147 results about "Radar network" patented technology

The invention discloses a networking X-band weather radar cooperative adaptive control method, and relates to the technical field of weather radars. The problems that in the prior art, real-time state data and historical data cannot be fully utilized to construct an accurate radar performance model, and deep analysis on environment characteristics is lacked when control parameters are dynamically adjusted are solved. According to the method, the operation state and historical data of the radar system are collected and analyzed, the radar performance model is established, and the control parameters are dynamically optimized, so that the observation performance and the resource utilization efficiency of the radar system are remarkably improved, state information sharing and cooperative adjustment among the radar systems are realized based on a cooperative control mechanism of a communication link, and the reliability of the system is improved. The adaptability and reliability of the system are effectively enhanced, main factors influencing the system performance can be identified by constructing an intelligent performance evaluation module, model parameters are dynamically adjusted, constraint conditions are optimized, and long-term efficient operation of the radar network under complex environmental conditions is ensured.

The invention discloses a multi-mode laser radar networked atmospheric parameter collaborative monitoring system and monitoring method, and relates to the technical field of atmospheric monitoring, and the method comprises the steps: deploying multi-mode laser radar nodes, synchronously collecting multi-source atmospheric parameters for preprocessing, and obtaining a fusion feature matrix; transmitting the fusion feature matrix to an edge computing node through dynamic networking, and aggregating the edge node through federal learning to realize cloud fusion; the method comprises the following steps: constructing a space-time dynamic graph based on laser radar nodes and a space-time dependency relationship between the nodes, decomposing space-time dynamic correlation into a stable item and a non-stable item through space-time decoupling, and updating space-time dynamic graph data by adopting an alternating optimization strategy through online learning; and constructing a prediction model, taking the real-time feature flow obtained by cloud fusion as input, detecting an abnormal event by predicting atmospheric parameters, and performing pollution traceability. According to the invention, high-precision and real-time monitoring of atmospheric parameters is realized through multi-mode cooperative sensing, intelligent fusion analysis and dynamic optimization decision.

The invention discloses a multi-extended target tracking method based on radar resource allocation, and the method comprises the steps: constructing a radar network non-cooperative game model according to the joint geometric precision attenuation factor of each extended target, carrying out the allocation of the extended targets of radar tracking, and obtaining an optimal radar tracking target allocation result; a radar network non-cooperative game model is constructed, a distribution problem is modeled as a multi-radar competition and cooperation relationship, and contour characteristics of an extended target are optimized and tracked, so that quicker response is realized, the resource utilization rate is optimized, and the accuracy and real-time performance of target tracking are improved; and after the distributed extended targets are measured by using the radars, constructing a joint association vector according to measurement results of the extended targets, obtaining joint states obtained by tracking the different extended targets by the radars, and performing fusion to obtain fusion results of the different extended targets so as to complete tracking of the multiple extended targets.

The invention discloses a hail early warning method and system based on lightning jump and a support vector machine, and the method comprises the steps: obtaining a combined reflectivity factor, a vertical integral liquid water content and echo top height data through radar networking data, recognizing a severe convective echo region, and calculating a lightning time change rate and a standard deviation thereof; a potential hail event is screened in combination with a lightning jump increase condition, a vertical integral liquid water content maximum value VILmax, a jump increase GVIL and a density VILD are further extracted as feature parameters, and the feature parameters are input into a support vector machine classification model based on historical sample training for secondary judgment, so that the false alarm rate of a traditional 2 sigma algorithm is effectively reduced, and the hail early warning accuracy is improved.

The invention provides a large-scale insect and bird migratory flight monitoring system based on a weather radar net, and the system employs a data collection module to obtain S, C and X wave band weather radar monitoring data of the national weather radar net, and a quality control module carries out the quality control of the radar-based data in the monitoring data, and further provides the radar-based data to an echo recognition module to construct recognition features. A classification recognition result is obtained by adopting a recognition model corresponding to the wave band; the inversion quantification module inverts the insect and bird density, the insect and bird speed and the vertical distribution of the movement direction based on the classified and identified insect and bird echoes to obtain an inversion quantification result; and the classification identification result and the inversion quantification result of the single wave band form a local monitoring result. And the visualization module displays a single-band local monitoring result or a multi-band fusion monitoring result. According to the invention, multi-band data can be collected, monitoring results are fused, real-time and efficient monitoring of migration of insects and birds is realized, and the monitoring range is expanded.

