A pulsed radar system is presented that includes a sliding window and DC offset. A method of pulsed DC radar operation, comprising an operation state, the operation state including initializing parameters for a current integration window; providing timing for the current integration window to an integrating filter based from a transmit pulse; providing a DC offset associated with the current integration window; and incrementing the current integration window to the next integration window to be timed from a next transmit pulse.

A reflectivity correction method using a double polarization variable-based bright band detection result includes a preprocessing operation for correcting a double polarization variable observation error and calculating a depolarization ratio; a fuzzy classifier generation operation for calculating a weighting and a membership function of each characteristic variable using a bright band height extracted from a quasi-vertical profile generated from specific elevation angle data, a bright band detection operation for detecting a bright band using a depolarization ratio and a fuzzy classifier for each elevation angle, and a reflectivity correction operation for correcting reflectivity over-observation for a detected bright band region on the basis of a correction factor calculated using an apparent profile of reflectivity generated by averaging reflectivity data for the bright band region for each elevation angle. Thus, it is possible to improve the accuracy of precipitation estimation by using the corrected reflectivity.

Disclosed are a pulse radar apparatus that detects a position and a motion of a target, and an operating method thereof. The pulse radar apparatus includes a clock signal generator that outputs a transmission clock signal and a reception clock signal, a transmitter that generates a first signal, a receiver that receives an echo signal and the reception clock signal, and generates a second signal, and a signal processor that converts the second signal into a digital signal and analyzes the digital signal. The clock signal generator controls a transmission-to-reception clock delay, and generates a synchronization signal. The signal processor converts the digital signal into a representative value and analyzes the second signal using the representative value. The representative value is one of an accumulated sum of the digital signal in a time duration between synchronization signals and an average value of the digital signal in the time duration between synchronization signals.

Upon each new detection, called pivot detection, by a radar system, the method includes the steps consisting of: grouping together, with the pivot detection, grouped detections, defined as detections that belong to a sweep preceding the sweep of the pivot detection and that have a non-nil probability according to a grouping criterion; filtering the grouped detections so as to keep only detections that are kinematically strictly coherent with the pivot detection, by: initializing a histogram, each dimension of which is a temporal variation of a coordinate measured by the radar system; computing a potential value interval for each coordinate of the pivot detection and each grouped detection; computing a minimum temporal variation and a maximum temporal variation for the or each coordinate from potential value intervals of the pivot detection and each grouped detection; incrementing the set of classes of the histogram whose index along each dimension is located between the computed minimum and maximum temporal variations; and detecting a target once at least one class of the histogram reaches a predefined value.

The learning device learns the target detection model used in the radar device. The learning device includes an acquisition unit, a learning data generation unit, and a learning processing unit. The acquisition unit acquires a reception signal generated based on the received wave and a tracking signal generated based on the reception signal from the radar device. The learning data generation unit generates learning data using the reception signal and the tracking signal. The learning processing unit learns a target detection model that detects a target from the reception signal, using the learning data.

Apparatus and method configured to determine locations of man-made objects within synthetic aperture radar (SAR) imagery. The apparatus and method prescreen SAR imagery to identify potential locations of man-made objects within SAR imagery. The potential locations are processed using a change detector to remove locations of natural objects to produce a target image containing location of substantially only man-made objects.

A method for creating a virtual reception channel in a radar system includes an antenna possessing two physical reception channels (1.sub.r, 2.sub.r) spaced apart by a distance d in a direction x, two emission channels (1.sub.e, 2.sub.e) spaced apart by the same distance d in the same direction x and processing means, the method comprising: dynamically selecting two different waveforms, the waveforms being orthogonal to each other; generating a radar pulse of given central wavelength in each emission channel, each of the emission channels emitting one of the two different waveforms; acquiring with the reception channels echoes due to pulses emitted by the emission channels and reflected by at least one target; compressing the pulses by matched filtering of the echoes acquired by each physical reception channel, this involving correlating them with each of the waveforms generated in the emission channel; and repeating steps a) to c) while randomly changing one of the values of each of the phase codes associated with the generated waveforms until the level of the sidelobes of all the compressed pulses has stabilized; and radar system for implementing such a method.

Systems and methods are described to identify motion events on a sloped surface, such as a mountainside, using transmitted and received radio frequency (RF) chirps. A one-dimensional array of receive antennas can be digitally beamformed to determine azimuth information of received reflected chirps. Elevation information can be determined based on time-of-flight measurements of received reflected chirps and known distances to locations on the sloped surface. Motion events may be characterized by deviations in return power levels and/or return phase shifts. The systems and methods may, for example, be used to provide real-time detection of avalanches and/or landslides.

A vehicle radar system, apparatus and method use a radar control processing unit generate compressed radar data signals, to apply the compressed radar data signals in parallel as a three-dimensional matrix to a coherent integrator (which generates a two-dimensional matrix of coherently integrated image data) and a non-coherent integrator (which generates a two-dimensional matrix of non-coherently integrated image data), and to generate a constant false alarm rate (CFAR) threshold from the two-dimensional matrix of non-coherently integrated image data for application to the two-dimensional matrix of coherently integrated image data to detect one or more targets in the MIMO radar signal returns from sample values from the two-dimensional matrix of coherently integrated image data that exceed the CFAR threshold.

The present disclosure relates to a method for compressing an evaluation curve, which is recorded during a radar-based fill level measurement of a filling material located in a container, and to a corresponding fill level measurement device for carrying out the method. Corresponding to the compression method according to the present disclosure, the present disclosure comprises a corresponding method for decompressing the compressed evaluation curve. The compression method is characterized in that the compression occurs using linear prediction, by corresponding estimation coefficients and an error curve being created. This makes use of the finding according to the present disclosure that evaluation curves can be compressed for diagnostic purposes, in particular in the case of FMCW-based fill level measurement, efficiently and without data loss using the model of linear prediction.

The present disclosure relates to a method for compressing an evaluation curve, which is recorded during a radar-based fill level measurement of a filling material located in a container, and to a corresponding fill level measurement device for carrying out the method. Corresponding to the compression method according to the present disclosure, the present disclosure comprises a corresponding method for decompressing the compressed evaluation curve. The compression method is characterized in that the compression occurs using linear prediction, by corresponding estimation coefficients and an error curve being created. This makes use of the finding according to the present disclosure that evaluation curves can be compressed for diagnostic purposes, in particular in the case of FMCW-based fill level measurement, efficiently and without data loss using the model of linear prediction.