27 results about "Ground based radar" patented technology

The invention relates to the technical field of deep foundation pit monitoring, and discloses a deep foundation pit micro-deformation InSAR remote sensing method and system and a storage medium. The method comprises the following steps: synchronously acquiring data through a ground radar and an InSAR satellite, and obtaining a point target set and an original scattering characteristic sequence; obtaining a net deformation phase sequence without influence through registration residual correction, phase deduction and weighted fusion processing, and carrying out phase consistency quality control and unwrapping processing to obtain an accumulated deformation quantity sequence; constructing a deformation mechanism correlation characteristic matrix based on correlation analysis of the cumulative deformation quantity sequence and radar reflection intensity amplitude attenuation characteristics; and fusing the deformation mechanism correlation feature matrix and the real-time differential interference image group, extracting deformation rate and phase gradient change, and further generating a deep foundation pit local micro-deformation risk early warning index set. According to the invention, the tiny deformation of the surrounding area of the foundation pit can be effectively detected, potential risks are warned in advance, and the safety and monitoring efficiency in the construction process are improved.

The invention relates to an unmanned aerial vehicle control method considering weather risks, and the method comprises the steps: collecting the flight environment data of an unmanned aerial vehicle in real time, synchronously receiving a cloud evolution map and a wind shear early warning signal of a ground radar, and carrying out the processing, thereby obtaining multi-mode meteorological data; predicting storm intensity distribution in the track area in 2-5 minutes in the future, and generating a three-dimensional threat level grid map; aiming at the conventional meteorological risk, constructing a threat level-evasion strategy mapping table, judging the threat level, calling a corresponding evasion strategy, and guiding the unmanned aerial vehicle to execute a corresponding evasion action; when encountering an extreme condition, activating an anti-interference navigation mode, enhancing flight stability through rotating speed-pitch angle cooperative control, and triggering a standby landing emergency protocol; after the avoidance action is completed, the flight path is re-planned in combination with space-time constraints, and the flight speed is reasonably adjusted. The invention also relates to an unmanned aerial vehicle control system considering the weather risk. According to the invention, the flight safety and stability of the unmanned aerial vehicle under complex weather conditions can be improved.

The present application relates to a kind of unmanned aerial vehicle control method considering weather risk, including the following steps: real-time acquisition unmanned aerial vehicle flight environment data, synchronous receipt cloud layer evolution map and ground radar's wind shear early warning signal, process to obtain multimodal meteorological data;Predict the storm intensity distribution in future 2-5 minutes track area, and generate three-dimensional threat level grid map;For conventional meteorological risk, build threat level-avoidance strategy mapping table, judge threat level, and call corresponding avoidance strategy, guide unmanned aerial vehicle to execute corresponding avoidance action;When encountering extreme situation, activate anti-interference navigation mode, enhance flight stability by rotating speed-pitch angle collaborative control, trigger emergency protocol of alternate landing;After completing avoidance action, re-plan flight path in combination with space-time constraint, reasonably adjust flight speed.The present application also relates to a kind of unmanned aerial vehicle control system considering weather risk.The present application can improve the flight safety and stability of unmanned aerial vehicle under complex weather conditions.

The invention provides a multi-unmanned aerial vehicle cooperative hoisting radar antenna aerial operation device and a coordinate transformation method, and belongs to the technical field of unmanned aerial vehicle control. The device comprises a radar antenna, a device landing base and a multi-rotor unmanned aerial vehicle cooperative hoisting uniform force platform system; the multi-rotor unmanned aerial vehicle collaborative suspension uniform force platform system comprises a plurality of multi-rotor unmanned aerial vehicles, a rigid uniform force connecting ring, a carbon fiber tube, a suspension cable and a rigid connecting arm, the plurality of multi-rotor unmanned aerial vehicles are connected with the rigid uniform force connecting ring through the suspension cable, the carbon fiber tube is arranged on the rigid uniform force connecting ring, and the rigid connecting arm is connected with the rigid uniform force connecting ring through the suspension cable. The back of the radar antenna is provided with a supporting beam, one end of the rigid connecting arm is connected with the carbon fiber tube, and the other end of the rigid connecting arm is connected with the supporting beam. According to the scheme, the target pose of the radar antenna is efficiently and accurately decomposed into the cooperative motion instruction of the unmanned aerial vehicle cluster, and it is ensured that the ground radar antenna becomes a high-stability and high-precision working platform in the air.

