25 results about "High resolution radar" patented technology

The invention relates to an artificial precipitation enhancement operation area identification method and system based on multi-source data, and relates to the technical field of meteorological intervention operation, and the method comprises the steps: building a multi-resolution dynamic data grid system, and enabling a coarse-grained grid layer to cover the whole operation area, and to be used for bearing the macro data of a satellite cloud picture and a conventional radar; the fineness grid layer is used for receiving and mapping real-time data provided by the high-resolution radar; receiving real-time data of all cloud blocks, mapping the real-time data to corresponding grid layers, and projecting the data collected at different time points to a unified time reference frame to obtain a cloud system state view; predictive interpolation is carried out by using the latest data of the conventional radar and the macroscopic trend of the satellite cloud picture in combination with the motion vector and confidence weighting so as to obtain cloud system information; and forming a visual cloud system three-dimensional view, identifying and tracking a target cloud block with an artificial precipitation enhancement potential, and generating an operation instruction. The method has the effect that the target cloud block with the operation value can be identified and tracked to generate the accurate operation instruction.

The invention discloses a three-dimensional radar echo reflectivity variational auto-encoder pre-training method, which belongs to the technical field of meteorological radar data analysis, and comprises the following steps: extracting advanced features from three-dimensional high-resolution radar data through a space encoder based on an attention mechanism; mapping the advanced features into determined probability distribution parameters using a probabilistic encoder; sampling according to the distribution parameters by using a re-parameterization technique to obtain continuous potential variables; mapping the potential variables back to a pixel space by using a probability decoder based on an attention mechanism to complete data reconstruction; and finally, constructing a mixed loss function consisting of a mean square error and KL divergence by utilizing a reconstruction result and a distribution parameter to train the model. According to the invention, by optimizing the network architecture and introducing the attention mechanism, high-quality reconstruction of high-resolution three-dimensional radar data is realized while extremely low video memory requirements and low parameter quantity are ensured, and the practical value of data synthesis and enhancement is remarkably improved.

The invention provides a hectometer-level short temporary rainfall forecasting method based on generative adversarial network downscaling and physical constraint, which belongs to the technical field of weather forecast, and is characterized in that S-band radar jigsaw and high-resolution X-band radar observation data are fused through an adaptive rule to generate a fused radar echo combined reflectivity, and the combined reflectivity is used for forecasting the rainfall of the hectometer-level short temporary rainfall. A super-resolution downscaling model is constructed by using a generative adversarial network, a long-sequence high-resolution radar echo training data set is reconstructed, a deep learning forecasting model is constructed, a high-resolution radar echo sequence is used as input, space-time modeling training is performed by using a composite loss function, and a future radar echo forecasting field is output. The Z-R relation is converted into quantitative rainfall forecast, and finally the quantitative rainfall forecast with the spatial resolution reaching the hectometer level is generated. The interpretability of the model is enhanced through physical constraint, the bottleneck of insufficient hectometer-level resolution training data is effectively solved, and the spatial refinement degree of short temporary rainfall forecasting and the forecasting capacity for a severe convection system are remarkably improved.

The invention relates to a radar scanning system (100) for non-invasive analysis of targets (10), comprising a plurality of radar transceivers (111) arranged in an irregular geometric configuration. The system (100) performs sequential acquisitions with a view to generating a high-resolution radar representation (20). A reconstruction processor coupled to an artificial-intelligence module (140) processes the acquired data in order to detect, classify and analyse objects within the target. The system (100) dynamically adapts to the characteristics of the target (10) and is able to compensate for relative movement between the system (100) and target. The invention is applicable to various fields requiring detailed and non-invasive analysis of internal structures.

