A system for determining distances to features in a scene is disclosed. The system includes, among other features, a target portion identifier module, a target surface generator, a reflector selection module, a light transport simulation module, a depth measurement correction generation module, and a distance calculation module. The target portion identifier module is configured to identify a plurality of target portions of the scene. The target surface generator is configured to simulate a plurality of target surfaces. The reflector selection module is configured to select a first plurality of reflector surfaces from the plurality of target surfaces and a second plurality of reflector surfaces from the first plurality of reflector surfaces. The light transport simulation module is configured to, for each target surface included in the target surfaces, simulate a multipath reflection of light emitted by the camera, reflected by the reflector surface to the target surface, and reflected by the target surface to the camera, to generate a simulated multipath response for the target surface. The depth measurement correction generation module is configured to generate a depth measurement correction for each target surface based on the simulated multipath response. The distance calculation module is configured to determine distances for the pixels based on the depth measurement corrections.

Embodiments for performing access point position determination using crowd sourcing are generally described herein. In some embodiments, a range report request is received, by at least one mobile device, from a network entity for determining a position of a plurality of access points (APs). The at least one mobile device performs range measurements on each of the plurality of APs at different locations. A range report associated with the range measurements performed on each of the plurality of APs is sent to the network entity by the at least one mobile device.

Embodiments for performing access point position determination using crowd sourcing are generally described herein. In some embodiments, a range report request is received, by at least one mobile device, from a network entity for determining a position of a plurality of access points (APs). The at least one mobile device performs range measurements on each of the plurality of APs at different locations. A range report associated with the range measurements performed on each of the plurality of APs is sent to the network entity by the at least one mobile device.

A user terminal device is disclosed. The user terminal device comprises: a communication unit for implementing communication between at least one other user terminal device and a terminal for payment; a display unit for displaying a UI screen for a payment; a user input unit for inputting information on payment means and a payment amount on the UI screen; and a processor for controlling a communication unit for receiving, from at least one other user terminal device, information on payment means and a payment amount input in the at least one other user terminal device and, on the basis of information input through the user input unit and received information, transmitting payment requests respectively corresponding to the user terminal device and the at least one other user terminal device to the terminal for payment.

Embodiments include devices and methods for navigating an unmanned autonomous vehicle (UAV) based on a measured magnetic field vector and strength of a magnetic field emanated from a charging station. A processor of the UAV may navigate to the charging station using the magnetic field vector and strength. The processor may determine whether the UAV is substantially aligned with the charging station, and the processor may maneuver the UAV to approach the charging station using the magnetic field vector and strength in response to determining that the UAV is substantially aligned with the charging station. Maneuvering the UAV to approach the charging station using the magnetic field vector and strength may involve descending to a center of the charging station. The UAV may follow a specified route to and/or away from the charging station using the magnetic field vector and strength.

The mobile, wearable, automated target tracking system is designed to enable an image and/or sound recording device, such as a video camera or directional microphone, to automatically follow a subject (or target) in order to keep that subject within the image frame or sound range that is being recorded. The automated target tracking system makes it possible to capture both the action and subject simultaneously without requiring a cameraman to manually operate the equipment. The indoor/outdoor, automated tracking system is designed to be independent of the video/sound recording device and may utilize a smartphone for location sensing and control. Both the target (or subject) and the tracking device may be moving, so the tracking device is designed to adjust position on 3 axes, azimuth (pan), elevation (tilt) and horizon (roll). Since the compact, battery-operated tracking device is mobile and wearable, it enables the user to capture the subject and all the action while also participating in the activity at the same time.

The present invention relates to a collision prevention apparatus and system for a parking lot and, more specifically, to an apparatus and system which, when a part of a car is detected within a safety distance, indicates the distance to a parking lot wall or outputs a warning so as to prevent a driver of the car from running the car into the parking lot wall. According to the present invention, the collision prevention apparatus and system for a parking lot is installed on the wall surface of a curved ramp for entering and exiting a parking lot, a pillar in the parking lot, or the like so as to prevent a car from being damaged by a collision with the wall surface of the curved ramp and the edge of the pillar due to inexperienced driving or carelessness, and assist a driver to prevent an accident and properly park his/her car by allowing the driver to accurately recognize the traveling direction of the car and the distance to the wall.

Aspects are provided which allow a UE to apply new radio high-speed train mode determination and false alarm suppression in HST deployments. The UE combines a plurality of indications associated with a high-speed train (HST) mode detection into a consolidated HST mode configuration signal. The UE determines whether to suppress the consolidated HST mode configuration signal based on a mobility metric of the UE and a plurality of thresholds. The UE transitions into a HST mode when the consolidated HST mode configuration signal is not suppressed based on the mobility metric of the UE exceeding at least one of the plurality of thresholds. As a result, false HST mode flags may be avoided and HST mode detection success rates may thereby be improved.

A speed determination system for an aircraft including one or more interfaces arranged to receive first speed data from a first speed measurement system and second speed data from a second speed measurement system. The first speed measurement system provides the first speed data using global positioning system data. The second speed measurement system provides the second speed data based on a second speed measurement. The speed determination system includes a processor arranged to determine whether the data received from the first speed measurement system is reliable. If global positioning data is determined to be reliable, the speed determination system determines a speed from the first speed data and determines correction values for the second speed measurement system. If global positioning data is determined to be unreliable, the speed determination system determines a speed from the second speed data and the correction values.

In one embodiment, a system of detecting seat belt operation in a vehicle includes at least one light source configured to emit a predetermined wavelength of light onto structures within the vehicle, wherein at least one of the structures is a passenger seat belt assembly having a pattern that reflects the predetermined wavelength at a preferred luminance. At least one 3-D time of flight camera is positioned in the vehicle to receive reflected light from the structures in the vehicle and provide images of the structures that distinguish the preferred luminance of the pattern from other structures in the vehicle. A computer processor connected to computer memory and the camera includes computer readable instructions causing the processor to reconstruct 3-D information in regard to respective images of the structures and calculate a depth measurement of the distance of the reflective pattern on the passenger seat belt assembly from the camera.