Denso Corporation

So-ken Corporation

Yusuke Akamine

Yasuyuki Miyake

Katsuhiko Kondo

Takuya Takayama

Mitsuyasu Matsuura

Naoki Kawasaki

Tomohiko Tsuruta

Takayuki Kitamura

Shunsuke Suzuki

Akiyoshi Mizutani

Mai Sakamoto

A radar apparatus, mounted to a vehicle, includes: a transmitting unit that transmits a transmission signal at a set repetition cycle; and a receiving unit that receives a reflection signal reflected by at least one object. The radar apparatus calculates a velocity residual of each of at least one target object, which is a difference between a velocity prediction value and a velocity measurement value. Based on a magnitude of variation in the velocity residual in time series of each of at least one target object, the radar apparatus calculates an evaluation value of each of at least one target object, which corresponds to a probability of each of at least one target object being a folding ghost. Based on the evaluation value of each of at least one target object, the radar apparatus determines whether each of at least one target object is a folding ghost.

Radar apparatus

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.

Target tracking device

An object tracking apparatus acquires detection information from a sensor mounted to a moving body, detects an object, and calculates a distance, a relative velocity, and an orientation thereof. For the initially detected object, the apparatus calculates aliased velocities of which aliasing from the relative velocity is assumed, and generates target candidates corresponding to the aliased velocities. For each target candidate, the apparatus estimates a current state of the target candidate from a past state thereof and observation information, and selects the target candidate estimated to be a true target from the target candidates for the same object. The apparatus calculates, as a reference velocity, an aliased velocity of the relative velocity that is equal to or greater than a velocity lower-limit value and is most negative or smallest in magnitude. The apparatus calculates the aliased velocities being the reference velocity aliased 0 to n times in a positive direction.

Object tracking apparatus

An object tracking device according to one aspect of the present disclosure includes a detection unit, a prediction unit, a first region setting unit, an estimation unit, a registration unit, a prohibition region setting unit, and a registration prohibition unit. The registration prohibition unit prohibits observed values of at least one observed value detected by the detection unit and that are within a prohibition region set by the prohibition region setting unit from being registered as new targets by the registration unit.

Object tracking device

An object tracking apparatus generates a plurality of target candidates in which ambiguity in velocity is assumed for an object detected for a first time, calculates a current prediction value of a state quantity of each target candidate from a past estimation value of the state quantity of each target candidate, using one filter among a plurality of filters, and calculates the current estimation value of the state quantity of the target candidate from each of the calculated prediction values and a current observation value that matches each prediction value. The object tracking apparatus deletes the target candidate of which a determined likelihood is less than a preset threshold among the target candidates, and switches a used filter to a filter that has a larger number of state variables among the filters, in response to the target candidate being deleted and the total number of target candidates decreasing.

In an object tracking device, a candidate generator is configured to, given P=Kmax−Kmin+1 that defines a range of foldings of velocity by phase rotation from Kminto Kmaxfoldings, calculate P velocity estimates for each of initial observation points. The candidate generator sets the number of foldings Kmin and the number of foldings Kmax such that Kmin<0 and |Kmin|>|Kmax| when an absolute value of an observation angle representing a direction of the observation point is equal to or less than a first threshold value, and Kmax>0 and |Kmin|<|Kmax| when the absolute value of the observation angle is greater than a second threshold. A velocity determiner is configured to, for each set of candidate targets, select one of the candidate targets belonging to the set of candidate targets, thereby determining the velocity of a target associated with the initial observation point.

An intersecting road estimation device includes an object detection unit that detects an object existing around an own vehicle and a position of the object, an object extraction unit that extracts a stationary object and a position of the stationary object from an object detection result, a first estimation unit that estimates a road edge of a traveling road on which the own vehicle is traveling based on the position of the stationary object, a candidate extraction unit that extracts a stationary object existing outside the road edge of the traveling road estimated by the first estimation unit as a candidate for an outside stationary object representing a road edge of an intersecting road intersecting the traveling road, and a second estimation unit that estimates the road edge of the intersecting road based on a position of the outside stationary object extracted by the candidate extraction unit.