The application discloses a kind of high-resolution radar echo extrapolation prediction methods of fusion satellite data, specifically as follows, first, input history radar echo sequence pretreatment of previous T time, including denoising, normalization processing, data set segmentation, obtain cleaned data;Then, by deterministic modeling method (SimVP), obtain the fuzzy prediction sequence of future T length, then variational autoencoder (VAE) respectively original radar echo image and fuzzy prediction sequence are mapped to low-dimensional latent space, and two-stage diffusion modeling is carried out on this basis;For the first stage, utilize space-time converter (ST-Translator) to extract the space-time evolution characteristics of radar echo;Second stage first input corresponding time satellite data of previous T time, pretreatment is carried out, including normalization processing, feature selection, data set segmentation, obtain cleaned data, adopt multi-source fusion denoising network Fsrformer, dynamically adjust the influence of satellite data in diffusion process, to make full use of satellite information;Finally, the output result of two stages is inversely transformed to pixel space, and the high-resolution radar echo extrapolation prediction result of future T length is obtained.The application can effectively reduce the consumption of computing resources, improve the precision and detail fidelity of short-term precipitation prediction.

The invention discloses a lightweight multilayer radar echo reconstruction method based on Gaussian splashing, and relates to the technical field of meteorological radar data processing. The method comprises the following steps: preprocessing and standardizing multi-layer radar echo data; dividing the data into space sub-blocks and independently executing Gaussian initialization; constructing a multi-scale lightweight encoder, and fusing spatial context information of adjacent sub-blocks while extracting local features of the sub-blocks; constructing a customized decoder, and reconstructing the implicit vectors into Gaussian ellipsoid parameters with physical constraints according to an attribute dynamic selection path; executing multi-layer micro rendering to generate a simulation image; and calculating composite loss and back-propagating optimization model parameters. According to the method, through sub-block context coding and parameterized Gaussian representation, the problem of discontinuous sub-block boundaries is effectively solved while the high-resolution radar data storage and calculation cost is remarkably reduced, and high-fidelity and physically reasonable radar echo three-dimensional reconstruction is realized.

A method for the model-based, high-resolution separation of radar targets for a radar sensor, in which the radar sensor initially generates radar data by capturing radar targets by sampling a field of view of the radar sensor. Various model orders are calculated for the number of radar targets with the aid of a grid-based method and are interleaved in one another. A highest model order is specified, and only the highest model order is calculated, so that the lower model calculations are implicitly produced from the calculation of the highest model order.

The application relates to a kind of artificial precipitation enhancement operation area identification method and system based on multi-source data, and relates to meteorological intervention operation technical field, comprising the following steps: establishing multi-resolution dynamic data grid system, coarse granularity grid layer covers entire operation area, for carrying satellite cloud atlas and the macro data of conventional radar;Fine grid layer, for receiving and mapping the real-time data provided by high-resolution radar;Receive all cloud block real-time data and map to corresponding grid layer, project the data collected at different time points to unified time reference frame to obtain cloud system state view;Using the latest data of conventional radar and the macro trend of satellite cloud atlas, combined with motion vector and confidence weighted, predictive interpolation is carried out to obtain cloud system information;Form a visual cloud system three-dimensional view, identify and track target cloud block with artificial precipitation enhancement potential and generate operation instruction.The application has the effect that target cloud block with operation value can be identified and tracked to generate accurate operation instruction.

The utility model belongs to the technical field of radars, and particularly relates to a high-resolution radar target recognition device, which comprises a shell, a cylindrical box, a screw rod, an adjusting assembly, a radar signal transmitting unit, a high-resolution signal acquisition unit, a data processing and analyzing unit and a data transmission interface, the radar signal transmitting unit, the high-resolution signal acquisition unit and the data processing and analyzing unit are electrically connected in sequence, and the data transmission interface is connected with the data processing and analyzing unit; the radar signal transmitting unit, the high-resolution signal acquisition unit, the data processing and analyzing unit and the data transmission interface are all arranged in the shell. The device provided by the utility model is reasonable in design, and solves the problems of inconvenient height and inclination angle adjustment and the like caused by signal emission, acquisition, processing, anti-interference and fixed installation modes of an existing device, thereby realizing high-resolution, high-precision and real-time identification of a target and use flexibility.

The invention relates to an adaptive radar sparse imaging method based on a near-field physical model, and the method is constructed at least based on the following scheme: imaging modeling: at least constructing an imaging problem of a specific distance unit into a linear inverse problem; designing a physical decoupling network architecture, and at least designing a learnable induction strategy and an adaptive threshold; offline training: updating learnable parameters at least according to the obtained total loss to complete model training; and performing online reasoning, and outputting a target image at least based on forward propagation. The problems of model mismatch and imaging failure caused by the fact that an existing deep learning model LISTA cannot adapt to the change of a physical observation model along with the distance in near-field or high-resolution radar application are at least solved.