The invention discloses a distance-speed deception jamming identification method based on space-time-frequency feature fusion. The method comprises the following steps: radar signal spatial domain feature statistics are selected; radar signal frequency domain feature statistics are selected; radar signal time-space domain feature statistics are constructed; constructing time-frequency domain characteristic statistics of the radar signals; and radar signal space-time frequency fusion feature judgment. According to the method, the condition that a radar net is subjected to distance-speed composite deception jamming is taken as a research background, and after possible target tracks are formed for echo trace points by utilizing the characteristic differences of a real target and a false target in a space domain, a frequency domain and a time domain, the space domain characteristics and the frequency domain characteristics of the echo trace points at a single moment are extracted; and over-threshold detection is carried out on the statistics corresponding to the spatial domain features and the frequency domain features at each moment, and the detection result is represented by '0' or '1'. And finally, the detection results are accumulated at multiple moments, so that the judgment on whether the radar is subjected to distance-speed composite deception jamming or not is completed.

The invention discloses a radar networking-oriented robust distributed target tracking method, a storage medium and equipment, and belongs to the technical field of target tracking of multi-radar networking. The objective of the invention is to solve the problem of poor tracking effect caused by non-Gaussian noise in a target tracking scene for multi-radar networking. The method comprises the following steps: firstly, accurately modeling a state equation, a radar measurement equation and non-Gaussian flicker noise of a target; a maximum correlation entropy CKF method with variance compensation is determined based on the maximum correlation entropy and a CKF algorithm, then the state of a target is estimated, and an estimated value # imgabs0 # of the state and a corresponding estimated error covariance matrix # imgabs1 # are obtained based on estimations # imgabs2 # and # imgabs3 # obtained by all radar nodes to perform diffusion fusion with neighbor nodes by using a CI strategy.

Disclosed herein are systems and methods for a multistatic radar system that is configured to detect airborne objects without the need for a transponder on the aircraft. The multistatic radar can be implemented using preexisting communications infrastructure associated with various networks such as paging networks. The multistatic radar system can be implemented using a plurality of multistatic communications links (e.g., transmitters that are communicatively coupled to a plurality of receivers). The distribution of transmitters and receivers in the network can be based on the RF conditions of the coverage area of the network. The multistatic radar network can produce one or more deterministic waveforms that provide the network with signal diversity needed for accurate detection, localization, and tracking of airborne assets. By controlling the waveforms in the system, as well as the density of the network, the multistatic radar system is able to use narrowband signals and operate with lower power than conventional radar systems.

The invention discloses a radar networking anti-stealth detection performance obtaining method, device and equipment and a medium, and relates to the technical field of radar detection, the method and device are applied to a preset radar networking, the preset radar networking comprises a plurality of basic radar detection units, and the method comprises the following steps: receiving echo signals generated by the plurality of basic radar detection units, obtaining an available observation information group by using the echo signal; performing coordinate estimation of a stealth target on the available observation information group to obtain a target position of the stealth target; obtaining the positioning precision of the target position by using the target position and a preset positioning precision formula; and obtaining the detection power of the preset radar network based on the detection area of each basic radar detection unit. According to the scheme, the anti-stealth detection performance of the radar networking can be determined by acquiring the positioning precision and the detection power.

The invention discloses a multi-radar vital sign monitoring system applied to a fixed crowd place. The multi-radar vital sign monitoring system comprises a horizontal layer 24 GHz radar network, a vertical layer 60 GHz radar array and an auxiliary sensor module. Through three-dimensional collaborative deployment of heterogeneous radars, an improved variational mode decomposition algorithm and a joint probability data association tracking technology are combined to realize separation of breathing, heart rate and behavior characteristics of multiple targets in a dense scene. The system adopts a space-time diagram convolutional network to extract individual gait periodic features, establishes a unique biological feature coding file through dynamic gesture track matching, and completes non-contact identity binding. A multi-band radar chip and a dual-mode communication interface are integrated in hardware design, and a lightweight AI model is deployed in software architecture to realize localized real-time analysis. The embodiment covers nursing home tumble monitoring, hospital postoperative monitoring and kindergarten safety management and control scenes, the radar distance and the beam direction can be dynamically adjusted, and the problems of privacy disclosure and target confusion existing in a traditional monitoring system are solved.