A monitoring system (1) for an orbiting space object (5) comprising a ground-based radar system (2) (7) including an antenna (6) with a controllable pointing direction for moving a space observation window (11) within a field of view (12), the pointing direction having a predetermined value (Zref) associated with the space object (5), the monitoring system (1) comprising ground-based optical sensors (3) (7) and a control unit (4) configured to determine a first orbital restitution (O1) from first positions (P1) of the space object (5) measured by the optical sensors (3), and, if the first orbital restitution (O1) crosses the field of view (12) of the radar system (2) outside the space observation window (11) associated with the predetermined value (Zref) of the pointing direction, to determine a command for the pointing direction of the antenna (6). Abstract figure: Figure 1

An unmanned aerial vehicle includes a control station for controlling a first co-operating unmanned aerial vehicle, a radar system or ground based radar system configured to scan for objects within a detection coverage range and to provide scan data indicative of objects detected within the coverage range, and processing circuitry configured to generate full data type radar plots based on obtained scan data, select irregular type radar plots from full data type radar plots, generate and store one or more UAV object tracks, receive telemetric data and / or transponder data for said first UAV, determine for each UAV object track whether there is a match between data of the UAV object track and corresponding telemetric data and / or transponder data for said first UAV, and classify the UAV of a UAV object track as a first co-operating UAV when predetermined matching conditions are fulfilled.

The invention discloses a road surface defect detection method and system based on deep learning, and the method comprises the steps: firstly, synchronously collecting an original visible light image, an original infrared thermal imaging image and original ground radar data of a target road surface, and carrying out the preprocessing and data enhancement in sequence; transmitting the standard visible light image, the standard infrared thermal imaging image and the standard radar data to a feature extraction module, and extracting visible light features, infrared features and radar features; secondly, the visible light features, the infrared features and the radar features are mapped to a shared space after being subjected to feature splicing, and a fusion feature vector is generated through a multi-head attention mechanism and a feedforward neural network; and finally, fusing the feature vectors, and outputting defect types of the target road pavement in a classified manner through an output layer. According to the invention, the pavement surface and internal defects are synchronously detected, and the accuracy of road pavement defect detection is improved.

The application discloses an air-ground cooperative detection networking deployment optimization method, which comprises the following steps: firstly, a mathematical model of ground radar detection sensor networking deployment is established; secondly, a detection area is subjected to gridding treatment, and genetic algorithm is used to optimize the deployment of the ground radar detection sensor networking to obtain a Pareto solution; thirdly, the weak index of each grid of the detection area is calculated to obtain a weak matrix; then, the weak matrix is processed by using the breadth-first search thought to extract and sort weak areas; finally, air-based radar deployment tasks are formulated according to the weak areas, and an air-ground cooperative detection networking deployment scheme is finally generated. The application can make up for the poor detection performance of ground radar networking on low-altitude targets such as unmanned aerial vehicles and the insufficient scheduling mobility, improve the air-frequency domain coverage capability of the ground radar networking and the anti-electromagnetic interference and anti-stealth capability, and make the patrol route designation of the air-based radar detection sensor key task more professional and rigorous.

