12 results about "Differential reflectivity" patented technology

The invention discloses a frequency domain adaptive clutter suppression method and system for a dual-polarization weather radar, and relates to the technical field of weather radar processing. According to the invention, pulse-level quality control and ground feature identification marking are carried out on radar original echoes; calculating power spectrums of the marking units, performing dynamic noise measurement and data quality grading, and screening out effective processing units; constructing a Gaussian mixture model of a power spectrum of an effective unit, and iteratively estimating model parameters through an expectation maximization algorithm to realize complete separation of a ground feature spectrum and a meteorological spectrum in a frequency domain; inverting single-channel parameters based on the separated meteorological spectrum; a cooperative spectrum separation strategy is adopted for horizontal and vertical polarization channels, and dual-polarization parameters such as differential reflectivity, correlation coefficients and differential phases are inverted based on the filtered dual-channel signals; according to the invention, high-precision separation of clutters and meteorological echoes is realized, the loss of meteorological signals is significantly reduced while ground features are effectively suppressed, and the accuracy and reliability of dual-polarization parameter inversion are improved.

The present application relates to radar signal processing technical field, specifically provide a kind of staggered pulse repetition interval time-frequency domain dual-polarized radar detection variable estimation method, comprising: in frequency domain, the estimation of echo signal-to-noise ratio, reflectivity factor, differential reflectivity of horizontal / vertical polarization based on power spectral density;And the estimation of average Doppler velocity and velocity spectrum width;In time domain, after ground clutter filtering based on odd-even pulse, respectively, odd-even pulse correlation parameter estimation is carried out, so that two detection variables of dual-polarized radar correlation coefficient and differential propagation phase shift of odd-even pulse are obtained respectively, then odd-even combination can obtain the estimation result of accurate correlation coefficient and differential propagation phase shift.The present application realizes the accurate estimation of dual-polarized radar multi-class detection variable, ensures that estimation result is not disturbed by ground clutter interference, simultaneously adapts single pulse repetition interval and staggered pulse repetition interval two working modes, improves the reliability and applicability of radar detection.

The invention provides a dual-polarization weather radar time domain echo simulation method based on Doppler spectrum reconstruction, and the method comprises the steps: constructing a scanning region and a resolution volume grid, dividing a sub-resolution volume grid, and carrying out the interpolation of the sub-resolution volume grid through a trilinear interpolation method; micro-physical information and a scattering matrix of each phase-state particle are calculated, echo intensity contributions are superposed along a speed coordinate axis of a Doppler spectrum and then are sequenced, a horizontal polarization channel Doppler spectrum of each sub-resolution volume grid is obtained, and an antenna pattern is taken as a weight and is superposed, so that a horizontal polarization channel Doppler spectrum of a resolution volume grid is obtained; and obtaining the power spectrum density of the horizontal polarization channel through coordinate transformation, obtaining the IQ echo sequence of the horizontal polarization channel through inverse Fourier transformation, and obtaining the IQ echo sequence of the vertical polarization channel in combination with the differential reflectivity factor, the differential propagation phase shift and the co-polarization correlation coefficient. According to the invention, reliable simulation of time domain echoes in the weather process of any shape spectrum can be realized.

The application discloses a weather radar wind turbine clutter recognition method and system based on fuzzy reasoning, and belongs to the technical field of fuzzy reasoning. The monitoring area of a target weather radar is divided into multiple echo observation subunits according to distance gates and scanning azimuth angles, and the reflectivity factor, radial velocity, spectral width and differential reflectivity of each echo observation subunit are continuously acquired within a preset data acquisition time sequence. By analyzing the discrete characteristics of the reflectivity factor and the radial velocity in the time sequence, echo stability characteristic quantities are constructed, echo shape consistency characteristic quantities are constructed based on the consistency deviation of the spectral width and the differential reflectivity in the neighborhood, the echo stability characteristic quantities and the echo shape consistency characteristic quantities are subjected to fuzzy mapping, and the wind turbine clutter and meteorological echoes are distinguished and recognized through a fuzzy comprehensive judgment quantity, so that the accuracy and robustness of the wind turbine clutter recognition are improved, and the weather radar data quality control under complex background conditions is suitable.