Intersecting road estimation device

A vehicle radar system includes at least one radar, a detection section, an extraction section, a pair determination section, and a target position determination section. The extraction section extracts at least one observation point pair from a plurality of detected observation points. The observation point pair is a pair of the observation points located in the same direction. The target position determination section calculates a surface direction of a reflection surface from a reflection surface observation point of the observation point pair and observation points around the reflection surface observation point, and determines a position of the target from the calculated surface direction and the at least one observation point pair.

Vehicle radar system

A radar system is provided with a plurality of radar units. Each radar unit includes a first processing unit for calculating a distance and a relative speed to an object in the vicinity of each radar unit in accordance with a beat signal, a frequency band of the first modulated waves being a first frequency band, and a modulation period of the first modulated waves being a first modulation period; a second processing unit for calculating a distance to the object in accordance with a beat signal, a frequency band of the second modulated waves being a second frequency band, and a modulation period of the second modulated waves being a second modulation period; and a calculation result determination unit for determining the distance and the relative speed to the object in accordance with calculation results of the first and second processing units.

Radar system suppressing interference between a plurality of radar units

A moving object recognition apparatus includes an object detection section, a position detection section, a road direction estimation section, and a moving direction estimation section. The object detection section detects a moving object that moves on a road around an own vehicle and a roadside object by the road, from objects present around the own vehicle. The position detection section detects positions of the moving object and the roadside object detected by the object detection section. The road direction estimation section estimates a road direction of the road on which the moving object is moving, based on the position of the roadside object detected by the position detection section. The moving direction estimation section estimates a moving direction of the moving object based on the road direction estimated by the road direction estimation section.

Stationary and moving object recognition apparatus

A radar apparatus is mountable to a vehicle. The radar apparatus includes an observing unit, an estimating unit, a predicting unit, a matching processing unit, and a determining unit. The estimating unit calculates, regarding an initial detection target object, a plurality of velocity estimation values in which folding is presumed, using a velocity observation value calculated by the observing unit. The predicting unit calculates a prediction value from each of the plurality of velocity estimation values. The matching processing unit performs association of the velocity prediction value and the velocity observation value.

An object detection apparatus detects a target object present in a periphery of a moving body. The object detection apparatus derives recognition information indicating a state of a target object, and predicts a state of the target object at a next second observation timing, based on the recognition information derived at a first observation timing. The object detection apparatus derives a score based on a degree of difference between a state of the target object observed at the second observation timing and a next state of the target object predicted at the first observation timing. The object detection apparatus derives a reliability level by statistically processing scores related to the target object derived at a plurality of observation timings from past to present. In response to the reliability level satisfying a predetermined reference, the object detection apparatus determines that the target object related to the reliability level is actually present.

Object detection apparatus based on scoring reliability and increasing relative range rate

A driving support apparatus supports driving of the vehicle. The driving support apparatus includes a brake pedal detection unit, a retraction speed calculation unit and a driving operation device setting unit. The brake pedal detection unit detects an operation amount of the brake pedal. The retraction speed calculation unit calculates a retraction speed of the brake pedal, based on the operation amount of the brake pedal detected by the brake pedal detection unit. The driving operation device setting unit sets a reaction force exerted by a driving operation device to a larger value as the retraction speed calculated by the retraction speed calculation unit becomes higher.

Driving support apparatus

The radar device is provided with a transmission array antenna, phase shifters, a reception array antenna, a transmission control unit and a signal processing unit. The transmission control unit transmits transmission waves in either a directivity control mode or a MIMO mode. The directivity control mode controls directivity of the transmission array antenna by controlling the phase shifters. The MIMO mode transmits transmission waves so as not to interfere with each other from the selected at least two transmission antenna elements.

Radar device

A vehicle information providing apparatus repeatedly acquires observation point information. The apparatus calculates at least one position of the predicted point. When the observation point information is acquired, the apparatus extracts a predicted point that can be connected to the observation point from the calculated predicted points. The apparatus calculates the position of the current filtered point based on the position of the current observation point and the position of the latest predicted point. When the observation point information of a new object (an object having no latest predicted point connectable to the observation point) is acquired, the device sets initial vectors. The apparatus calculates the position of the predicted point at time instants succeeding the current time instant for each of the traveling directions indicated by the initial vectors.

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Nisshin, Japan

Yusuke Akamine