The invention belongs to the technical field of electronic countermeasures, discloses a small approaching type unmanned aerial vehicle flight path deception feasibility evaluation and correction method, and discloses a flight path plan making method for implementing flight path deception interference on a radar by using a small approaching type unmanned aerial vehicle, which comprises the steps of expected flight path feasibility evaluation and expected flight path correction. The advantages of the small approaching type unmanned aerial vehicle are developed to the maximum extent. The method is suitable for flight path deception of a single unmanned aerial vehicle to a single radar and flight path deception of an unmanned aerial vehicle group to a radar net. According to the flight path plan making method for implementing flight path deception on the radar by using the unmanned aerial vehicle, power and speed constraints of the unmanned aerial vehicle are considered, feasibility evaluation is carried out on the designed expected flight path, a set of correction strategies is provided for an infeasible area, it is guaranteed that the corrected flight path is close to the original expected flight path as much as possible, and the flight path deception rate is improved. And the effect of the unmanned aerial vehicle is maximized.

The invention relates to an active and passive joint tracking scheduling method and device for radar networking under main lobe jamming, and the method comprises the steps: designing an evaluation function with a minimum tracking error as a target through constructing a radar active measurement model and a passive positioning model, and obtaining a radar active measurement model and a passive positioning model; and a reinforcement learning agent of a near-end strategy optimization algorithm is used for carrying out radar active and passive working mode distribution, and the optimal residence time is further solved, so that the tracking performance and the system anti-interference capability of the radar networking cooperative detection system in a strong interference environment are improved. Therefore, the problems that the optimal performance of the system cannot be achieved in the prior art, the tracking performance of the radar networking cooperative detection system under the main lobe interference is easily reduced, and multi-radar task allocation under the main lobe suppression interference environment is difficult to reasonably plan are solved.

A radar sensor system comprises a first radar sensor and at least a second radar sensor and one or more processors configured to perform acts comprising transmitting a first signal from a first transmit antenna in a first radar sensor and transmitting a second signal from a second transmit antenna in a second radar sensor. The acts further comprise detecting an object at the first radar sensor and the second radar sensor and estimating vector velocity information vx and vy for the object. The acts also comprise generating a radar measurement vector z that comprises position information px and py for the object and incorporating the vector velocity information vx and vy into the radar measurement vector z. Additionally, the acts comprise iteratively performing a measurement update using the measurement vector z, with velocity information incorporated therein, and a linear Kalman filter until correct velocity values are determined.

The invention discloses a hydrogel phase state identification method and system based on dual-polarization radar networking fusion, and relates to the technical field of hydrogel phase state identification. The method comprises the following specific steps: acquiring dual-polarization radar observation data from a plurality of radar stations; performing data quality evaluation on the dual-polarization radar observation data to obtain qualified data; qualified data are interpolated into a unified grid, networking fusion is performed through an inverse distance weight algorithm, a data set is constructed, and the data set is divided into a training set, a test set and a verification set; constructing a convolutional neural network, training the convolutional neural network by using the training set, and extracting hydrogel particle features in the training set; and after the training set finishes training, verifying the convolutional neural network by using the verification set, carrying out cycle training for multiple times to obtain a phase state identification model, and carrying out hydrogel phase state identification through the phase state identification model. According to the method, a hydrogel classification result with high robustness and accuracy can be obtained, the method does not depend on manually set weight coefficients, and the phase state identification process is objective.

The invention provides a novel spatial micro-motion target identification method based on a radar network system, and the method comprises the following steps: building a target micro-motion model and a signal model, and constructing a data set of an RCS sequence, a time Doppler image and an HRRP sequence for the spatial micro-motion target identification of a networking radar system; constructing an adaptive feature fusion sub-network; xCA and LA-Att modules with linear complexity are introduced, fine-grained features are effectively extracted, self-adaptive weighted fusion of multi-domain features is realized by adopting a CAFM module, and information useful for recognition is effectively enhanced; and designing a time-space modeling sub-network based on BiGRU and double-graph fusion. According to the method, multi-band and multi-view target features can be obtained, and more accurate information is provided for identification of a spatial micro-motion target; according to the method, the feature information of each radar in the heterogeneous radar network is fully utilized, the recognition precision of 96% or above can still be obtained under the condition that the signal-to-noise ratio is 0dB, and the effectiveness and robustness of the method are obvious.

