged at a first interval Dt along a first axis direction, wherein m is an integer of 2 or larger. The other one of the transmission array antenna and the reception array antenna includes a second antenna element group having n antenna elements arranged at a second interval Dr along the first axis direction, wherein n is an integer of 4 or larger. The second interval Dr includes several different intervals.

Abstract: Contactless operation of a device is provided via a mobile pointing apparatus and a receiving arrangement associated with the device. The mobile pointing apparatus includes a signal emitter for emitting an optical or electromagnetic signal, and the receiving arrangement associated with the device determines a pointing target of the mobile pointing apparatus relative to the device based on the signal emitted by the mobile pointing apparatus and triggers a function of the device based on the pointing target of the mobile pointing apparatus.

Abstract: This disclosure describes, in part, techniques for implementing customized intrusion zones for security monitoring. For instance, a user may provide (e.g., via a GUI) an indication of a physical space to be monitored. An electronic device may detect one or more objects and its respective location from radar data collected by a radar sensor. The electronic device may additionally detect one or more objects within image data captured via a camera. The electronic device may then analyze the radar data and the image data in order to determine that the object detected by the radar sensor includes the same object represented by the image data. As such, the electronic device may send an alert to one or more computing devices that may include the radar data and/or the image data.

Abstract: A vehicle environment detection system in an ego vehicle, including a sensor arrangement and a main control unit is arranged to detect and track at least one oncoming vehicle, and to determine whether the ego vehicle has entered a curve. The main control unit is arranged to determine a common curve with a radius, along which common curve the ego vehicle is assumed to travel, determine a measured oncome direction of the oncoming vehicle on the common curve, corresponding to an oncome angle, determine a difference angle between the measured oncome direction and an oncome direction corresponding to if the oncoming vehicle would be moving along the common curve, compare the difference angle with a threshold angle, and to determine that the oncoming vehicle is crossing if the difference angle exceeds the threshold angle.

Abstract: A method with rear cross collision warning includes: dividing a surrounding area of a host vehicle into a plurality of cells arranged in lateral and longitudinal directions; creating a grid map on which cells, among the plurality of cells, corresponding to positions where a stationary object around the host vehicle is viewed are classified as occupied cells; determining a position of a reflective structure reflecting radar signals based on a positional relationship between the occupied cells on the grid map; and determining, based on the determined position of the reflective structure and either one of a position of a tracking target viewed by the radar and moving direction of the tracking target, whether the tracking target is a ghost tracking target.

Abstract: A radar system transmits pulses towards a target and receives pulses reflected back therefrom. Based on samples (of the received pulses) corresponding to a CPI, a first 2D matrix having a slow-time index and a fast-time index is generated. A slow-time FFT is performed to convert the slow-time index to a Doppler bin index to produce a second 2D matrix having the Doppler bin index and the fast-time index. Thereafter, a 1D interpolation is performed along the Doppler bin index to produce a third 2D matrix having a Velocity bin index and the fast-time index. Thereafter, a fast-time FFT is performed to convert the fast-time index to a Range bin index to produce a fourth 2D matrix having the Velocity bin index and a Range bin index. A distance to and a velocity of a target is determined based on the fourth 2D matrix.

Abstract: A method for dithering radar frames includes determining at least one of a chirp period Tc for radar chirps in a radar frame and a chirp slope S for radar chirps in the radar frame. In response to determining the chirp period Tc, a maximum chirp dither ?c(max) is determined, and for the radar frame N, a random chirp dither ?c(N) between negative ?c(max) and positive ?c(max) is determined. In response to determining the chirp slope S, a maximum slope dither ?(max) is determined, and for the radar frame N, a random slope dither ?(N) between negative ?(max) and positive ?(max) is determined. A radar sensor circuit generates radar chirps in the radar frame N based on the at least one of (1) the chirp period Tc and the random chirp dither ?c(N) and (2) the chirp slope S and the random slope dither ?(N).

