451 results about "Radar measurement" patented technology

The invention discloses a geological disaster deformation monitoring method based on an airborne laser radar, and belongs to the technical field of geological disaster monitoring and early warning. The monitoring method comprises the following steps: acquiring ground point cloud data of a target area in different periods through an unmanned aerial vehicle airborne laser radar measurement system; filtering the ground point cloud data of the target area in different periods to obtain real ground point cloud data of the target area in different periods; the real earth surface point cloud data of the target area in different periods are subjected to the following processing: generalization processing; based on a point cloud elevation difference algorithm of plane fitting and space fitting, calculating change conditions of real earth surface point cloud data of the target area in different periods according to a time sequence; and finally obtaining deformation areas of the target area in different periods according to the change conditions of the real earth surface point cloud data of the target area in different periods. The method is high in precision, is more comprehensive, and provides data support for monitoring and early warning of geological disasters.

The invention provides a maneuvering target intelligent tracking method based on a self-attention mechanism and physical constraints, and the method comprises the steps: carrying out the coordinate transformation of original radar measurement data, obtaining a trace point under a Cartesian system, and calculating a Sigma point set of a target state vector of each time step of an initial window; for the n sampling points, Sigma points are calculated; performing normalization processing, and inputting the normalized Sigma point sequence into the prediction model to generate a prediction result; configuring physical constraints in the loss function, wherein the physical constraints comprise speed constraint loss and acceleration constraint loss; the prediction result is combined with an insensitive Kalman filter, and the real-time correction capability of the insensitive Kalman filter is utilized. And outputting the final estimated values of the position, the speed and the acceleration for a radar tracking system to display. Compared with an IMM interactive multi-model method, the accuracy of the three-dimensional maneuvering target tracking performance is improved, and compared with an existing maneuvering target intelligent tracking method, the prediction accuracy and efficiency are improved.

The invention discloses a geological disaster risk intelligent pre-judgment method based on deep learning, and relates to the technical field of geological disaster monitoring and early warning. According to the method, high-precision alignment and feature extraction can be automatically performed on monitoring data with different temporal-spatial resolutions and different physical meanings, such as optical remote sensing, radar measurement, laser point cloud and the like, uniform and information-rich representations are generated, a solid data foundation is laid for subsequent accurate prediction, and the limitation of data splitting application in a traditional method is overcome; a space-time diagram with slope units as nodes is constructed, an attention mechanism diagram convolutional network with hydrological directivity introduced is utilized, and the model can accurately describe the spatial propagation process that slope substances migrate and accumulate along with a confluence path and block a river channel under the rainfall condition; meanwhile, the time sequence module effectively learns the influence of the past hydrological state on the future evolution trend.

The invention discloses a sparse cloth double-array element multi-frequency ambiguity resolution interference angle measurement method and system, relates to the technical field of radar measurement, realizes design of a multi-frequency signal frequency selection criterion, and further realizes non-ambiguity and high-precision angle measurement of all angles in an angle range required by engineering. According to the technical scheme, a physical baseline length and a reference frequency are set according to a layout space; deriving a plurality of signal carrier frequency design criteria according to the Chinese remainder theorem; calculating the carrier phase difference of the double-array-element receiving signals under different signal carrier frequencies; and reconstructing the congruence equation set, and solving the congruence equation set to solve ambiguity so as to obtain a target angle estimation value.

A method, for determining a dynamic occupancy grid, includes: obtaining radar measurement data from at least one radar sensor of an apparatus; obtaining camera-derived data based on at least one image obtained by at least one camera of the apparatus; and determining the dynamic occupancy grid based on the radar measurement data and the camera-derived data.

Techniques are disclosed to build a map for an area around at least a route traversed by a moving platform. An integrated navigation solution for a device within the moving platform is generated using motion sensor data obtained from a sensor assembly of the device and absolute navigational information for the platform. The integrated navigation solution is then used to project radar measurements obtained from at least one radar of the platform onto the area so that the map is built using the projected radar measurements.