The invention discloses a radar rainfall deviation correction algorithm based on combination of probability density matching and a climate state ratio method. The radar rainfall deviation correction algorithm comprises collection and preprocessing of ground station observation data, PDF deviation correction of radar rainfall and climate state deviation correction of radar rainfall. According to the invention, effective utilization of rainfall observation data of a ground meteorological station is realized, deviation correction is carried out on a radar networking estimation rainfall product by using a ground station grid analysis field and a ground-radar climate state proportion analysis field, and the deviation between a radar rainfall estimation value and real rainfall is effectively corrected. According to the method, the discontinuity and systematic deviation of space-time distribution of a fusion product are reduced, the adaptability of the fusion product to complex terrains and rapid evolution precipitation scenes is enhanced, collaborative optimization correction of multi-scale and multi-type deviation is realized, and the reliability and service applicability of a radar precipitation product are remarkably improved.

The utility model provides a kind of electronic sounding apparatus and radar detection system based on double channel digital frequency modulation, sounding apparatus includes temperature sensor, humidity sensor, baroceptor, measurement conversion unit, transmitter and receiver, data acquisition module is used to receive temperature, humidity and air pressure signal in high altitude, single-chip microcomputer converts sounding signal into square wave signal and is transmitted to transmitter, transmitter sends square wave signal to ground radar, receiver has answering radar inquiry function, receives the answering signal generated by amplitude modulation ranging inquiry pulse sent by ground radar, inquiry pulse modulation is sent to transmitter, and answer pulse is sent back for ground radar reception;The utility model's sounding apparatus avoids the shortcomings of unstable ranging and easy to be disturbed by continuous wave ranging pulse, and cooperates with ground double channel wind finding radar, and the temperature, humidity, pressure, wind speed, wind direction in 30 kilometers from ground to high altitude, square 200 kilometers in air can be accurately detected.

The application provides a satellite control system, method, electronic equipment and storage medium. The system comprises: a ground radar detection station, a control adjustment system and an excitation emission source. The ground radar detection station is used for detecting position data and attitude data of a satellite relative to the ground in real time, and transmitting the position data and the attitude data to the control adjustment system through a first signal transmission network between the ground radar detection station and the control adjustment system. The control adjustment system is used for determining an excitation signal required by the excitation emission source to emit to the satellite according to the position data and the attitude data. The excitation emission source is used for emitting the excitation signal to the satellite through a second signal transmission network between the excitation emission source and the satellite, so as to control the operation of the satellite and enable the satellite to run on a preset operation orbit where the satellite is currently located. The application can automatically control the operation of the satellite, so as to reduce the operation burden of a satellite tester.

The invention relates to a target tracking method based on multi-pulse response signal coherent accumulation, and the method comprises a calibration mode and a formal working mode: in the calibration mode, an active target is fixed at a known position, and a plurality of pulse response signals emitted by the active target are received; estimating a frequency difference and an initial phase difference between the response signal and the ground radar transmitting signal; in the formal working mode, receiving a plurality of pulse response signals transmitted by the active target, performing frequency and initial phase compensation on the pulse response signals according to the frequency difference and the initial phase difference, and then performing matched filtering to obtain a distance dimension compression result; arranging the compression results of the pulses according to a time sequence to form a fast time-slow time two-dimensional data matrix, and performing Fourier transform on the slow time dimension to realize multi-pulse coherent accumulation so as to obtain distance-Doppler two-dimensional information; and finally, determining the distance scale and Doppler scale of the target through peak detection to obtain the distance and radial speed of the active target.

The application provides a low-cost ground-layered antenna radome plate prepreg forming method and belongs to the field of composite material design and manufacturing. The application solves the existing problems in the processing of the ground-layered antenna radome, the mold for manufacturing the antenna radome is reformed, the mold retains the original functions and performances, and the mold is additionally provided with the functions of continuous heating and heat preservation through the reform, the wet hand lay-up process commonly used for the antenna radome is changed into the process form of the prepreg, the female mold of the antenna radome mold and the matched gland are reformed, the mold is provided with the continuous heating capacity, the middle-low temperature curing prepreg with the content of 45%-50% is selected as the reinforcing material, the product can be cured and formed in the mold without moving, and the low-cost prepreg forming of the ground radar antenna radome is realized.