Abstract: Disclosed is a method and a corresponding distance-measuring device for measuring a distance to an object using FMCW radar. The method includes the frequency-dependent determination of the amplitude of the radar signal, i.e. the frequency response in the output path and in the input path of the distance-measuring device. The standard windowing of the evaluation signal can be corrected using a correction factor dependent on the frequency responses. Thus the frequency dependence of the radar signal is compensated independently of device-internal or external interferences by adapting the window function. The result is more accurate and reliable distance measurement using FMCW radar. Because the distance can be determined by the disclosed method very accurately and without distortion, it is advantageous to use the distance-measuring device as a fill-level measuring device to measure the fill level of a filling material in a container.

Abstract: An aerial vehicle including a body, a first ranging device, a second ranging device and a controller is provided. The first ranging device is disposed on the body and is configured to detect a first distance between the first ranging device and the reflector. The second ranging device is disposed on the body and is configured to detect a second distance between the second ranging device and the reflector. The controller is configured to obtain an included angle between a direction of the body and the reflector according to the first distance and the second distance.

Abstract: A LIDAR-based method of determining an absolute speed of an object at a relatively longer distance from an ego vehicle, including: estimating a self speed of the ego vehicle using a first frame t?1 and a second frame t obtained from a LIDAR sensor by estimating an intervening rotation ? about a z axis and translation in orthogonal x and y directions using a deep learning algorithm over a relatively closer distance range; dividing each of the first frame t?1 and the second frame t into multiple adjacent input ranges and estimating a relative speed of the object at the relatively longer distance by subsequently processing each frame using a network, with each input range processed using a corresponding convolutional neural network; and combining the estimation of the estimating the self speed with the estimation of the estimating the relative speed to obtain an estimation of the absolute speed.

Abstract: Methods, systems, computer-readable media, and apparatuses for radar or LIDAR measurement are presented. Some configurations include transmitting, via a transceiver, a first beam having a first frequency characteristic; calculating a distance between the transceiver and a moving object based on information from at least one reflection of the first beam; transmitting, via the transceiver, a second beam having a second frequency characteristic that is different than the first frequency characteristic, wherein the second beam is directed such that an axis of the second beam intersects a ground plane; and calculating an ego-velocity of the transceiver based on information from at least one reflection of the second beam. Applications relating to road vehicular (e.g., automobile) use are described.

Abstract: The present disclosures discloses a method of target feature extraction based on millimeter-wave radar echo, which mainly solves the problems that techniques in the prior art cannot fully utilize raw radar echo information to obtain more separable features and cannot accurately distinguish targets with similar physical shapes and motion states. The method is implemented as follows: acquiring measured data of targets, generating an original RD map, and removing ground clutter of the map; sequentially performing target detection, clustering and centroid condensation on the RD map after the ground clutter removal; acquiring a continuous multi-frame RD maps and carrying out the target tracking; according to the tracking trajectory, selecting candidate areas and extracting features based on a single piece of RD map and features based on two successive RD maps, respectively.

Abstract: An object detection apparatus 1000 is provided with: a transmission unit 1101 that emits a radio wave as a transmission signal toward a target 1003 object; a reception unit 1102 that receives, through receiving antennas, radio waves reflected by the object as reception signals, and that generates, for each reception signal received by the respective receiving antennas, using the reception signals, an intermediate frequency signal; and an arithmetic device 1211 that decides sampling times so as to suppress generation of a virtual image by a beam pattern obtained by synthesizing the respective intermediate frequency signals, and generates an intermediate frequency signal for target position detection by performing sampling on the intermediate frequency signals at the decided sampling times, and detects the target using the intermediate frequency signals for position detection.

Abstract: The present invention obtains a controller and a control method capable of achieving appropriate cornering during cruise control of a straddle-type vehicle. In the controller and the control method according to the present invention, during the cruise control, in which acceleration/deceleration of the straddle-type vehicle is automatically controlled without relying on an accelerating/decelerating operation by a driver, a vehicle speed of the straddle-type vehicle is restricted to be equal to or lower than an upper limit speed at the time of turning, an exit of a curved road is detected on the basis of a predicted route of the straddle-type vehicle, and a magnitude of the deceleration of the decelerated straddle-type vehicle is reduced at a time point before the straddle-type vehicle reaches the exit.