The invention discloses a phased array radar adaptive cooperative scanning method for severe convective weather, and belongs to the technical field of meteorological radar detection. The method comprises a central cooperative control module, a data analysis module and a distributed phased array radar network. Basic scanning is executed through the phased array radars, and the boundary and the core of the severe convective region of interest are identified and drawn in real time through threshold segmentation and a region growing algorithm; the data analysis module extracts characteristic parameters and calculates a dynamic threat index; the central cooperative control module constructs a global state vector and generates a scanning task instruction for each radar by using a multi-agent depth deterministic strategy gradient algorithm; after scanning is executed, the central module fuses observation data to generate a high-temporal-spatial-resolution three-dimensional meteorological data body and calculates a reward value to update algorithm parameters; according to the invention, multi-radar adaptive cooperative scanning is realized, the monitoring precision and efficiency of severe convection weather are improved, and radar resource allocation is optimized.

The invention belongs to the technical field of radars, and discloses a radar networking anti-interference method based on a digital array radar software definition multifunctional digital radio frequency technology. Various working modes of conventional radar narrowband and broadband detection, multi-station cooperative detection and anti-interference, external radiation source cooperative detection, single-station / double-station MIMO detection, channelized external electromagnetic environment cognitive reconnaissance, cooperative interference, detection and drying integration, multi-platform communication and the like can be realized at the same time. High-isolation signal frequency diversity is realized by using a wide-narrow band signal receiving and transmitting channelization technology, effective coding isolation diversity is realized by using coding pulses, and multifunctional signal time diversity is realized based on partial function time division multiplexing. According to the method, a set of broadband hardware system with composite functions is reused, electronic functions required by a radar networking system are achieved through different software, the purpose of software definition functions is achieved, and meanwhile the anti-interference capacity of the networking system is enhanced.

Various technologies described herein pertain to systems and methods for increasing radar resolution by, for example, combining radar information. In one embodiment, beamforming is performed using radar units that are individually coherent but collectively do not need to be coherent. Each radar transmits and receives its own signal to process and generate target information including beamforming information and / or virtual receiver channel information. The target information from each radar is then merged or summed into a combined beamforming based on all the target information received from all the radar units. When the radar units used in this manner are separated by a distance, the resulting beamforming information is representative of an aperture / resolution based on the total space or distance between the radar units. Thus, having an improved resolution, benefits such as improved target resolution (e.g., size, position, and detection) can be achieved.

The invention relates to the technical field of data transmission, and discloses an FPGA-based radar network real-time data transmission system, method, device and medium, the system comprises a network port transmission module, a high-speed interface transmission module and a high-speed optical port transmission module, radar instruction control information of a central machine is transmitted to an FPGA through a network port chip, and the high-speed optical port transmission module transmits the radar instruction control information to the FPGA; the radar state information is transmitted back to the central machine; the high-speed transmission interface is used for transmitting the radar instruction control information in the FPGA to the digital signal processor, the radar instruction control information transmitted to the digital signal processor is subjected to signal processing, radar control parameters are obtained, and the radar control parameters are transmitted to the FPGA through the high-speed transmission interface; the radar control parameters in the FPGA are transmitted to the radio frequency front end through the high-speed optical port, the radio frequency assembly is configured according to the radar control parameters in the radio frequency front end, and echo information of the configured radio frequency assembly is transmitted to the FPGA. According to the invention, the efficiency of radar network data transmission can be improved.

