Abstract: A detection device includes processing circuitry configured to acquire sensor information from at least one sensor; the at least one sensor configured to be disposed on at least one of balustrades erected on both right and left sides with respect to a moving direction of steps of at least one passenger conveyor, each of the balustrades including a plurality of side plates; determine whether or not the detection target is a designated target to be warned on a basis of the acquired sensor information; and display a warning image indicating the designated target on a display device in a case where the processing circuitry determines that the detection target is the designated target.

Abstract: A ceramic electronic device includes a multilayer structure having a substantially rectangular parallelepiped shape, a first cover layer, and a second cover layer that is provided on a second end of the multilayer structure in the stacking direction, a main component of the second cover layer being ceramic, a porosity of the second cover layer being higher than that of the first cover layer. Q=(A+B)/2C×100(%) is 0.5% or more and 1.6% or less, when, at an interface of the second cover layer on a side of the first cover layer, two heights of curvature portions of both ends of the interface are respectively a height A and a height B, and a shortest height from the first cover layer to the second cover layer is a height C.

Abstract: A laser radar device according to the present disclosure technology includes a signal processing unit, in which the signal processing unit includes a wind field calculating unit, a blind region extracting unit, and a learning algorithm unit, the wind field calculating unit obtains a Doppler frequency from a peak position of a spectrum at each of observation points and calculates a wind velocity, the blind region extracting unit extracts a blind region on the basis of a geometrical relationship including a laser irradiation direction and disposition of a structure, and the learning algorithm unit includes a learned artificial intelligence, and estimates a wind velocity value in the blind region.

Abstract: A laser radar device according to the technique of the present disclosure is a laser radar device that scans a laser beam and measures a wind speed field of observation environment, and includes a signal processor including a spectrum conversion processor, an integration processor, a wind speed field calculator, and a algorithm learning AI, and in which the spectrum conversion processor performs FFT processing on a beat signal that is a time-series digital signal, and generates spectrum data, the integration processor performs integration processing on the spectrum data, the wind speed field calculator calculates the wind speed field by referring to information on data processed by the integration processor, the algorithm learning AI includes a trained artificial intelligence, and interpolates an observation result by referring to information on the wind speed field.

Abstract: A wind speed prediction device includes processing circuitry configured to acquire a scattering signal that is each of a plurality of beams after being emitted to space and scattered in the space; variably set a range bin width as distance resolution of each of the acquired scattering signals in accordance with an elevation angle of each of the beams emitted to the space, and calculate at least one Doppler frequency of at least one range bin corresponding to a two-dimensional plane including an observation region from the each of the scattering signals; estimate at least one wind speed distribution in the two-dimensional plane from the plurality of Doppler frequencies calculated; and predict a wind speed in the observation region from the at least one wind speed distribution in the two-dimensional plane using a two-dimensional Navier-Stokes equation.

Abstract: The radar device includes a transmission section, a reception antenna section, a reception section, a frequency analysis section, a first correlation matrix generation section, and an averaging process section. The transmission section transmits a chirp at cycle periods, the number of the transmitted chirps being a repetition number. The first correlation matrix generation section generates, for the chirps, first correlation matrixes based on complex information on long-distance bins in distance spectra corresponding to respective reception antennas that have received the identical chirp. The averaging process section performs, for the respective long-distance bins, an averaging process for the repetition number of first correlation matrixes generated so as to correspond to the long-distance bins, to generate average correlation matrixes.

Abstract: 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.

Abstract: A driving assistance device includes an object detection unit, an acquisition unit acquiring a first value of a relative speed of an approaching object with respect to an own vehicle, a ghost determination unit, and an assistance determination unit. The ghost determination unit calculates a second value of the relative speed of the approaching object in accordance with a speed of the own vehicle and a value of the relative speed of a following object located between the own vehicle and the approaching object; calculates, as a speed difference, an absolute difference between the first value of the relative speed and the second value of the relative speed; calculates, as an azimuth difference, an absolute difference between an azimuth of the following object and an azimuth of the approaching object; and determines whether the approaching object is the ghost target based on the speed difference and the azimuth difference.

Abstract: Disclosed is a physique estimation device that can estimate a physique. The physique estimation device includes: a sensor having a transmission antenna to transmit a transmission wave, and a reception antenna to receive the transmission wave reflected by at least one target in a vehicle cabin as a received wave; a frequency analysis unit to acquire position information about a reflection point where the transmission wave is reflected using the received wave; and a physique estimation unit to estimate the physique of a non-static object present in the vehicle cabin using the position information.

Abstract: An object detection device includes processing circuitry configured to acquire wave data; acquire the moving velocity of a radar device; estimate a relative distance between the radar device and a target, angle of incidence of a reflection signal from the target, and a first relative velocity between the radar device and the target, by using the wave data; and estimate a second relative velocity between the radar device and the target in a case where the target is a static object, on the basis of the acquired moving velocity and the relative distance and the angle of incidence, and determine whether the target is a static object by comparing the first relative velocity and the second relative velocity.