Abstract: The present invention obtains a controller and a control method capable of achieving appropriate cornering during cruise control of a straddle-type vehicle. In the controller and the control method according to the present invention, during the cruise control, in which acceleration/deceleration of the straddle-type vehicle is automatically controlled without relying on an accelerating/decelerating operation by a driver, an entry of a curved road is detected on the basis of a predicted route of the straddle-type vehicle, and the straddle-type vehicle is decelerated at a time point before the straddle-type vehicle reaches the entry.

Abstract: Two-dimensional data obtained by performing a Fourier transform on a digitally converted FMCW radar signal at every pulse repetition interval over N pulse repetition intervals is input to a convolutional neural network (CNN) to find the probabilities of the existence of a target in range indices. The range indices, i.e., bit frequencies are selected based on the probabilities of the existence of the target. In order to reduce the size of the CNN, windowing is applied to the two-dimensional data. A speed-index-specific coefficient value may be calculated by re-performing a Fourier transform on range data for the selected bit frequencies. Thus, the range and speed of the target may be calculated.

Abstract: An object detection radar apparatus is installed in a vehicle and is configured to detect an object. The object detection radar apparatus includes a transceiver configured to transmit a radar signal to the outside of the vehicle and receive a radar signal reflected from the object; a driving environment detector configured to detect a driving environment of the vehicle based on an operation status of the vehicle; an object detector configured to detect the object based on the received radar signal; and a controller configured to determine whether or not a predetermined event occurs based on the driving environment of the vehicle or a result of the detection of the object, and control signal characteristics of the transmitted radar signal or the received radar signal when the predetermined event occurs.

Abstract: The present invention relates to a device (20) for determining a radar target list, comprising: an input interface (22) for receiving preprocessed sensor data from a radar sensor (18) with information on detected strengths at high points (H1, H2) in a distance and/or velocity dimension and in predefined neighborhood ranges of the high points in the distance and/or velocity dimension; an analysis unit (24) for determining mutually adjacent high points with overlapping neighborhood ranges based on the preprocessed sensor data; an adjustment unit (26) for adjusting the neighborhood ranges of the mutually adjacent high points; and an evaluation unit (28) for determining a radar target list with information on targets (17) in a field of view of the radar sensor based on the high points and the neighborhood ranges thereof. The present invention also relates to a method for determining a radar target list and a sensor system (10) for detecting targets (17) in an environment (12) of a vehicle (14).

Abstract: The position detecting apparatus repeatedly acquires, from a radar apparatus, object information including at least an object distance as a distance between the radar apparatus and a reflecting object and a relative speed between the radar apparatus and a reflecting object. The position detecting apparatus calculates a speed ratio as a ratio between the relative speed and the travelling speed. The position detecting apparatus calculates, based on the speed ratio, a projection distance between a projected position of the reflecting object projected onto a projection plane and a position of the radar apparatus on the projection plane, the projection plane having a predetermined angle with respect to a center axis indicating a direction along which the radar waves are transmitted by the radar apparatus and including the radar apparatus. The position detection apparatus calculates the position of the reflecting object based on the calculated projection distance.

Abstract: Techniques for Doppler correction of chirped optical range detection include obtaining a first set of ranges based on corresponding frequency differences between a return optical signal and a first chirped transmitted optical signal with an up chirp that increases frequency with time. A second set of ranges is obtained based on corresponding frequency differences between a return optical signal and a second chirped transmitted optical signal with a down chirp. A matrix of values for a cost function is determined, one value for each pair of ranges that includes one in the first set and one in the second set. A matched pair of one range in the first set and a corresponding one range in the second set is determined based on the matrix. A Doppler effect on range is determined based on combining the matched pair of ranges. A device is operated based on the Doppler effect.

