Patent classifications
G01S15/12
Object detection apparatus
An object detection apparatus includes distance measuring devices and a hardware processor. The distance measuring devices are provided in a vehicle and emit ultrasonic waves. The distance measuring devices detect an object around the vehicle and obtain distance information indicating a distance to the detected object. The hardware processor determines a scene in which the vehicle is placed. The determination is performed on the basis of the distance information, vehicle speed information, an image of surroundings of the vehicle, and/or a location of the vehicle on a map. The hardware processor performs, on the basis of a scene determination result, setting of a high-sensitivity area where sensitivity for detecting the reflected waves is temporarily increased, a change of an emission interval of the ultrasonic waves, and/or a change of an emission sequence of the ultrasonic waves.
Object detection apparatus
An object detection apparatus includes distance measuring devices and a hardware processor. The distance measuring devices are provided in a vehicle and emit ultrasonic waves. The distance measuring devices detect an object around the vehicle and obtain distance information indicating a distance to the detected object. The hardware processor determines a scene in which the vehicle is placed. The determination is performed on the basis of the distance information, vehicle speed information, an image of surroundings of the vehicle, and/or a location of the vehicle on a map. The hardware processor performs, on the basis of a scene determination result, setting of a high-sensitivity area where sensitivity for detecting the reflected waves is temporarily increased, a change of an emission interval of the ultrasonic waves, and/or a change of an emission sequence of the ultrasonic waves.
Data readout via reflected ultrasound signals
A system and method are provided. The system includes a data reader having a processor for performing a signal frequency analysis, an ultrasound transmitter for transmitting ultrasound signals, and an ultrasound receiver for receiving reflected ultrasound signals. The system further includes a movable reflector for receiving the ultrasound signals and reflecting the ultrasounds signals back to the ultrasound receiver (a) as the reflected ultrasound signals without modulation when the movable reflector is stationary and (b) as the reflected ultrasound signals with modulation when the movable reflector is mobile. The system also includes a chip for storing a specification of motion states for the movable reflector.
Data readout via reflected ultrasound signals
A system and method are provided. The system includes a data reader having a processor for performing a signal frequency analysis, an ultrasound transmitter for transmitting ultrasound signals, and an ultrasound receiver for receiving reflected ultrasound signals. The system further includes a movable reflector for receiving the ultrasound signals and reflecting the ultrasounds signals back to the receiver (a) as the reflected ultrasound signals without modulation when the reflector is stationary and (b) as the reflected ultrasound signals with modulation when the reflector is mobile. The system also includes a chip for storing a specification of motion states for the reflector. The processor performs the signal frequency analysis to detect a presence or an absence of modulated frequency components in a received ultrasound signal and outputs a first value or a second value respectively depending upon whether the presence or the absence of the modulated frequency components is detected.
Fluid flow analysis
A method of determining a measure of wave speed intensity in a fluid conduit uses ultrasound measurements to determine the conduit diameter, as a function of time, at a longitudinal position of the conduit, and to determine a measure of fluid velocity, as a function of time, in a volume element at said longitudinal position of the conduit. The ultrasound measurement to determine the measure of fluid velocity is effected by decorrelation of scattering objects within the fluid flow in successive frames sampling the volume element. A wave speed may be determined from a ratio of the change in fluid velocity at the longitudinal position as a function of time and the change in a logarithmic function of the conduit diameter as a function of time. A measure of wave intensity may be determined as a function of change in determined conduit diameter and corresponding change in fluid velocity.
Fluid flow analysis
A method of determining a measure of wave speed intensity in a fluid conduit uses ultrasound measurements to determine the conduit diameter, as a function of time, at a longitudinal position of the conduit, and to determine a measure of fluid velocity, as a function of time, in a volume element at said longitudinal position of the conduit. The ultrasound measurement to determine the measure of fluid velocity is effected by decorrelation of scattering objects within the fluid flow in successive frames sampling the volume element. A wave speed may be determined from a ratio of the change in fluid velocity at the longitudinal position as a function of time and the change in a logarithmic function of the conduit diameter as a function of time. A measure of wave intensity may be determined as a function of change in determined conduit diameter and corresponding change in fluid velocity.
Robust touch sensing via ultra-sonic sensors
A method of sensing touch on a touch surface of a touch structure includes: transmitting, from within an enclosed interior volume, an ultra-sonic transmit signal towards an inner surface of the touch structure that is arranged counter to the touch surface; receiving, from within the enclosed interior volume, an ultra-sonic reflected signal produced from the ultra-sonic transmit signal being reflected by the inner surface; acquiring a plurality of digital samples from the ultra-sonic reflected signal; calculating an Euclidean distance of the plurality of digital samples to a first plurality of reference samples; and determining whether a no-touch event or a touch event has occurred at the touch surface based on the Euclidean distance.
DISTANCE MEASURING SYSTEM AND METHOD USING PHYSICALLY OFFSET TRANSDUCERS
A system and method measure distances using physically offset transducers. The system includes first and second transducers physically offset by a predetermined offset distance for generating time-of-flight values of sonic pulses from the transducers to an object. A processor determines a speed of sound in a medium from the time-of-flight values and the offset distance, and determines a distance of at least one of the transducers from the object using the speed of sound and a corresponding time-of-flight value. A controller generates a control signal from the determined distance to control movement of a mobile device. A method implements the system.
DISTANCE MEASURING SYSTEM AND METHOD USING PHYSICALLY OFFSET TRANSDUCERS
A system and method measure distances using physically offset transducers. The system includes first and second transducers physically offset by a predetermined offset distance for generating time-of-flight values of sonic pulses from the transducers to an object. A processor determines a speed of sound in a medium from the time-of-flight values and the offset distance, and determines a distance of at least one of the transducers from the object using the speed of sound and a corresponding time-of-flight value. A controller generates a control signal from the determined distance to control movement of a mobile device. A method implements the system.
PROXIMITY AND LIVENESS DETECTION USING AN ULTRASONIC TRANSCEIVER
Devices and methods are provided that facilitate proximity or liveness detection of a user of a wearable device or a user interacting with a device based on ultrasonic information. In various embodiments, machine learning classifier models can be employed to generate classification predictions of a donned or a doffed state of a wearable device. In various aspects, a gated-recurrent unit (GRU) recursive neural network (RNN) can be employed as a machine learning classifier model. In other aspects, a liveness detection classifier decision tree can be employed as a machine learning classifier model. Power states or operating modes for associated devices can be selected based on the proximity or liveness of the user of the wearable device, as an example.