The invention provides a ground-based unmanned aerial vehicle positioning scheme based on event camera and millimeter-wave radar high-frequency fusion, and belongs to the technical field of the Internet of Things. Event stream data of an unmanned aerial vehicle are acquired based on an event camera; acquiring radar measurement data of the unmanned aerial vehicle based on a millimeter wave radar; and based on the event stream data and the radar measurement data, carrying out time synchronization cooperative tracking processing on the unmanned aerial vehicle to obtain ground positioning measurement data of the unmanned aerial vehicle. According to the technical scheme of the invention, the method can achieve the stable high-precision and low-delay ground positioning of the unmanned plane through the coordination of the ultrahigh sampling frequency characteristics of the event camera and the millimeter-wave radar.

The invention discloses a fan blade clearance intelligent monitoring method based on multi-modal fusion. A laser radar and a visual sensor are adopted to collect point cloud data and image data of the fan blade; environment parameters are collected, validity judgment is conducted on the point cloud data and the image data of the fan blade according to the environment parameters, and radar monitoring data and visual monitoring data are obtained; modeling the fan blade according to the radar monitoring data to obtain a three-dimensional model of the fan blade, and further obtaining a radar measurement value of the blade clearance according to the three-dimensional model of the fan blade; performing image segmentation, edge extraction and depth estimation on the visual monitoring data in sequence to obtain a visual measurement value of the blade clearance; and the radar measurement value and the vision measurement value of the blade clearance are combined, and a multi-modal fusion algorithm is adopted for processing to obtain the fusion clearance distance of the fan blade. The accuracy and real-time performance of fan blade clearance monitoring are remarkably improved, blade collision accidents can be effectively prevented, and reliable guarantee is provided for safe operation of a wind turbine generator.

A design method of a trust region satellite-borne dual-base interference SAR system is provided, relating to the field of radar measurement. Firstly, error sources of the interference SAR system are classified and analyzed, phase errors caused by image decoherence are calculated according to wave positions, and an analytical expression of baseline-related errors is reserved; a maximum phase error caused by imaging processing and an electronic device are estimated; and a baseline error is estimated. Then, the phase errors and the baseline errors are converted into elevation errors through an elevation fuzzy number, thereby obtaining an analytical expression of the elevation errors and the baseline parameters (length and dip angle). With a relative height measurement accuracy index of the system as an optimization object, a feasible solution interval between the baseline length and the baseline dip angle of the system is solved through a trust region algorithm. A minimum value of the baseline length is corrected according to a flying-around safety distance of a dual-satellite formation. According to the method of the present disclosure, the design of the satellite-borne dual-base interference SAR system can be guided, so that the satellite-borne dual-base interference SAR system is ensured to carry out terrain elevation surveying and mapping tasks with high accuracy and high reliability.

The utility model provides a multi-laser radar fusion ship loader non-blind area measuring system, which relates to the field of laser radar measurement and comprises a ship body, a multi-laser radar fusion measuring device, a ship loader and a mechanical arm. The mechanical arm clamps the upper end of the multi-laser radar fusion measurement device; the mechanical arm is movably arranged on the ship loader, the moving route of the mechanical arm is from the bow to the stern of the ship body, and the mechanical arm is always located on the center line above the ship body. According to the utility model, the two long-distance laser radars are longitudinally installed, the high-precision holder is equipped, and the holder rotates at a low speed and at a small angle, so that dynamic splicing of scanning data is realized, accurate point cloud data can be rapidly obtained in a short time, data acquisition efficiency and precision are greatly improved, and the system is suitable for large-scale popularization and application. Through the installation of two long-distance radars and the cooperation of the other two short-distance radars, the non-blind area type measurement of the ship body is realized.