The application relates to the technical field of digital signal processing, and provides an intelligent data analysis method and system based on a distributed radar network. The intelligent data analysis method based on the distributed radar network comprises the following steps: acquiring working parameters of all radars at present based on a sensor interface; preprocessing the working parameters to generate attribute parameters; determining an utility function representing a radar working effect based on the attribute parameters, determining a dynamic selection strategy according to the utility function, and constructing a radar network topology to collect radar signals; encrypting the radar signals through a blockchain technology to generate encrypted data; and transmitting the encrypted data to a cloud server. Through the construction of the radar network topology, the scheme can adapt to different application scenarios and requirements, improve the flexibility and scalability of the radar network, enhance the data transmission efficiency and security, and realize real-time acquisition, safe encryption and automatic transmission of radar network data.

The invention belongs to the technical field of spaceborne distributed radars, and discloses a network optimization method for spaceborne distributed radar multi-node synchronous link construction. The method comprises the steps of establishing a distributed multi-satellite system, performing phase synchronization and improving network stability. Aiming at the problems that the number of distributed radar nodes is large and phase synchronization is needed in cooperative work, in the prior art, on one hand, the more complex the network structure is, the longer the link is, the more synchronization error accumulation is; and on the other hand, when the satellite moves, the positions of the nodes can be changed, or when a certain node is unstable, the whole network can be paralyzed. Compared with the prior art, by dynamically evaluating the signal-to-noise ratio and the mutual shielding condition of multiple satellites, the system can adapt to environmental changes, the connection between radar points is optimized, the radar network is more effectively constructed, and the performance of the network is improved.

A method for operating a cooperative multiple-input multiple-output (MIMO) radar network with a plurality of analog radar sensors and at least one digital radar sensor. The method includes determining the deviation of the transmission time points and transmission frequencies of at least the plurality of analog radar sensors in relation to one another, and adjusting the transmission time points, reception time points, and transmission frequencies of the signals of at least the plurality of analog radar sensors to one another. A method for interference detection and interference avoidance is also described. A cooperative multiple-input multiple-output (MIMO) radar network including a plurality of analog radar sensors and at least one digital radar sensor is also described.

This invention designs a method for optimizing networked radar station placement based on a genetic algorithm. Under distributed interference conditions, the optimal placement of networked radar stations is crucial. Existing networked radar station placement schemes are generated solely based on constraints and are suboptimal. This invention combines constraints with a genetic algorithm to optimize, calculate fitness expressions, and perform genetic operations to obtain an optimal station population. By using the genetic algorithm to rationally configure the positions of radars within the network, the radar network's detection area can be expanded while effectively monitoring key detection areas, thereby improving the anti-interference capability of the networked radar system.

The application discloses a forward scattering radar echo parameter extraction method based on GNSS, and comprises the following steps: 1, forward scattering signal extraction; 2, using the Rényi entropy of the smooth pseudo-Wigner-Ville distribution to judge whether the forward scattering signal contains a target scattering signal; 3, using a sliding window to analyze the frequency domain characteristics of each signal segment of the target scattering signal, and judging whether a target crossing event occurs; 4, using a smaller sliding window to analyze the signal segment of the crossing event in sections, calculating the time domain statistical characteristic value of the signal segment in the sliding window, and extracting an optimal signal; 5, using the optimal signal to estimate the target crossing Doppler slope; and 6, using the optimal signal to estimate the target crossing time. The application can realize preliminary judgment of the relative position relationship between a target and a baseline, can realize target crossing Doppler slope estimation and target crossing time estimation of a forward scattering radar echo, and can be popularized to a forward scattering radar network of platforms such as the ground, the sea surface and the air.

The application discloses a kind of distributed space-based radar networking tracking methods based on message passing, based on the distributed space-based radar networking of multiple satellite platforms, antenna array, transmitting system, receiving system, radar power etc., the method comprises: the sequence of first target motion state, target visible state, data association and latent variable in joint observation variable are described using factor graph;Based on the connection relationship of variable node and factor node in factor graph, the approximate solution of joint posterior probability density is solved using BP-MF combined approximation method;According to the approximate solution of joint probability density, the target is tracked.The present application is based on the distributed space-based radar networking, combines factor graph and uses BP-MF combined approximation method to convert the solution of high-dimensional posterior probability density fitting into the solution of low-dimensional posterior probability density product, solves the problem of cumulative propagation of estimation error and identification risk in the case of guaranteeing networking performance using distributed networking tracking method, avoids.