The application discloses a kind of collapsible loess region road collapse intelligent monitoring early warning system and processing method, belong to collapsible loess region road monitoring early warning and processing technical field, solve the problem that existing detection technology is difficult to comprehensively, intuitively timely monitoring and early warning to road collapse.The present application includes information acquisition device, office management facilities and communication facilities, communication facilities include 3S integrated system, commercial satellite and ground radar system, office management facilities include internet, computer and display device, 3S integrated system and ground radar system are connected with computer through internet respectively, information acquisition device is connected with 3S integrated system.Processing method: the information provided by 3S integrated system and ground radar system is compared, and the classification of road collapse hazard classification is judged, and corresponding collapse treatment measures are taken accordingly.The present application realizes 3S integrated system and ground radar detection system double control, and is more accurate and intuitive for collapse prediction.

The invention discloses an oil field global security and protection coverage method, and aims to solve the problems of fixed distribution of monitoring resources, weak cooperative capability of an unmanned aerial vehicle and a ground radar, lagging of abnormal response and difficulty in timely recognition of a coverage blind area in the prior art. Training an attention mechanism model by using the model data to obtain a region weight; on the basis of radar real-time scanning, patrol or investigation tasks are distributed to the unmanned aerial vehicle according to the weight; radar detection is carried out when abnormity occurs, and the unmanned aerial vehicle is dispatched to carry out supplementary detection when the abnormity is not detected; the unmanned aerial vehicle generates a patrol target according to the weight after completing investigation and automatically returns to charge when the electric quantity is insufficient; and calculating a coverage value according to the coverage conditions of the radar and the unmanned aerial vehicle, generating a blind area early warning and coverage optimization report when the coverage is insufficient, and displaying an equipment state, an abnormal event and a coverage thermodynamic diagram on a monitoring interface. The method is applied to the fields of dynamic security monitoring, coverage optimization and the like of a large-range area of an oil field.

A monitoring system (1) for an orbiting space object (5) comprising a ground-based radar system (2) (7) including an antenna (6) with a controllable pointing direction for moving a space observation window (11) within a field of view (12), the pointing direction having a predetermined value (Zref) associated with the space object (5), the monitoring system (1) comprising ground-based optical sensors (3) (7) and a control unit (4) configured to determine a first orbital restitution (O1) from first positions (P1) of the space object (5) measured by the optical sensors (3), and, if the first orbital restitution (O1) crosses the field of view (12) of the radar system (2) outside the space observation window (11) associated with the predetermined value (Zref) of the pointing direction, to determine a command for the pointing direction of the antenna (6). Abstract figure: Figure 1

The invention relates to the field of artificial intelligence, discloses an AI-based regional weather anomaly intelligent detection and judgment method and system, and aims to solve the problems of insufficient multi-source meteorological data fusion, high static threshold false alarm rate, lack of interpretability and weak dynamic adaptability in the prior art. The method comprises the following steps: fusing satellite, ground, radar and numerical forecasting data, and carrying out space-time alignment and quality control; extracting high-dimensional meteorological state representation through three-dimensional convolution and a graph attention network; detecting the probability, range and intensity of an abnormal event by using a space-time anomaly perception neural network; performing cause tracing in combination with physical constraint verification and an integrated gradient method; and generating a grading early warning instruction and pushing the grading early warning instruction. According to the technical scheme, high-precision, low-false-alarm, high-interpretability and quick-response weather abnormity intelligent detection and early warning are realized.

The invention discloses a train control method and a train debugging system, and relates to the technical field of train control. Through receiving and sending of the radar device, the distance parameter between the tractor and the ground equipment is measured. And in the off state, the controller performs traction removal treatment on the train. And determining the spatial position and the motion state of the tractor based on the relationship between the first distance parameter and the preset distance parameter between the tractor and the ground radar equipment and the relationship between the first speed parameter and the preset speed parameter in order to determine whether the tractor is located in a safe area. According to the method and the system, the collision risk of the tractor and the train can be known according to the traction state and the stopping and moving states of the tractor, namely, the traction state mechanism of the train and whether traction removal or traction input is performed or not are determined, so that the safety of no collision between the train and the tractor is guaranteed. The method is incorporated into a safety prevention and control system to further avoid the risk of collision between the train and the tractor so as to ensure the reliability of test safety.