The invention relates to the technical field of radar measurement, in particular to a radar height measurement and radio frequency transceiving integrated system which comprises a signal processing module, a channel linkage scheduling module, a path stability judgment module, a frequency distribution management module and a positioning path feedback module. According to the invention, through amplitude peak point and time drift extraction, energy sudden change identification precision is enhanced, signal feature discrimination is improved, a screening channel is matched by using a beam main lobe and an energy center, efficient coupling of direction and energy is realized, path stability analysis introduces power attenuation and energy continuity evaluation, and available section identification accuracy is improved. The signal-to-noise ratio and the channel stable value are considered in frequency selection, the path spectrum utilization continuity is enhanced, frequency mapping is combined with round-trip time difference and height point coverage, the vertical positioning precision and the beam drop point judgment capability are improved, and the adaptability and reliability of radar measurement in a dynamic environment are integrally enhanced.

The invention discloses a takeoff point rear side operation safety interval calculation method and system under the influence of engine jet flow, and the method combines laser wind finding radar measurement experiment, data assimilation, computational fluid dynamics (CFD) numerical simulation and other methods, and measures the engine jet flow data of a takeoff aircraft at an airport runway end through a laser wind finding radar; constructing a double-engine nozzle model by using a computational fluid mechanics method, correcting a numerical simulation model by using a data assimilation method in combination with high-credibility laser radar wind measurement experimental data, and calculating an influence distance of typical aircraft engine jet flow; a model of the airplane under the influence of engine jet flow is established by using a CFD method, the model and the model are combined to calculate the minimum safety interval of rear side crossing, and reliable data reference is provided for a multi-runway airport to use a take-off point rear side runway crossing mode. The accurate safety interval between the front and rear airports is defined, and the overall operation efficiency of airports in China is remarkably improved.

The invention discloses a laser radar-assisted wind power generation wind shear modeling method, and relates to the technical field of wind shear modeling, and the method comprises the steps: collecting the wind speed measurement data of a laser radar at a plurality of heights in a target fan region, and constructing a measurement volume integral operator matrix; constructing a unit induction field correction model based on large eddy simulation in combination with a gradient boosting tree; coupling the measurement volume integral operator with the unit induction field correction model, and obtaining a high-precision wind speed vertical section and a corresponding wind shear parameter through inversion; on the basis of the high-precision wind speed vertical section and the corresponding wind shear parameters, physical constraints are fused, a wind shear model is generated, and uncertainty evaluation is carried out; according to the wind shear modeling method, the problems that the measurement error of the laser radar is difficult to correct, the wind shear modeling lacks the physical constraint and the result credibility cannot be quantified are solved by constructing the volume measurement integral operator and the unit induction field correction model for coupling inversion and fusing the physical constraint and the Bayesian uncertainty evaluation method.

The invention discloses a slope monitoring data calibration and three-dimensional point cloud matching method, belongs to the field of monitoring data calibration, and aims to improve orientation errors caused by the fact that global satellite positioning and navigation system measurement endpoint errors and equipment length problems are not fully considered in existing slope radar measurement. The method solves the problem of position deviation of a monitoring result caused by the fact that the position of a deformation area is monitored, breaks through the limitation of insufficient precision when a traditional radar image is converted into geographic space coordinates, improves the accuracy and reliability of data, remarkably improves the position precision of slope radar monitoring data, and enables the position monitoring of the deformation area to be more accurate. The high-precision requirement of slope stability monitoring is met, reliable data support is provided for fine monitoring of slope stability, potential safety hazards can be found in time, and corresponding measures can be taken.

The invention relates to a sparse cloth double-array-element phase comparison and double-frequency phase solution ambiguity radar angle measurement method and device, and belongs to the technical field of radar measurement. The method specifically comprises the following steps of: 1, performing phase comparison measurement on sparse cloth double array elements at a dual-carrier frequency and a lower dual-channel to obtain a phase difference between the array elements so as to obtain a fuzzy coefficient containing a phase error; according to the fuzzy coefficient, determining constraint conditions of dual-frequency and carrier wave values; step 2, under the constraint condition determined in the step 1, selecting a radar signal working frequency, and constructing a virtual short baseline according to the dual-array-element phase difference under different frequencies; and step 3, based on a virtual baseline ambiguity resolution method, calculating to obtain a non-ambiguity high-precision one-dimensional angle measurement angle.