This invention discloses a rapid measurement method for sea surface backscattering coefficient based on airborne high-resolution radar, belonging to the field of sea surface backscattering coefficient measurement technology. The method includes the following four steps: S1, determining the rubbing angle interval and the number of measurements, and performing measurements sequentially; S2, compressing the range pulses of the echo signal to obtain a one-dimensional high-resolution range image of the sea surface that varies over time; S3, calculating the local rubbing angle of each pulse in each range unit of the range image, and classifying them according to small step intervals of the rubbing angle; S4, calculating the sea surface backscattering coefficient for each category, obtaining the measurement results at small step intervals of the rubbing angle. This invention employs the above-mentioned rapid measurement method for sea surface backscattering coefficient based on airborne high-resolution radar, requiring only a few measurements with large step intervals of the rubbing angle to obtain the sea surface backscattering coefficient measurement results at small step intervals of the rubbing angle, which helps reduce the cost and time of sea clutter measurement.

The invention provides a wind field inversion method based on an X-band radar and a numerical mode, and the method comprises the following steps: firstly, taking a three-dimensional wind field predicted based on a 3-kilometer numerical mode of a coarse resolution as an initial field of wind field inversion in a wind field inversion process; then, high-resolution S-band and X-band radar observation data are introduced, the radar reflectivity is subjected to quality control, and radial wind is subjected to speed deblurring processing; then combining the coarse resolution mode data and the high resolution radar data to perform data fusion; introducing a conservation equation as a constraint condition and calculating a loss function in a mode of solving the vertical velocity in the high-precision three-dimensional wind field; and finally, iteratively solving the optimal solution of the loss function based on an optimization algorithm to obtain an inversion wind field. According to the technical scheme, the problem of lack of 1-2 kilometer low-altitude wind field monitoring of the S-band radar is solved.

The invention relates to a method for model-based high-resolution separation of radar targets for a radar sensor, in which the radar sensor first generates radar data by detecting radar targets through scanning a field of view of the radar sensor, wherein different model orders for the number of radar targets are calculated using a grid-based method and are nested within each other, a highest model order is determined, wherein only the highest model order is calculated, so that the lower model calculations result implicitly from the calculation of the highest model order.

The invention relates to a radar scanning system (100) for the non-invasive analysis of targets (10), comprising a plurality of transceiver radars (111) arranged in an irregular geometric configuration. The system (100) performs sequential acquisitions to generate a high-resolution radar representation (20). A reconstruction processor, coupled to an artificial intelligence module (140), processes the acquired data to detect, classify, and analyze objects within the target. The system (100) dynamically adapts to the characteristics of the target (10) and can compensate for relative motion between the system (100) and the target. This invention has applications in various fields requiring detailed and non-invasive analysis of internal structures. Figure to be published with the abstract: Figure 1

This invention discloses an inverse synthetic aperture radar (ISAR) imaging method based on multi-scale synchronous compression transform, which is achieved through the following steps: decomposing the target echo signal into low-frequency rigid body components and high-frequency micro-Doppler components; using coarse-scale synchronous compression to extract the low-frequency main structure, and fine-scale synchronous compression to separate high-frequency micro-motion features; using entropy normalization weights to fuse multi-scale time-frequency features to generate a high-resolution fused spectrum; reconstructing the target image based on the fused spectrum, simultaneously suppressing noise and enhancing micro-motion features. This invention, through multi-scale hierarchical processing and entropy weight fusion mechanism, solves the problems of image blurring and micro-Doppler aliasing caused by acceleration motion, significantly improving the imaging clarity and feature recognition capability of high-speed maneuvering targets in complex scenes, and providing a reliable solution for high-resolution radar imaging.