The invention belongs to the technical field of radars, and discloses a radar echo time delay prediction method and device, equipment, a storage medium and a product. The method comprises the steps of collecting a current echo signal of a ground radar at a current moment, then performing short-time Fourier transform on the current echo signal to obtain a current time-frequency graph, and then inputting the current time-frequency graph into a preset time delay prediction model to obtain a time delay value corresponding to the echo signal. The preset time delay prediction model comprises a preset denoising layer used for outputting a denoised time frequency graph, a preset reversible short-time Fourier transform layer used for outputting a time domain signal, and a preset full-connection regression layer used for outputting a signal time delay. The time-frequency domain can be entered by performing short-time Fourier transform on the echo signal received by the ground radar, and then the current time-frequency graph is input into the preset time delay prediction model, so that the time delay of the echo signal received by the ground radar can be accurately predicted through the preset time delay prediction model under the condition of urban scene shielding and noise superposition.

The utility model discloses a double-frequency broadband large-angular-domain high-gain antenna based on a cavity structure, and mainly solves the problems that the existing antenna cannot meet the requirements of wide frequency band, high gain of a large angular domain near an end-fire direction and conformal installation at the same time. The antenna comprises a radome (1), a metal cavity (2), three sealing rings (3, 7 and 8), two radiators (4 and 5) and a connector (6), the radome comprises a radome front end, a radome flange and an air conditioning cavity from top to bottom, and the influence of the size non-uniformity of the radome on the antenna performance can be eliminated by changing the shape and size of the air conditioning cavity; the two radiators are located in the metal cavity and jointly adjust the angular domain range of the antenna; the first sealing ring (3) is positioned between the antenna housing and the metal cavity; second and third sealing rings (7, 8) are located between the metal cavity and the connector. The antenna has the characteristics of wide frequency band, high gain of a large angular domain near an end-fire direction and easy conformal performance, is high in water pressure resistance and sealing performance, and is suitable for ground radar equipment and submarine radar equipment.

The application discloses a novel non-line-of-sight target detection method and system, and the non-line-of-sight target detection method comprises the following steps: a ground radar transmits a signal to an airborne relay system; the relay system receives and amplifies the transmission signal of the radar, and transmits the enhanced transmission signal to a target to be detected; the target to be detected receives the enhanced transmission signal and generates a return signal; the relay system receives and amplifies the target return signal, and transmits the enhanced return signal to the ground radar; and the ground radar processes the received enhanced target return signal, so that the non-line-of-sight target is detected. The non-line-of-sight target detection system comprises the ground radar, the airborne relay system and the target to be detected. The application amplifies the radar transmission signal and the target scattered return signal by using the airborne relay system, expands the radar detection range, and can detect the non-line-of-sight target which is blocked by high-rise buildings in a city environment.

A soil compactor comprises at least one compactor roller (18, 20) rotatably mounted on a compactor frame (12) and at least one ground radar density measuring arrangement (34) arranged in an internal volume area (VI) of the compactor frame (12).

This invention discloses a three-dimensional positioning method for aerial targets based on distributed ground radar cooperation, comprising: constructing a cross-correlation function by transmitting and echoing signals, and obtaining the range estimate of each ground radar to the target through quadratic fitting; constructing a nonlinear spherical equation system, introducing auxiliary variables for linearization, and iteratively solving it using the Lagrange multiplier method to obtain the initial three-dimensional position estimate of the target; extracting the initial horizontal coordinates, obtaining the altitude correction contribution of each radar based on the geometric relationship between the radar and the target, adaptively selecting the radar with the largest contribution and satisfying the decoupling premise as the optimal correction radar, using its range information to decouple from the spherical range equation to obtain the altitude closed-form solution, and fusing the horizontal coordinates and the corrected altitude to obtain the final three-dimensional position. This invention overcomes the accuracy degradation problem caused by the lack of altitude dimension information and ill-conditioned matrix in traditional algorithms, and significantly improves the three-dimensional positioning accuracy of distributed ground radar for aerial targets.