The invention provides a high-dynamic weak space target space-based radar real-time measurement method and device, and belongs to the technical field of radar measurement. According to the method, maximum likelihood estimation is carried out by using search parameters to obtain target parameters. Selecting search values of radial relative acceleration and jerk in the search parameters, and determining upper and lower limits of a radial relative speed value according to a circular section where a radar search ball and a target position error ball intersect; according to the constraint relation of the radial relative speed to the radial relative acceleration, converting the upper limit and the lower limit of the value of the radial relative speed into a radial relative acceleration range, and selecting a radial relative acceleration search value from the radial relative acceleration range; the search values of the relative distance, the radial relative speed and the radial relative acceleration are utilized, and the search value of the radial relative jerk is uniquely determined through calculation. Compared with a traditional method, the method has the advantages that the parameter search dimension is reduced, the operand can be remarkably reduced, and the method can be implemented on a space-based platform in real time.

The invention relates to the technical field of target tracking, and discloses a maneuvering target tracking system and method based on hybrid coding and UKF decoding. The maneuvering target tracking method comprises the steps of obtaining radar measurement data of a target position at each moment based on a target trajectory; the method comprises the following steps: encoding radar measurement data by adopting an attention-GRU network to obtain a target state encoding value; based on the target state coding value, obtaining a corrected target state noise covariance matrix, a corrected target state measurement noise covariance matrix and a corrected state initial covariance matrix by adopting an expectation maximization algorithm; and performing UKF decoding calculation on radar measurement data by adopting the corrected target state noise covariance matrix, the corrected target state measurement noise covariance matrix and the corrected state initial covariance matrix to obtain a target position. Model parameters such as noise variance information do not need to be preset, the tracking precision of the maneuvering target can be effectively improved, and noise interference is weakened.

The invention discloses an unmanned aerial vehicle target detection and tracking method based on thunder-vision fusion, and the method comprises the following steps: obtaining camera measurement data obtained through a camera and radar measurement data obtained through a radar, and carrying out the alignment of the camera measurement data and the radar measurement data; a camera is used as an auxiliary sensor to screen radar detection; and fusing the radar measurement data and the camera measurement data, outputting the fused data to the tracker, and generating and updating the track of the target identified in the field of view of the sensor. According to the invention, through fusion of the double-level radar sensor and the visual sensor, the radar and visual data are preliminarily integrated and processed before the target is tracked to reduce noise and clutter, so that the calculation efficiency can be improved, the situation that the radar is submerged by environmental noise due to weak sensor signals during low-altitude flight can be prevented, and the reliability of flight is improved. Therefore, the detection accuracy is improved.

The invention discloses a radar target tracking method based on transport mapping, which adopts a pulse-by-pulse estimation strategy and comprises the steps of initial construction, initial particle generation and pulse-by-pulse updating. A target transfer equation and a radar measurement equation are initially constructed, and an equal-weight particle set is generated to represent initial probability distribution. And at each pulse moment, predicting a target state by using a transfer equation, calculating a measurement predicted value, carrying out downsampling on a high-dimensional measurement signal and the predicted value, constructing transport mapping and updating particles based on state prediction and downsampling data to obtain a posterior state set, and finally solving an average output target state estimated value. The method solves the problem of calculation complexity of particle degradation and high-dimensional measurement data processing in an existing method, improves the target state estimation precision and tracking efficiency, and is especially suitable for a complex nonlinear and high-noise environment. According to the method, high-dimensional measurement data and multi-modal distribution can be processed, particle degradation is avoided, real-time performance and robustness are enhanced, and the method has important application value.

Techniques are disclosed to build a map for an area around a route traversed by a moving platform. An integrated navigation solution based at least in part on obtained motion sensor data for a device within the moving platform is used to build an online map during a first instance of time for the area using perception sensor data, such as, for example, radar measurements and / or optical samples. The integrated navigation solution may then be revised in a second instance of time with a nonlinear state estimation technique that uses a nonlinear measurement model for perception sensor data, wherein integrating the motion sensor data and perception sensor data in the nonlinear state estimation technique is tightly-coupled. Generating the revised integrated navigation solution in this tightly coupled technique includes using the motion sensor data with the nonlinear state estimation technique and integrating the perception sensor data directly by updating the nonlinear state estimation technique using the nonlinear measurement models and the online map information.