The invention particularly relates to a networking radar data fusion analysis method and system. The method comprises the following steps: calling map data, and configuring radar networking configuration parameters according to a currently configured target scene and radar performance parameters; configuring multi-target trajectory data; the multi-target trajectory data comprises a target type corresponding to a target scene and original trajectory data; random noise data and / or false alarm points are added to the original track data to generate primary trace point data, and the primary trace point data are input to the radars so that the radars can perform target tracking based on the primary trace point data, and a simulated track is output; acquiring a detection trace point output by each radar, performing track fusion processing on each detection trace point, and generating a corresponding fusion track; and comparing the fused track with the multi-target track data to obtain corresponding track precision evaluation data. According to the method, data fusion simulation of various different scenes can be realized; and real-time analysis of the data can be supported.

The application discloses a heterogeneous networked radar space registration method based on adaptive grid reconstruction, which comprises the following steps: 1, constructing a radar network system model, presetting related parameters of the radar network system, and initializing the related parameters; 2, obtaining a space sampling unit association group of each grid, and merging grids with the same space sampling unit association group into a reconstructed overlapping area; 3, obtaining a space sampling unit association group of each reconstructed overlapping area, and forming a set; according to the set, an average registration rate of a plurality of randomly distributed point targets is obtained, and a local mismatch rate of each radar station and other radar stations is obtained; if the average registration rate is greater than or equal to a preset average registration rate threshold value, and the local mismatch rate is less than or equal to a preset local mismatch rate threshold value, the optimal grid side length is determined; 4, obtaining a calibration point of the reconstructed overlapping area corresponding to the optimal grid side length. The application effectively improves the registration accuracy.

This invention relates to the field of three-dimensional cloud field forecasting technology, and specifically to a spatially scalable forecasting method, system, device, and medium for three-dimensional cloud fields. The method includes: constructing a first basic training set based on preprocessed first historical radar network data; inputting the first basic training set into a model to obtain an initial forecasting model; inputting various specialized historical data into the initial forecasting model to train specialized identification capabilities, obtaining a specialized enhancement model; constructing a second basic training set based on preprocessed second historical radar network data, and processing the second basic training set based on the specialized enhancement model to select and construct multiple specialized training sets; inputting the second basic training set and the multiple specialized training sets into the specialized enhancement model for multi-resolution joint training to obtain a target forecasting model. This method solves the problems of insufficient spatial adaptability and specialized identification capabilities of three-dimensional cloud field forecasting models under complex weather conditions.

The present invention discloses a multi-laser radar autonomous network construction system, method and terminal based on adaptive registration, and relates to the technical field of network construction and network information processing. Multiple laser radars are used to register and fuse the point cloud images of different radars using a point cloud registration algorithm. The point cloud registration uses 4PCS for coarse registration and Trimmed ICP for fine registration, so that the laser radars in the same indoor environment automatically form a radar network and obtain the fused indoor environment point cloud. The data is saved locally and in the cloud at the same time, and the user changes the corresponding registration parameters or obtains the original point cloud data through the cloud. The present invention is a multi-laser radar autonomous network construction system based on adaptive registration designed for home-based elderly care projects. The user can remotely view the laser radar network status and indoor environment point cloud images in the elderly's residence. Through the radar network and environmental point cloud data, the user can use it in the further design and use of home-based elderly care projects.

The invention discloses a synthetic aperture imaging method of an orthogonal frequency division multiplexing signal based on backward projection, and belongs to the technical field of radar imaging. According to the method, in the process of carrying out synthetic aperture imaging by utilizing OFDM signals, firstly, range compression is carried out, range direction compression is carried out by adopting a matched filtering thought, then range direction interpolation is carried out, range direction interpolation is carried out by adopting a frequency domain zero filling thought, then an imaging area is divided, the distance from each azimuth moment to a radar grid point is calculated, and the distance between each azimuth moment and the radar grid point is calculated. And finally, phase compensation and coherent superposition are carried out on the data at each azimuth moment, and the spatial position of the target in the imaging area is reconstructed point by point. According to the method, each pixel point in the imaging area can be accurately calculated, the spatial positions of all targets in the imaging area are reconstructed, the imaging precision is improved, the image quality is improved, and the good imaging effect is achieved under the near-field condition.