645 results about "Radar measurement" patented technology

A wind-finding method based on fusion of millimeter wave radar data and laser radar data, comprising: S1, acquiring wind-finding radar parameters; S2, on the basis of the wind-finding radar parameters, acquiring system state flag bits of wind-finding radars, determining whether the wind-finding radars work normally, and executing corresponding behaviors; S3, acquiring measurement data of the wind-finding radars at different heights, and caching related parameters; S4, by determining radial wind speed significant bits, selecting a corresponding wind-finding radar, and performing inversion on the wind speed; S5, fusing the wind speeds inverted by the millimeter wave wind-finding radar and the laser wind-finding radar to obtain a fused output wind speed; and S6, outputting a horizontal wind speed and a wind direction corresponding to each height level. According to the wind-finding method based on fusion of millimeter wave radar data and laser radar data, two types of wind-finding radar measurement data obtained simultaneously are fused, improving the data reliability of wind speed and wind direction measurement; and the advantages of different wind-finding radars are fully utilized, improving the overall measurement precision.

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.

The invention provides a quality control method based on laser wind-finding radar data, and the method comprises the steps: taking radial data directly obtained by a laser wind-finding radar as basic data, and fusing the signal-to-noise ratio characteristics and spatial distribution characteristics of abnormal data; quality control such as abnormal value elimination and missing value filling is carried out on the radial wind speed data, and abnormal value effective elimination is carried out on the radial wind speed data, so that the false alarm rate of the laser wind finding radar detection signals is greatly reduced. According to the spatial relationship of the wind speed data detected by the laser wind-finding radar in the radial direction and the tangential direction, effective filling of the radial wind speed is realized by adopting a mode based on frequency statistics and median filtering in the moving window, and the integrity of the wind speed measured by the laser wind-finding radar is ensured.

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 invention discloses a light-weight wind measurement laser radar system based on an unmanned aerial vehicle platform. The light-weight wind measurement laser radar system comprises a servo scanning unit, a radar measurement unit and a system hanging frame, the radar measurement unit adopts a lightweight main body frame, and adopts various lightweight materials in structural design; the internal space of the radar measurement unit is divided into a plurality of different subareas, the plurality of different subareas are arranged in a stacked mode, and the aspects of hardware scheme, composition, stacking mode and the like are redesigned. Hardware and a structure are deeply fused, so that the system has obvious advantages in size and weight, miniaturization and light weight are realized, and the weight index of the radar system reaches a 5-7kg level. Wherein the servo scanning unit further comprises a two-degree-of-freedom scanning servo device which enables the system to realize three-dimensional scanning in a large range, various scanning modes such as PPI, VAD and RHI are realized, and the tail end direction of the servo scanning unit is adjusted according to the current attitude information of the unmanned aerial vehicle platform while scanning is performed; and the influence caused by the attitude change of the unmanned aerial vehicle platform is compensated.

A method for utilizing radar from wireless earpieces includes activating one or more radar sensors of the wireless earpieces, performing radar measurements of a user using the one or more radar sensors of the wireless earpieces, and analyzing the radar measurements to determine pulsatile measurements associated with the user, the analyzing performed using a processor of the wireless earpieces.

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 a three-dimensional laser radar measurement analysis control system, which belongs to the technical field of three-dimensional laser radar measurement analysis control and comprises an acquisition module, a data analysis module and a tracking analysis module. The acquisition module is used for performing environment measurement by using a three-dimensional laser radar to obtain corresponding three-dimensional point cloud data, and generating a three-dimensional point cloud map according to the three-dimensional point cloud data; the data analysis module is used for analyzing the three-dimensional point cloud map and determining an abnormal measurement area; identifying an abnormal reason corresponding to the abnormal measurement area; evaluating a target influence value corresponding to the abnormal measurement area according to a preset measurement purpose; performing corresponding processing according to the obtained target influence value; the tracking analysis module is used for tracking and analyzing the abnormal measurement area; calculating a target influence value corresponding to a corresponding abnormal measurement area in the three-dimensional point cloud map in real time, and generating an influence curve; and evaluating a corresponding early warning value according to the influence curve, and performing corresponding early warning processing according to the obtained early warning value.

A single-station single-target flight path data particle filtering method based on a target position relates to the field of radar data processing, and comprises the following steps: sampling a flight path state of a flight target at 0 moment according to prior distribution to obtain a particle set of the flight path state at 0 moment, and predicting the particle set of the flight path state of the flight target at k moment to obtain a particle set of the flight path state of the flight target at k moment; obtaining a predicted value of the observation value of the flight target at the k moment; then tracking and measuring the flight target at the k moment through a radar to obtain an observed value of the flight path state of the flight target at the k moment, updating the weight of the particle set at the k moment, and finally processing flight path data measured by the radar through the steps of resampling, statistical output and iteration. According to the method, the distribution of the particle set can be updated by resampling according to the particle weight, the filtering effect is achieved, the observation error can be obviously reduced, the noise is further reduced, and the measurement tracking effect is improved.

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 in the present application are a radar measurement compensation method and a device. The method comprises: matching atmospheric environment data samples and radar measurement data samples with respect to timestamps, so as to obtain radar sequence data and environment humidity data; processing the radar sequence data to obtain normalized radar data; performing sampling processing to obtain humidity-normalized radar data; and obtaining a compensation parameter by means of polynomial fitting, and using same for compensating for a radar result, so as to reduce measurement error.

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.

The invention provides a laser measurement method and a laser radar, and relates to the field of laser radar measurement. The method comprises the following steps: generating a frequency sweeping light beam; splitting the sweep-frequency light beam into a signal light beam and a local oscillator light beam; emitting the signal light beam; receiving a reflected light beam generated by reflection of the signal light beam encountering an object; carrying out time delay or frequency shift on at least one of the signal light beam, the reflected light beam and the local oscillation light beam, and / or carrying out in-phase orthogonal coherent demodulation on the local oscillation light beam and the reflected light beam so as to obtain scalar values of beat frequency of a frequency raising stage and beat frequency of a frequency lowering stage; and detecting a beat frequency of an up-conversion phase and a beat frequency of a down-conversion phase between the local oscillator beam and the reflected beam to determine the speed of the object and / or the distance between the object and the lidar. According to the scheme, a measurement blind area can be avoided, and the measurement precision is improved.

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.