Abstract: The subject disclosure relates to features for improving the modularity and interoperability of sensors and in particular, sensors deployed for use in vehicle related sensing applications. In some aspects, the disclosed technology encompasses a sensor aggregation module (e.g., sensor pod) that includes a sensor enclosure having an interior volume configured for housing one or more sensors, a data port integrated into an exterior surface of the sensor enclosure, wherein the data port is configured to be electrically coupled to a vehicle data port, and a plurality of sensor ports disposed within an interior volume of the sensor enclosure, wherein the sensor ports are configured for modular connectivity to the one or more sensors.

Abstract: Provided is a vehicle control system, a vehicle control method, and an image sensor, the vehicle control system including: an image sensor disposed on the vehicle to have a field of view of an outside of the vehicle to capture image data; at least one non-image sensor disposed on the vehicle to have a field of sensing of the outside of the vehicle to capture sensing data; at least one processor configured to process the image data captured by the image sensor and the sensing data captured by the non-image sensor; and a controller configured to determine a chance of a collision with an obstacle with respect to a rear side warning determination reference area that is changed depending on whether a trailer is mounted on the vehicle, on the basis of at least part of processing at least one of the image data and the sensing data.

Abstract: A method for detecting critical transverse movements. The method includes the following steps: emitting a CW radar signal and generating radar data based on the received reflected CW radar signal with the aid of a radar device; ascertaining collision-relevant spectral ranges of the radar data as a function of an ego velocity of the radar device; ascertaining a time dependency of a relative velocity and of an object angle of an object by evaluating the radar data in the ascertained spectral ranges; and detecting a critical transverse movement of the object using the time dependency of the relative velocity and of the object angle of the object.

Abstract: The present invention provides a method for calculating a swing trajectory of a golf club using radar sensing data capable of calculating a swing trajectory of a golf club therefrom, a radar sensing device using the same, and a recording medium readable by a computing device recording the calculation method, which calculates the position coordinate information of the golf club through the analysis of the radar signal separately from calculating the motion parameters for the ball through the analysis of the radar signal when the golfer hits the ball with the golf club, and effectively calculate the swing trajectory of the golf club from the calculated position coordinate information of the golf club.

Abstract: For example, an apparatus may include a radar antenna including at least one Transmit (Tx) antenna to transmit a Tx radar signal; and a plurality of Receive (Rx) antennas to receive Rx radar signals based on the Tx radar signal, wherein a distance between a first Rx antenna of the planarity of Rx antennas and a second Rx antenna of the plurality of Rx antennas, which is adjacent to the first Rx antenna, is at least ten times a wavelength of a central frequency of the Tx radar signal.

Abstract: Techniques and apparatuses are described that implement height-estimation of objects using radar. In particular, a radar system, which is mounted to a moving platform, receives reflection signals that represent versions of a radar signal that are reflected off of objects. The radar system generates a range-elevation map based on raw data from the reflection signals, identifies an elevation bin and a range bin in the range-elevation map that corresponds to a selected object, and calculates a height for the selected object based on the range and elevation bins. The radar system then calculates a de-noised height for the selected object based on one or more previously calculated heights for the selected object. In this way, the radar system can determine accurate heights of objects at sufficiently long ranges for evasive action.

Abstract: A method including detecting an object within a field of view of a radar using a radar signal; tracking movement of the object through the field of view of the radar; triggering a camera to capture a plurality of images of the object based on the movement of the object; detecting the object in the plurality of images; combining data of the radar signal with data of the camera to estimate a position of the object; identifying a radar signal track generated by the motion of the object based on the combined data; and estimating a trajectory of the object based on identifying the radar signal track.

Abstract: A configuration to configure a first wireless device to detect clutter echo in order to improve a configuration for SIM. The apparatus receives a SIM configuration having one or more parameters specific to clutter echo detection. The apparatus performs SIM for the clutter echo detection based on the SIM configuration. The apparatus reports one or more beams having a largest self-interference RSRP due to clutter echo.

