An object recognition system of the present disclosure includes: a light source section that irradiates a subject with dot light having a predetermined pattern; an event detection sensor that receives the dot light having the predetermined pattern reflected by the subject and detects, as an event, that a change in luminance of a pixel exceeds a predetermined threshold; and a signal processor that performs, in a case where a plurality of successive pixels in a pixel array section of the event detection sensor detects occurrence of an event in a certain period, processing of removing the event as noise, the plurality of successive pixels being equal to or greater than a predetermined number of pixels.

Thermal imaging odometry and navigation systems and related techniques are provided to improve the operational flexibility of autonomous/unmanned vehicles. A thermal imaging odometry system includes a thermal imaging module configured to be coupled to an unmanned vehicle, a ranging sensor system fixed to the thermal imaging module, and a logic device. The thermal imaging module provides thermal imagery of a scene in view of the unmanned vehicle and centered about an optical axis of the thermal imaging module, where the optical axis is fixed relative to an orientation of the unmanned vehicle. The ranging sensor system provides ranging sensor data indicating a standoff distance between the thermal imaging module and a surface intersecting the optical axis of the thermal imaging module. The logic device receives thermal images of the scene and corresponding ranging sensor data and determines an estimated relative velocity of the unmanned vehicle.

Thermal imaging odometry and navigation systems and related techniques are provided to improve the operational flexibility of autonomous/unmanned vehicles. A thermal imaging odometry system includes a thermal imaging module configured to be coupled to an unmanned vehicle, a ranging sensor system fixed to the thermal imaging module, and a logic device. The thermal imaging module provides thermal imagery of a scene in view of the unmanned vehicle and centered about an optical axis of the thermal imaging module, where the optical axis is fixed relative to an orientation of the unmanned vehicle. The ranging sensor system provides ranging sensor data indicating a standoff distance between the thermal imaging module and a surface intersecting the optical axis of the thermal imaging module. The logic device receives thermal images of the scene and corresponding ranging sensor data and determines an estimated relative velocity of the unmanned vehicle.

Techniques and apparatuses are described that implement a smart-device-based radar system capable of detecting user gestures in the presence of saturation. In particular, a radar system 104 employs machine learning to compensate for distortions resulting from saturation. This enables gesture recognition to be performed while the radar system 104's receiver 304 is saturated. As such, the radar system 104 can forgo integrating an automatic gain control circuit to prevent the receiver 304 from becoming saturated. Furthermore, the radar system 104 can operate with higher gains to increasing sensitivity without adding additional antennas. By using machine learning, the radar system 104's dynamic range increases, which enables the radar system 104 to detect a variety of different types of gestures having small or large radar cross sections, and performed at various distances from the radar system 104.

Techniques and apparatuses are described that implement a smart-device-based radar system capable of detecting user gestures in the presence of saturation. In particular, a radar system 104 employs machine learning to compensate for distortions resulting from saturation. This enables gesture recognition to be performed while the radar system 104's receiver 304 is saturated. As such, the radar system 104 can forgo integrating an automatic gain control circuit to prevent the receiver 304 from becoming saturated. Furthermore, the radar system 104 can operate with higher gains to increasing sensitivity without adding additional antennas. By using machine learning, the radar system 104's dynamic range increases, which enables the radar system 104 to detect a variety of different types of gestures having small or large radar cross sections, and performed at various distances from the radar system 104.

Embodiments of an axle monitoring system of the present invention generally include an oil bath cap plug equipped with a sensor assembly containing one or more power provision components, and an oil level monitor, a humidity/temperature sensor, a vibrational energy detector, and/or a GPS tracking chip, all of which are mounted on a microcircuit board, wherein the sensor assembly is adapted and configured to be fitted inside the axle oil bath cap plug. In various embodiments, information and/or data obtained by the sensor assembly can be transmitted, in raw or processed form, to one or more remote devices. Embodiments of a method of using embodiments of an axle monitoring system of the present invention are also provided.

Embodiments of an axle monitoring system of the present invention generally include an oil bath cap plug equipped with a sensor assembly containing one or more power provision components, and an oil level monitor, a humidity/temperature sensor, a vibrational energy detector, and/or a GPS tracking chip, all of which are mounted on a microcircuit board, wherein the sensor assembly is adapted and configured to be fitted inside the axle oil bath cap plug. In various embodiments, information and/or data obtained by the sensor assembly can be transmitted, in raw or processed form, to one or more remote devices. Embodiments of a method of using embodiments of an axle monitoring system of the present invention are also provided.

A first behaviometric user profile for a first user is generated and stored, by detecting a position and velocity of the first user relative to the mobile device based on a received response from a radar transmission while the first user uses the mobile device, the received response over time indicating a position and velocity of the first user. Based on further received responses of additional radar transmissions an additional behavioral pattern of an unknown user is determined. The additional behavioral pattern is then compared to the first behaviometric user profile, and based on the comparison, a measure of similarity between the first behaviometric user profile and the additional behavioral pattern, measuring if the first user and the unknown user are a same user is heuristically determined. As a result of the comparison, operation or access to at least some data stored on the mobile device is prevented.

This application is applicable to the field of radar technologies, and provides a radar data processing method, a terminal device, and a computer-readable storage medium. The method includes: obtaining radar data collected by a receiving area array; if the radar data is saturated, performing data fusion processing based on a floodlight distance value to obtain a fusion result; and determining a distance of a target object based on the fusion result. The method can accurately obtain an actual distance of the target object, effectively reduce a measurement error, improve calculation accuracy, and resolve an existing problem of a large deviation of a measurement result when an actual echo waveform cannot be effectively restored because a signal received by the radar is over-saturated when a laser is directly irradiated on a target object with high reflectivity.

This application is applicable to the field of radar technologies, and provides a radar data processing method, a terminal device, and a computer-readable storage medium. The method includes: obtaining radar data collected by a receiving area array; if the radar data is saturated, performing data fusion processing based on a floodlight distance value to obtain a fusion result; and determining a distance of a target object based on the fusion result. The method can accurately obtain an actual distance of the target object, effectively reduce a measurement error, improve calculation accuracy, and resolve an existing problem of a large deviation of a measurement result when an actual echo waveform cannot be effectively restored because a signal received by the radar is over-saturated when a laser is directly irradiated on a target object with high reflectivity.