The application discloses a kind of field end laser radar's calibration method, device, storage medium and terminal equipment, comprising: obtaining the ROS point cloud data of field end laser radar to be calibrated, and display;According to point cloud display result, select ground point cloud;Obtain the first residual equation corresponding to the pose of each ground radar point in world coordinate system and in radar coordinate system;According to the correspondence of Euler angle and rotation matrix of pre-set rotation order, the first residual equation corresponding to each ground radar point is processed according to the correspondence, and the second residual equation corresponding to each ground radar point is obtained;According to the second residual equation corresponding to all ground radar points, residual minimization optimization processing is carried out, and optimization variable is obtained;According to the optimization variable, the external parameter calibration result of the laser radar is obtained.The technical scheme of the application can simplify the external parameter calibration process of laser radar, and improve the calibration accuracy.

The present application relates to a kind of target tracking methods based on the coherent accumulation of multiple pulse response signals, the method includes calibration and official work two modes: in calibration mode, active target is fixed in known position, receives multiple pulse response signals emitted by it, estimates the frequency difference and initial phase difference between response signal and ground radar transmission signal;In official work mode, receive multiple pulse response signals emitted by active target, according to frequency difference and initial phase difference, carry out frequency and initial phase compensation to pulse response signal, then carry out matched filtering to obtain distance dimension compression result;The compression result of each pulse is arranged in time sequence to form fast time-slow time two-dimensional data matrix, Fourier transform is carried out to slow time dimension to realize multiple pulse coherent accumulation, and distance-Doppler two-dimensional information is obtained;Finally, the distance scale and Doppler scale of target are determined by peak detection, and the distance and radial velocity of active target are obtained.

A meteorological parameter-based method for correcting ground-based radar atmospheric parameters includes the steps of: determining reference points based on range bins of a ground-based radar, acquiring mercury thermometer temperatures and electronic meteorological data at the reference points, and constructing a temperature correction model; calculating first atmospheric phases from the electronic meteorological data, identifying stable reference points, and obtaining corrected temperatures of the stable reference points using the temperature correction model; constructing a relative humidity correction model based on the corrected temperatures, and obtaining corrected relative humidities; and performing atmospheric compensation using the corrected temperatures and corrected relative humidities, and determining micro-deformation at a target point based on atmospheric compensation results. This method can not only improve the accuracy of the ground-based radar atmospheric parameter correction method to obtain high-precision and reliable micro-deformation data, but also provide good interpretability, with significant implications for structural health monitoring (SHM) of buildings.

This invention relates to the field of three-dimensional wind field inversion technology using meteorological radar, specifically disclosing a method and system for inverting three-dimensional wind fields based on multi-source data fusion. The invention involves acquiring multi-source data from ground, radar, and satellite sources, performing data cleaning and spatiotemporal alignment; extracting multi-source feature data, performing weighted fusion to construct an initial three-dimensional wind field; performing physical constraint optimization to generate an optimized three-dimensional wind field; performing spatial interpolation and multi-scale feature fusion to expand the optimized three-dimensional wind field, generating a full-space three-dimensional wind field; and verifying and updating the full-space three-dimensional wind field. This invention enables multi-source data acquisition from ground, radar, and satellite sources, performing multi-source feature extraction and weighted fusion to construct an initial three-dimensional wind field, and performing constraint optimization and wind field expansion to generate a full-space three-dimensional wind field. It effectively avoids uncertainties in the lateral and vertical directions of the inversion results and solves the problem of large inversion errors in local areas.