The present application relates to SAR radar signal processing technical field, specifically to a kind of SAR radar system transmitting time delay stable method, comprising: acquisition radar operating frequency, transmitting pulse repetition frequency, system operating temperature and transmitter power amplifier operating voltage and other operating parameters, and system reference time delay value under nominal operating condition is obtained by table lookup method.The real-time compensation time delay value is obtained by using improved adaptive filter algorithm, combining frequency and pulse repetition frequency variation amount for iterative update, and real-time correction to reference time delay.In the SAR imaging range direction pulse compression stage, according to the time delay value, the radar echo sampling time sequence is adjusted, the compensated pulse compression data is generated, and the imaging processing is completed.The method can quickly track the time delay drift caused by operating condition change, accurately eliminate time delay deviation in key imaging link, effectively suppress the image distortion caused by time delay fluctuation, so that the system can output stable high-resolution SAR radar image under different operating environments.

This application discloses a radar echo spatial downscaling method, apparatus, equipment, medium, and program product, relating to the field of meteorological information processing technology. The method includes: acquiring low-resolution radar echo data to be processed; upsampling the low-resolution radar echo data to be processed through interpolation to obtain high-resolution target echo data; extracting features from the high-resolution target echo data to obtain an initial high-frequency information representation map; and inputting the low-resolution radar echo data to be processed and the high-resolution target echo data into a downscaling model to obtain a high-resolution radar echo field corresponding to the low-resolution radar echo data to be processed. This application enhances the application value of radar echo data in refined weather analysis and severe weather early warning.

The invention provides a high-resolution radar signal processing method and system for building deformation monitoring, and the method comprises the steps: setting a radar parameter according to a monitoring demand, and collecting a reflection echo signal of a building surface; the data are acquired by an ADC to obtain staggered I / Q channel data, and the I / Q channel data are separated and reconstructed to obtain a complex signal; processing the complex signal by adopting an improved Chirp-Z transformation algorithm to obtain a complex frequency spectrum; calculating the amplitude of a complex frequency spectrum, extracting a frequency spectrum index corresponding to the strongest reflection point on the surface of the building through peak detection, and converting the frequency spectrum index into a preliminary distance value of a target relative to the radar; calculating an azimuth angle of the target relative to the radar, and obtaining a two-dimensional coordinate of the strongest reflection point in a relative coordinate system of the radar through coordinate transformation in combination with the initial distance value; the method is used for calculating two-dimensional coordinate position changes of monitoring points on the surface of the building, millimeter-level deformation monitoring is achieved, and the method is suitable for a radar monitoring system.

The application provides a Ka-band circularly polarized antenna unit, an antenna array and a phased array on a satellite, and belongs to the technical field of antennas.The application aims to solve the connection problem between the phased array and a T / R component and the wideband wide-angle radiation problem.The phased array comprises a radiation structure in an upper layer, a parasitic structure in an intermediate layer and a feeding structure in a lower layer.The radiation structure is composed of upper metal patches and can realize circularly polarized antenna beam radiation.The feeding is realized by coupling transmission from the lowermost metal probe to the upper metal to realize radiation.A metal via hole is added around the radiation antenna to reduce the coupling effect between the antennas.The rotation angle of each antenna unit and the phase of the corresponding phase shifter are the same and are n times of 90 DEG, wherein n is 0, 1, 2 or 3;the rotation angle difference of any two adjacent antenna units and the phase difference of the phase shifter are both 90 DEG, so as to be matched with the bottom T / R component feeding hole.The application can be used for millimeter wave antenna communication and high-resolution radar imaging.

The invention discloses a high-resolution radar through-wall imaging method based on broadband radar signal space frequency spectrum shifting, and belongs to the technical field of through-wall radar imaging. The method aims to solve the problems of low imaging resolution, target defocusing, position offset and the like caused by wall refraction in the prior art. According to the invention, a co-prime MIMO radar structure is adopted to transmit broadband signals and receive echoes; the method comprises the following steps: firstly, performing path compensation on an echo signal according to a wall dielectric constant and thickness, and correcting beam propagation time delay and path bending caused by a wall; then, eliminating emission signal time waveform information in the echo, and extracting a space phase component containing target position information; calculating spatial frequency points corresponding to different transmitting-receiving antenna pairs, and filling the spatial frequency points into a spatial frequency spectrum matrix to construct an original spatial spectrum of a target; and finally, performing two-dimensional inverse Fourier transform on the spatial frequency spectrum matrix to realize high-resolution and high-precision focusing imaging of the target. According to the invention, the imaging side lobe and defocusing effect are effectively reduced, and the definition and accuracy of through-wall imaging are improved under the condition that hardware and data are limited.

