A method and system. The method includes receiving weather radar data. The method further includes filtering out weather from the weather radar data to provide filtered radar data. Additionally, the method includes determining whether the filtered radar data includes any non-weather targets. If any of the non-weather targets is a hazard target, the method includes storing data associated with the hazard target in a hazard data structure.

An information display device (100) is provided, which includes a distance setting module (20) configured to set a distance, a closest approach position estimating module (32) configured to estimate a closest approach position (Psa, Psb) of a first ship (S) and a closest approach position (Pa, Pb) of a second ship (Ea, Eb) at a time point when the first and second ships (S, Ea, Eb) approach each other the closest, based on navigational information of the ships (S, Ea, Eb), and a display controlling module (35) configured to cause a display screen to display the estimated closest approach position (Pa, Pb) of the second ship (Ea, Eb), a risk area (Aa, Ab), and current positions of the ships (S, Ea, Eb), the risk area (Aa, Ab) formed into a circle based on the set distance, centering on the estimated closest approach position (Psa, Psb) of the first ship (S).

A RADAR apparatus and a method for generating echo images and enhancing the visibility of echo images on a display unit are disclosed. The RADAR apparatus has an antenna configured to receive echo information of a plurality of electromagnetic waves at a vessel, from a plurality of objects. The plurality of objects includes land objects, Automatic Identification Systems (AISs), and floating objects. A smart RADAR is configured to generate a display output based on the echo information, electronic chart information extracted from a storage module, and AIS information received from the AIS. The smart RADAR applies a mask to the plurality of objects in the display output, based on mask information received from a user, to identify at least one unknown object from the plurality of objects. The smart RADAR automatically applies dilation of the mask in the display output, based on a display parameter set by the user.

An image processing device which generates an image where a target object can be discriminated from an object other than the target object. An image processor (15), for echo signals read from a sweep memory (14), calculates a ratio of echo signals indicating a predetermined level or higher among the echo signals of a predetermined number of samples, and generates image data having a display element according to the calculated ratio. This ratio indicates a lower value for an object more isolated and a higher value for an object existing as a larger mass. The image processor (15)acquires color values according to the calculated ratio. Since the target object, such as a ship, is an isolated object and the ratio becomes low, the color values indicate red, and since inland is an object existing as a large mass and the ratio becomes high, the color values indicate green.

A radar or sonar system amplifies the signal received by an antenna of the radar system or a transducer of the sonar system is amplified and then subject to linear demodulation by a linear receiver. There may be an anti-aliasing filter and an analog-to-digital converter between the amplifier and the linear receiver. The system may also have a digital signal processor with a network stack running in the processor. That processor may also have a network interface media access controller, where the system operates at different ranges, the modulator may produce pulses of two pulse patterns differing in pulse duration and inter-pulse spacing, those pulse patterns are introduced and used to form two radar images with the two images being derived from data acquired in a duration not more than twenty times larger than the larger inter-pulse spacing, or for a radar system, larger than one half of the antenna resolution time. One or more look-up tables may be used to control the amplifier. The radar system may generate digital output which comprises greater than eight levels of radar video.

This disclosure is directed to methods, devices, and systems for generating a weather radar output with bright band suppression. In one example, a method includes determining, for each of several portions of a vertical column from a weather radar signal, a reflectivity range selected from a highest reflectivity range and one or more lower reflectivity ranges. The method further includes determining, in response to determining that portions of the vertical column are in the highest reflectivity range, whether a combination of the reflectivity ranges of the portions of the vertical column meet criteria indicative of high-reflectivity stratiform weather. The method further includes generating, in response to determining that the combination of the reflectivity ranges of the portions of the vertical column meet the criteria indicative of high-reflectivity stratiform weather, a weather radar output that indicates each of the portions of the vertical column as associated with one of the lower reflectivity ranges.

An exemplary computer implemented digital image processing method conveys probabilities of detecting terrestrial targets from an observation aircraft. Input data defining an observation aircraft route relative to the geographical map with lines of communications (LOC) disposed thereon are received and stored as well as input data associated an aircraft sensor's targeting capabilities and attributes related to the capability of targets to be detected. Percentages of time for line-of-sight visibility from the aircraft of segments of LOC segments are determined. Probability percentages that the sensor would detect a terrestrial target on the segments are determined. The segments are color-coded with visibility and sensor detection information. A visual representation of the map with the color-coded segments is provided to enhance the ability to select appropriate observation mission factors to achieve a successful observation mission.

According to one embodiment, a system includes a radar configured to irradiate electromagnetic waves on a target and receive reflected electromagnetic waves from the target, an imaging unit configured to image the target and output target image information, a measurement unit configured to measure a position of the radar, and a processor configured to output first image information representing a first area within the target where the electromagnetic waves are not irradiated based on the position of the radar.

An active radio-frequency (RF) sensing technology for determining the relative and/or absolute state (e.g., position, velocity, and/or acceleration) of a target object (e.g., a person, a car, a truck a lamp post, a utility pole, a building) is described. The sensors described herein operate in the Terahertz band (300 GHz to 3 THz). An active RF sensing device comprises a substrate and first and second semiconductor dies mounted on the substrate. The first semiconductor die has an RF transmit antenna array integrated thereon, and the transmit antenna array comprises a first plurality of RF antennas configured to generate an RF signals having frequency content in the 300 GHz-3 THz band. The second semiconductor die has an RF receive antenna array integrated thereon, and the receive antenna array comprises a second plurality of RF antennas configured to receive RF signals having frequency content in the 300 GHz-3 THz band.

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.