Abstract: Techniques for determining a location of a client device using recursive phase vector subspace estimation are described. One technique includes receiving a plurality of angle-of-arrival (AoA) measurements from a plurality of access points (APs). Each AoA measurement includes a plurality of entries for phase values measured from a signal received from a client device at the plurality of APs. At least one AoA measurement of the plurality of AoA measurements that includes at least one of: (i) one or more entries with missing phase values and (ii) one or more entries with erroneous phase values is identified, based on a recursive phase estimation. The plurality of AoA measurements are updated based on the identified at least one AoA measurement. The location of the client device is determined, based on the updated plurality of AoA measurements.

Abstract: An object detector includes: a triangulation calculation unit that performs triangulation calculation for detecting a location of an object based on first distance information calculated based on direct waves in which transmitted waves transmitted from a first transmission and reception unit are reflected by an object and received by the first transmission and reception unit, and second distance information calculated based on indirect waves in which transmitted waves transmitted from a second transmission and reception unit arranged in a location different from the first transmission and reception unit are reflected by an object and received by the first transmission and reception unit; and a prohibition processing unit that prohibits triangulation calculation when a difference between first velocity information indicating a velocity of an object calculated based on the direct waves and second velocity information indicating a velocity of an object calculated based on the indirect waves exceeds a predetermin

Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with sensor output segmentation are provided. For example, sensor data can be accessed. The sensor data can include sensor data returns representative of an environment detected by a sensor across the sensor's field of view. Each sensor data return can be associated with a respective bin of a plurality of bins corresponding to the field of view of the sensor. Each bin can correspond to a different portion of the sensor's field of view. Channels can be generated for each of the plurality of bins and can include data indicative of a range and an azimuth associated with a sensor data return associated with each bin. Furthermore, a semantic segment of a portion of the sensor data can be generated by inputting the channels for each bin into a machine-learned segmentation model trained to generate an output including the semantic segment.

Abstract: Systems and methods for operating radar systems. The methods comprise, by a processor: receiving point cloud information generated by at least one radar device; generating a radar track initializer using the point cloud information; determining whether the radar track initializer includes false information; generating a radar track for a detected object when a determination is made that the radar track initializer does not include false information; and/or using the radar track to control operations of a vehicle.

Abstract: A LIDAR device for measuring a distance to an object in a scanning zone includes a light source, a light receiver, a rotatable mirror, a motor, an angle sensor, and a controller. The rotatable mirror is configured to reflect the light beam emitted from the light source toward the scanning zone. The motor is configured to rotate the mirror back and forth between a first position and a second position. The angle sensor is configured to detect a rotation angle of the mirror and to output a detection signal indicative of the rotation angle of the mirror at a plurality of predetermined angle intervals during each rotation cycle between the first position and the second position of the mirror. The controller is configured to output a control signal to the light source to emit a light beam upon receiving the detection signal from the angle sensor.

Abstract: A simulation method for predicting a false positive for a predefined region outside a desired field of view of a radar sensor. Calculated primary rays having a respective primary energy level represent the radar signal. Reflected rays are calculated based on the primary rays or other reflected rays and based on geometrical data for at least one item within the predefined region. An energy level is determined for each reflected ray based on an estimated reflectivity of the at least one item and based on the primary energy level of the respective primary ray, and a clustering level for the reflected rays is determined based on distances of the respective reflection points. A probability for an occurrence of a false positive is estimated based on the energy level and the clustering level.

Abstract: A vehicle safety system performs close-in incipient collision detection that combines high sample rate near-field sensors with advanced real-time processing to accurately determine imminent threats and the likelihood of a collision before a collision occurs. This allows applicable countermeasures to be deployed based upon the probability of a collision, while also taking into account the type of threat and the impending impact's location on the vehicle. This radically new approach will soon transform the passive safety market to greatly reduce injuries from automotive crashes and save lives.