The invention provides a paper moisture content measuring method and system based on radar backscattering, and relates to the technical field of radar measurement, and the method comprises the steps: obtaining a to-be-measured target paper package, and determining the dielectric constant of the target paper package; transmitting a radar signal to the target paper parcel according to a preset angle and a preset frequency point, and receiving a returned radar echo signal; calculating a radar backscattering coefficient based on the dielectric constant of the paper package, the surface roughness, the radar parameter and the radar echo signal; based on the backscattering coefficient, a mathematical model between the backscattering coefficient and the water content in the paper is constructed through a linear regression method, and the mathematical model is solved to achieve measurement and calculation of the water content in the paper parcel. Through signal processing and image display, the moisture content in the paper can be intuitively reflected.

The invention provides a spatial transformation linear fusion tracking method for a Doppler radar, and the method comprises the steps: firstly constructing a state space of a to-be-tracked target based on the distance of the target relative to the radar, the Doppler speed, the angle and a target speed module; at a preset initial moment, using Doppler radar measurement and target prior information to initialize target related parameters to obtain an initial state; then, the posterior state of the state space of the target to be tracked at the current moment is converted into a Cartesian coordinate system, the state model is used for prediction and then is switched back, and a predicted value at the next moment is obtained; then, according to a linear Kalman filtering theory, filtering and updating the predicted value and the radar measurement value to obtain an optimal state estimation value at the next moment; and finally, the steps of initialization, state transition prediction and filtering update are continuously repeated until target tracking is completed, and the method effectively realizes continuous and accurate tracking of the Doppler radar on the target.

A radar measurement method and an apparatus are disclosed, which relate to the field of communications technologies, and are used to support radar measurement in a wireless local area network (WLAN). The method includes: An access point (AP) generates a first frame, where the first frame includes radar measurement information. Then the AP sends the first frame to M stations (STAs), to configure the way the M STAs perform radar measurement. This application is applicable to a radar measurement procedure.

The invention discloses a tight coupling laser inertial vision fusion method based on a merged probability voxel map, and relates to the technical field of vision fusion. Comprising the steps of performing display parametric modeling based on radar measurement noise, and constructing a probability voxel plane model; combining the planes which may have a coplanar relationship, and adding the laser radar point clouds in the determined effective voxel planes into a global map; projecting the global map into an image frame to obtain a tracking point, tracking by using an LK optical flow method, and meanwhile, further eliminating an abnormal point by using a random sampling consensus algorithm based on a dynamic Bayesian network; and based on image information acquired by the camera, optimizing and maintaining the global map by minimizing frame-to-frame pixel errors and frame-to-map color errors and updating the global map. According to the method, the performance of the laser inertial visual odometer is improved by combining a framework of efficient coupling radar, IMU and camera information of the probability voxel map.

The invention relates to a three-coordinate air radar height measurement value correction method based on joint estimation, and belongs to the technical field of multi-radar data fusion. According to the method, a relative system error thought is adopted, observation data of main and auxiliary station radars on a typical air route target are selected, and a height relative system error joint calculation model derived from radar asynchronous measurement data is established through three-dimensional unified rectangular coordinate conversion, linear parameter estimation, time registration point calculation and the like; and the reliability of an error accumulation estimation result is ensured through operations such as singular value elimination. Experimental results show that the follow-up height measurement value of the auxiliary station radar is corrected according to the cumulative estimation result, the average difference of the height values of the track lines is reduced by one order of magnitude, the error correction effect is very ideal, and the requirements for air radar height estimation and fusion precision in engineering practice are met. The estimation method provided by the invention is scientific, reasonable in scheme implementation steps and very high in operability and practicability.