Abstract: A radar device includes: a control unit to cause a series of processing to be repeatedly executed, the series of processing including transmitting transmission signals to space using transmission antennas arranged linearly, receiving reflected signals that are the transmission signals reflected in the space using reception antennas linearly arranged in the same direction as the transmission antennas, transmitting the transmission signals simultaneously from the transmission antennas, receiving the reflected signals by the reception antennas, and acquiring digital data; and a signal processing unit to generate a three-dimensional radar image of a target moved in a direction crossing an antenna arrangement direction of the transmission antennas and the reception antennas by using the digital data sequentially acquired in the series of processing repeatedly executed as two-dimensional array data.

Abstract: A transmission antenna unit includes transmission antennas arranged in a row along a predetermined array direction at a predetermined first interval. A reception antenna unit includes reception antennas arranged in a row along the array direction at a second interval set to differ from the first interval. The transmission antennas and the reception antennas form a virtual array in which virtual reception antennas are arranged in a row along the array direction. The first interval is equal to a multiplication value of a minimum interval being a minimum value of an arrangement interval of the virtual reception antennas and a first multiple being an integer of 2 or greater. The second interval is equal to a multiplication value of the minimum interval and a second multiple being an integer of 2 or greater and set to differ from the first multiple. The first and second multiples are coprime.

Abstract: A radar signal processing device includes: a frequency analysis unit performing frequency analysis on a reception signal of at least one reception channel generated by a sensor unit; a target object discriminating unit calculating, on the basis of the frequency analysis, a measurement value of at least one type of feature amounts that characterizes a state of a target object moving in an observation space; and a learned data storing unit storing at least one learned data set that defines a probability distribution in which the at least one types of feature amounts is measured when a recognition targets is observed in the observation space. The target object discriminating unit calculates a posterior probability that a target object belongs to each of class(es) from the measurement value using a learned data set and discriminates the target object on the basis of the calculated posterior probability.

Abstract: An other lane monitoring device of the present disclosure includes an other vehicle acquisition section, a path acquisition section, a lane estimation section, and a position estimation section. The other vehicle acquisition section is configured to acquire other vehicle position information that indicates the current position of an other vehicle near the own vehicle. The path acquisition section is configured to acquire an own vehicle travel path that indicates a path along which the own vehicle has traveled. The lane estimation section is configured to use the own vehicle travel path as a basis for estimating an other lane area that is a lane where the other lane is present. The position estimation section is configured to estimate a future position of the other vehicle, assuming that the other vehicle moves along the own vehicle travel path or in the other lane area.

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: A target detection device includes an analysis section, a direction estimating section, a received waveform forming section, and a distance calculating section. The received waveform forming section forms a received waveform for each of the frequencies of the continuous waves by weighting beat signals corresponding to received waves received by each of receiving antennas, so as to have directivity in one of arrival directions estimated by the direction estimating section.

Abstract: A transmission antenna unit includes a plurality of transmission antennas, a reception antenna unit, and a processor. The plurality of transmission antennas that are arranged in a row along a predetermined array direction. The reception antenna unit includes a plurality of reception antennas that are arranged in a row along the array direction. The plurality of transmission antennas and the plurality of reception antennas form a virtual array in which a plurality of virtual reception antennas are arranged in a row along the array direction. The processor corrects a plurality of virtual reception signals by multiplying a virtual reception signal matrix by an inverse matrix of a reception mutual coupling matrix and an inverse matrix of a transmission mutual coupling matrix.

Abstract: A driving assistance device includes an object detection unit, an acquisition unit acquiring a first value of a relative speed of an approaching object with respect to an own vehicle, a ghost determination unit, and an assistance determination unit. The ghost determination unit calculates a second value of the relative speed of the approaching object in accordance with a speed of the own vehicle and a value of the relative speed of a following object located between the own vehicle and the approaching object; calculates, as a speed difference, an absolute difference between the first value of the relative speed and the second value of the relative speed; calculates, as an azimuth difference, an absolute difference between an azimuth of the following object and an azimuth of the approaching object; and determines whether the approaching object is the ghost target based on the speed difference and the azimuth difference.

Abstract: In an azimuth estimation device, a center generation unit configured to generate, for each peak bin extracted by the extraction unit, a center matrix which is a correlation matrix obtained using values of the same peak bin collected from all of transmitting/receiving channels. A surrounding generation unit is configured to generate, for each of one or more surrounding bins of each of the peak bins, a surrounding matrix which is a correlation matrix obtained using values of the same surrounding bin collected from all of the transmitting/receiving channels. An integration unit is configured to generate, for each peak bin, an integrated matrix which is a correlation matrix obtained by weighting and adding the center matrix and the one or more surrounding matrices. An estimation unit is configured to execute an azimuth estimation calculation using the integrated matrix generated by the integration unit.

Abstract: The radar device includes a transmission section, a reception antenna section, a reception section, a frequency analysis section, a first correlation matrix generation section, and an averaging process section. The transmission section transmits a chirp at cycle periods, the number of the transmitted chirps being a repetition number. The first correlation matrix generation section generates, for the chirps, first correlation matrixes based on complex information on long-distance bins in distance spectra corresponding to respective reception antennas that have received the identical chirp. The averaging process section performs, for the respective long-distance bins, an averaging process for the repetition number of first correlation matrixes generated so as to correspond to the long-distance bins, to generate average correlation matrixes.