The application provides a ZDR arc automatic recognition random forest modeling method and system, relates to the meteorological radar data processing technical field, and includes the following steps: acquiring dual-polarization radar observation data, extracting a differential reflectivity field and a reflectivity field, determining an arc candidate area based on a spatial position relationship and extracting multi-dimensional feature parameters, calculating a mutual information matrix and a partial correlation coefficient matrix to screen feature pairs and perform tensor product operation to generate high-order interaction features, constructing a training sample set, initializing a basic random forest, and based on feature conditional entropy, reconstructing a sampling probability distribution to complete decision tree growth to obtain a basic classifier, extracting a decision tree discrimination path sequence, converting it into a topology graph, encoding it into a path embedding vector to train a meta-random forest classifier, inputting to-be-recognized data into the basic classifier and the meta-random forest classifier, and outputting a recognition result. The accuracy and automation degree of ZDR arc recognition are effectively improved.

The invention discloses a weather radar wind turbine clutter identification method and system based on fuzzy reasoning, and belongs to the technical field of fuzzy reasoning. A monitoring area of a target weather radar is divided into a plurality of echo observation subunits according to a range gate and a scanning azimuth angle, and a reflectivity factor, a radial speed, a spectral width and a differential reflectivity of each echo observation subunit are continuously acquired in a preset data acquisition time sequence. By analyzing discrete characteristics of a reflectivity factor and a radial velocity on a time sequence, an echo stable characteristic quantity is constructed, an echo form consistent characteristic quantity is constructed based on consistency deviation of a spectral width and a differential reflectivity in a neighborhood, fuzzy mapping is performed on the echo stable characteristic quantity and the echo form consistent characteristic quantity, and the echo stable characteristic quantity and the echo form consistent characteristic quantity are calculated. The wind turbine clutter and the meteorological echo are distinguished and recognized through the fuzzy comprehensive judgment quantity, the accuracy and robustness of wind turbine clutter recognition are improved, and the method is suitable for weather radar data quality control under the complex background condition.

The invention relates to the technical field of forest fire monitoring, and discloses a forest fire monitoring method based on a polarization radar, and the method comprises the steps: S10, obtaining the body scanning data of a monitoring point through the polarization radar, the body scanning data comprising polarization variables, and the polarization variables comprising a horizontal reflectivity, a differential reflectivity, a cross correlation coefficient and a radial speed standard deviation; s20, the polarization variables are preprocessed, the preprocessing comprises normalization and abnormal value cutting processing, and the polarization variables with effective pixel masks are constructed; s30, performing initial classification on the preprocessed polarization variables based on a fuzzy logic algorithm, performing confirmation by adopting multi-source cross validation, and generating forest fire segmentation labeling data of the monitoring points; s40, performing model training by using the mountain fire segmentation historical annotation data set to obtain a mountain fire monitoring model; and S50, inputting the mountain fire segmentation labeling data of the monitoring point into a mountain fire monitoring model to obtain mountain fire monitoring data.

The invention discloses a single dual-polarization radar data self-filling method based on physical constraint and dynamic optimization, and relates to the technical field of data filling. Comprising the following steps: acquiring original observation data, preprocessing the original observation data, and calculating a beam blocking rate; establishing a reliability criterion, and selecting an optimal filling path for each pixel point; when the relative differential phase is determined to be reliable, constructing a core path based on a-relationship; when the differential phase is not reliable but the differential reflectivity is reliable, an auxiliary path is constructed based on a statistical relationship, and data filling is executed hierarchically; and solving a reflectivity field which is finally filled and is physically coherent by minimizing a cost function. Smooth transition of the filling area and the surrounding effective observation area is ensured, and a high-quality data field is formed.

