A weather radar module includes a memory, a vertical weather display, and a processor. The vertical weather display is configured to display weather in a vertical format. The processor is configured to control a radar antenna of the aircraft to perform a sweep in the horizontal direction and receive horizontal sweep radar returns, determine first weather parameters of a weather model in the vertical format based on the horizontal sweep radar returns, and store the first weather parameters in the memory. The processor is further configured to provide an estimate of the weather in the vertical format based on fusing vertical weather data, which is based on the vertical sweep radar returns, with the first weather parameters in the memory or with vertical display data based on the first weather parameters, and cause the vertical weather display to display the estimate of the weather in the vertical format.

A bicycle radar system including a camera is disclosed. The system may include a radar unit and a mobile electronic device that are in communication with one another. The radar unit may transmit radar signals, receive return signals (reflections), and process the returned radar signals to determine a location and velocity of one or more targets located in a sensor field behind a user's bicycle. The mobile electronic device may include a communication component configured to wirelessly receive content including cartographic data and one or more high-risk geographic areas and a processor configured to determine a threat level based on the targets, the high-risk geographic area and a determined geographic position.

This disclosure relates to systems and methods for spatial and temporal concealed object detection. In a particular system, there is included at least one mm-wave sensor configured to sense parameters indicative of an object, a processor, and a memory. The memory includes stored thereon instructions which, when executed by the processor, cause the system to capture a mm-wave image, by the at least one mm-wave sensor, the mm-wave image including the object, and perform spatial and temporal object detection of the object on the mm-wave image.

This disclosure relates to systems and methods for spatial and temporal concealed object detection. In a particular system, there is included at least one mm-wave sensor configured to sense parameters indicative of an object, a processor, and a memory. The memory includes stored thereon instructions which, when executed by the processor, cause the system to capture a mm-wave image, by the at least one mm-wave sensor, the mm-wave image including the object, and perform spatial and temporal object detection of the object on the mm-wave image.

In a mobile part having at least one module, and a method for operating a mobile part, the mobile part is able to be moved on a driving surface, and the module includes a controllable illumination device. The illumination device is provided and/or situated in elongated form along a planar curve, in particular, a line.

Radar systems and methods for imaging surfaces. A processor receives raw data from the radar and executes an image data generation. A display unit displays an image representing the targeted surface. The radar unit may be incorporated in a handheld scanner. Rectangular antenna arrays may be configured and processors may be operable such that the image data generated may be processed and displayed in real time.

A radar detection and identification device is disclosed, comprising at least one display host, at least one camera and at least one radar detector, wherein the camera and the radar detector, after photographing and detecting, are capable of performing masked face recognition and radar physiological detection recognition processes in order to identify the identity information and human physiological signals and display them on the display host.

A radar detection and identification device is disclosed, comprising at least one display host, at least one camera and at least one radar detector, wherein the camera and the radar detector, after photographing and detecting, are capable of performing masked face recognition and radar physiological detection recognition processes in order to identify the identity information and human physiological signals and display them on the display host.

A motion recognition method may include receiving a plurality of frame signals based on radar pulses reflected from a target at different times, generating a plurality of micro-range enhanced frame signals obtained by reinforcing a component of a second region having more movement than movement of a first region among the plurality of frame signals, generating a micro-range enhanced frame set formed by stacking the plurality of micro-range enhanced frame signals at preset time intervals, generating a micro-range enhanced radar image which is an image obtained by viewing the micro-range enhanced frame set in a direction perpendicular to a time axis of the micro-range enhanced frame set, and determining motion of the target by inputting the micro-range enhanced radar image to a machine learning-based learning model.

A bicycle radar system including a camera is disclosed. The system may include a radar unit and a mobile electronic device that are in communication with one another. The radar unit may transmit radar signals, receive return signals (reflections), and process the returned radar signals to determine a location and velocity of one or more targets located in a sensor field behind a user's bicycle. The mobile electronic device may include a communication component configured to wirelessly receive content including cartographic data and one or more high-risk geographic areas and a processor configured to determine a threat level based on the targets, the high-risk geographic area and a determined geographic position.