A high-resolution radar device is provided, which includes a transmission antenna, a plurality of reception antennas, a radio frequency (RF) transceiver chip, and a signal processor. The transmit antenna transmits the radar transmit signal to the moving object. The plurality of reception antennas simultaneously receive a plurality of radar receive signals reflected from the moving object, respectively. The RF transceiver chip simultaneously converts the plurality of radar received signals into a plurality of baseband signals, respectively. The signal processor simultaneously back-projects the plurality of baseband signals to detect a location of the moving object.

An apparatus comprising an interface and a processor. The interface may receive radar data from a plurality of radar devices. The radar device may each be implemented at a respective edge site. The radar data may comprise sparsity. The processor may be configured to receive the radar data corresponding to each of the radar devices from the interface, perform virtual aperture imaging in response the radar data, and generate high resolution radar data based on the virtual aperture imaging. The sparsity may be used to capture the radar data may enable the radar data to have a low data volume. The virtual aperture imaging may be configured to enable the high resolution radar data to be generated from the low data volume. The processor may enable high data throughput at a central location for the radar data generated at the respective edge sites.

The invention relates to the technical field of millimeter wave radar and deep learning, in particular to a millimeter wave radar virtual channel prediction method and system based on self-supervised learning and a medium. According to the method, after radar channel signal preprocessing and recombination, multi-scale residual feature extraction, feature pyramid fusion and angle dimension up-sampling, virtual channel signal regression prediction and self-supervised training and loss constraint are carried out in sequence, radar data with high angle resolution are obtained; according to the method, on the premise of not depending on high-resolution radar data as external supervision, prediction and extension of a virtual channel are realized by using a channel structure and an internal association relationship of low-resolution radar data; self-supervised virtual channel prediction and high-angle-resolution atlas generation can be stably realized under multiple data sets, different hardware and different labeling modes, and a reliable, efficient and migratable technical scheme is provided for target detection and environmental perception of a millimeter wave radar with only a small number of antennas or low-angle-resolution low-hardware configuration.

The application belongs to the technical field of computer modeling and simulation, and discloses a multi-resolution radar modeling and simulation method and system based on AFSIM, which registers and builds a pluggable multi-resolution radar framework through a plug-in registration interface in an application extension mode, embeds a communication interface protocol to realize bidirectional interaction with an external high-resolution radar, embeds an AFSIM communication mechanism to realize bidirectional interaction with an embedded low-resolution model, adds a script language adaptation layer to support runtime dynamic parameter configuration and resolution switching, compiles the plug-in into a dynamic link library and places it in an AFSIM scanning directory to realize automatic loading and scheduling, so as to build a plug-and-play multi-resolution radar architecture model. The application builds a plug-and-play multi-resolution radar architecture model, provides a technical basis for high / low dual-resolution joint simulation, and provides a general method and reference for building a sensor simulation architecture with multi-resolution switching capability.

The invention discloses an unmanned aerial vehicle micro-Doppler separation inverse synthetic aperture radar imaging method, and relates to the technical field of radar imaging. The method comprises the following steps: performing distance compression, envelope alignment and phase compensation on a received echo signal to obtain processed data; according to the method, radar echo data are processed, the processed data form a one-dimensional range profile, the modal number input in a VMD algorithm is determined according to the number of strong scattering points in the one-dimensional range profile, then the VMD algorithm is expanded to a complex signal domain, radar echo data are separated, radar echo data with micro-Doppler signals removed are obtained, and finally radar echo imaging is carried out. According to the method, effective information of a high-resolution radar one-dimensional range profile is utilized, a traditional VMD optimization method is improved, the micro-Doppler separation ISAR imaging algorithm optimized through the VMD is more efficient, and meanwhile interference of ISAR imaging of the micro-Doppler effect can be effectively removed.