The invention discloses a visibility inversion method and device of a laser radar, equipment and a storage medium, and relates to the technical field of laser, and the method comprises the steps: determining a detection range boundary based on a laser radar voltage value and a preset threshold value; synchronously measuring the visibility in a segmented manner by using a ground single-point measurement visibility meter and a laser radar visibility meter, and performing inversion to obtain a function value; constructing a joint relation model by combining a laser radar equation according to the average error of the function value and the radar measurement signal, and generating a parameter mapping relation lookup table; acquiring signal intensity by means of a near-field visibility measuring device, and determining a target laser radar ratio and an extinction coefficient through the look-up table; and finally, resolving an extinction coefficient profile and inverting a visibility profile by adopting a Fernald inversion algorithm in combination with the laser echo signal path, the target extinction coefficient and the laser radar ratio. The efficiency of laser radar visibility inversion is improved.

The invention discloses a radar measurement method, device and equipment, a medium and a product, and relates to the technical field of radar signal processing. According to the method, a space angle is divided into a main lobe area and a side lobe area; determining a phase modulation strategy of twice observation of the radar; the phase modulation strategy comprises the steps that phases of a main lobe area are kept consistent in two observations, and the phase difference of a side lobe area is 180 degrees; according to a phase modulation strategy, determining a directional diagram of expected radiation of the array antenna in two times of observation, and optimizing a unit excitation weighting vector in two times of observation to obtain an optimized value of the unit excitation weighting vector; according to the optimization value, performing phase modulation on a transmitting signal of the array antenna; and coherent superposition is carried out on echo signals reflected by the target and received by the radar in two times of observation. On the premise that the array size is not changed, the anti-interference capability and the spatial resolution of the radar are remarkably improved, and the monitoring precision of the radar on parameters such as distance, speed, deformation and angle is effectively improved.

Disclosed are embodiments for determining the position and speed of a projectile in three-dimensional world coordinates using a single camera and radar. In some embodiments, a method comprises: determining a zero radial speed time of the projectile based on radar measurements of the projectile; determining a radial speed of the projectile at a particular time based on the radar measurements; determining a radial speed slope at the particular time based on the radial speed measurements; determining a two-dimensional image point of the projectile at the particular time; determining a depth scale coefficient at the particular time based on the zero radial speed time, the radial speed, the radial speed slope, the image point, and a homographic transformation; and determining a position of the projectile in space at the particular time based on a three-dimensional position of the camera, the depth scale coefficient, the image point and the homographic transformation.

The invention relates to the field of radar detection, in particular to an unmanned aerial vehicle radar cross-sectional area full-angle measurement method, which comprises the following steps of: measuring the radar cross-sectional area of a to-be-measured unmanned aerial vehicle by using an unmanned aerial vehicle with radar equipment as a measuring device; the measuring device and the to-be-measured unmanned aerial vehicle are lifted to a preset height, and the measuring device points the antenna beam direction of the radar equipment to the to-be-measured unmanned aerial vehicle; recording radar output signal power under each group of attitude angles when the to-be-measured unmanned aerial vehicle flies to a specified position with a radar distance R from the measuring device; acquiring position information and attitude angle information of the measuring device and the to-be-measured unmanned aerial vehicle; and aligning the output signal power measured by the radar with the attitude angle of the to-be-measured unmanned aerial vehicle in time, and calculating the radar scattering cross-sectional area at each attitude angle to realize the full-angle measurement of the radar scattering cross-sectional area of the unmanned aerial vehicle. According to the method, the radar cross-sectional area of the unmanned aerial vehicle can be measured at a low altitude, interference of ground clutters on the radar is avoided, and the method is not limited by a measurement space.

The invention relates to the technical field of weather radars, in particular to a method and a device for monitoring key parameters of a weather radar on line by using the sun. By using the sun signal as a stable reference target object, tiny performance change of key parameters in a radar system can be monitored and corrected, so that whether the radar performance is abnormal or not can be identified in time, a worker is guided to calibrate the weather radar in time, the accuracy of measured data of the radar is ensured, and the working efficiency is improved. And the influence of system performance reduction on data quality is avoided. In addition, the key parameter change in the radar system monitored by the embodiment of the invention can also provide reference for manual calibration, and the calibration accuracy is improved.