This invention relates to the field of electromagnetic wave technology, specifically to a method, apparatus, and device for identifying short-duration heavy precipitation. The method includes: acquiring radar base data; wherein the radar base data is acquired based on X-band radar; parsing the radar base data to obtain dual polarization parameters corresponding to the target spatial region, the dual polarization parameters including differential reflectivity and differential phase shift rate; determining a portion of the target spatial region that meets preset requirements as a warning area; wherein the preset requirements include: the differential reflectivity is less than a first preset threshold and the differential phase shift rate is greater than a second preset threshold. This addresses the problem in existing technologies that require complex operations such as data correction using other band radars to quickly and accurately identify precipitation.

The invention relates to the technical field of radar signal processing, and particularly provides a staggered pulse repetition interval time-frequency domain dual-polarization radar detection variable estimation method, which comprises the following steps of: in a frequency domain, estimating a horizontal / vertical polarization echo signal-to-noise ratio, a reflectivity factor and a differential reflectivity based on power spectral density; estimating the average Doppler velocity and the velocity spectrum width; in a time domain, after ground clutter filtering based on odd-even pulses, odd-even pulse cross-correlation parameter estimation is carried out respectively, so that two detection variables of a dual-polarized radar correlation coefficient and differential propagation phase shift of the odd-even pulses are obtained respectively, and then odd-even combination is carried out to obtain an accurate estimation result of the correlation coefficient and the differential propagation phase shift. According to the method, accurate estimation of multi-class detection variables of the dual-polarization radar is achieved, it is ensured that the estimation result is not interfered by ground clutters, meanwhile, two working modes of single pulse repetition interval and staggered pulse repetition interval are adapted, and the reliability and applicability of radar detection are improved.

The application provides an X-band weather radar double-channel multifunctional receiving assembly, and relates to the technical field of communication, which comprises: parallel receiving of horizontal and vertical polarization echo signals, twice frequency down-conversion by using first and second local oscillator signals, two digital intermediate frequency signals obtained through a digital intermediate frequency processing module; meanwhile, an up-conversion excitation signal is input into a transmitting chain; a function calibration module calibrates the noise coefficient of a receiving channel, calibrates the delay of a transmission path, and feeds a coupled sample of a transmitting signal into a receiving channel for power monitoring to determine a link gain compensation coefficient; the local oscillator signal and the digital intermediate frequency signal are led out to an external interface for monitoring the frequency source performance and amplitude and phase consistency; two signals are calibrated according to the compensation coefficient, differential reflectivity and differential phase are extracted, precipitation particle phase state structure is analyzed, strong convective weather core areas are determined and circled, and the automation level and early warning timeliness of the X-band weather radar in short-term early warning business are significantly improved.

This disclosure provides a method and system for quality control of non-precipitation data from X-band weather radar. Applied to the field of weather radar technology, the method includes acquiring X-band weather radar data; identifying and removing electromagnetic interference echoes based on the continuity characteristics, correlation coefficient (CC), and differential reflectivity factor (ZDR) distribution of electromagnetic interference echoes; determining whether the difference in reflectivity factor before and after hardware filtering at each echo point is greater than a preset threshold; if so, marking the echo point as a precipitation echo; otherwise, performing fuzzy logic recognition and elimination based on feature parameters; wherein, the probability P of non-precipitation echoes at each echo point is calculated based on the feature parameters. NPR and precipitation echo probability P PR Determine P NPR Is it greater than P? PR If so, the echo point is marked as a non-precipitation echo; otherwise, a weak non-precipitation echo is identified. This is determined by comparing the mean reflectivity factor, mean correlation coefficient, and the percentage of effective distances between the echo points at the entire elevation angle. CC与 The threshold value is used to determine whether an echo is non-precipitation. If it is, the echo point is marked as a non-precipitation echo; otherwise, the radial and azimuth reflectivity factors are continuously used to filter out scattered and patchy noise around the echo point to obtain precipitation echoes. In this way, the quality of weather radar data can be improved.