270 results about "Radar imaging" patented technology

The invention relates to the technical field of satellite remote sensing monitoring, in particular to a method for monitoring a resident-free island by adopting satellite remote sensing, which comprises the following steps of: acquiring optical images and cloud layer data of a target island through optical and meteorological satellites, predicting a cloud shielding probability, and scheduling a radar satellite when the cloud shielding probability exceeds a threshold value; comparing the effective area of the optical image with a reference demand, triggering radar imaging when a difference value reaches a preset proportion, extracting a coastline feature point set from a historical image, calculating a spatial distribution entropy screening subset, constructing an optimized affine transformation matrix to compensate a radar image, and obtaining a new optical image when the cloud cover is low. Coastline feature point errors of the calibration radar image and the new optical image are calculated, secondary compensation is carried out, global time sequence monitoring data are generated, monitoring continuity and data consistency in a cloud shielding scene are improved, and the method is suitable for resident-free island dynamic monitoring.

The invention provides a light intensity measurement method and device based on single-photon detection and electronic equipment, and relates to the technical field of single-photon detection and laser radar imaging, and the method comprises the steps: collecting the arrival time information of photons in a plurality of single-photon detection events for each detection position; extracting a time sequence characteristic quantity related to the light intensity estimation based on the arrival time information; constructing a model input parameter for estimating the target light intensity based on the time sequence characteristic quantity; inputting the model input parameters into a light intensity estimation model, and predicting a light intensity estimation value of the target light intensity; and generating a corresponding light intensity distribution image according to the light intensity estimation value. According to the method, high-precision light intensity estimation can be realized only by a few photons, the requirements on the repeated detection times and the signal-to-background ratio are greatly reduced, and the imaging robustness is enhanced.

The invention discloses a preprocessing and compression method and system for single-photon laser radar data, and belongs to the technical field of single-photon laser radar data processing. According to the method, firstly, a target distance image is collected by means of a single-photon laser radar imaging system, and original data is provided for subsequent processing; thirdly, constructing a frequency-time histogram for each pixel point of the acquired image so as to visually present the distribution condition of photons in the time dimension; then, Gaussian fitting and peak value screening operation is carried out on the histogram of each pixel point, effective photon signal peak values are accurately identified, false signals caused by noise and interference are eliminated, and the data quality is improved. And finally, inputting the photon data corresponding to the screened peak values into a multi-attention three-dimensional single-photon compression neural network, and realizing high-efficiency compression of the single-photon laser radar data by using the strong feature extraction, high-efficiency compression mechanism and flexible output control capability of the network, thereby providing powerful support for the application of the single-photon laser radar technology in multiple fields.

The invention discloses a scanning radar super-resolution imaging method based on data-driven adaptive parameter learning, which is applied to the technical field of radar imaging and aims to overcome the defects that a traditional super-resolution method is high in parameter sensitivity and an existing network expansion method has a redundant structure and poor adaptability. The method comprises the following steps: firstly, converting a non-differentiable L1 regularization problem into a differentiable L2 problem based on a maximum-minimum principle; secondly, expanding an iteration process into a multi-stage cascade neural network, and performing adaptive learning on regularization parameters in a data driving mode; and finally, layered parameter optimization and super-resolution reconstruction are realized through an end-to-end network architecture. By adopting the method of the invention, the super-resolution imaging performance of the radar is effectively improved.

The invention discloses an I SAR fusion imaging method, system and device based on centralized multi-station networking, and relates to the technical field of radar imaging, and the method comprises the steps: obtaining I SAR frequency domain echo data of each subsystem; performing frequency domain space matching on the frequency domain echo data based on the observation angle difference of each radar; performing frequency domain alignment processing on the matched frequency domain data; and fusion and imaging are carried out. According to the I SAR fusion imaging method, system and device based on the centralized multi-station networking, the imaging resolution is remarkably improved, multi-station frequency domain data are mapped to a unified local frequency space through a coordinate transformation matrix, non-uniform data are subjected to uniform reconstruction in combination with a self-adaptive interpolation algorithm, and the imaging resolution is remarkably improved. The frequency domain integration interval is effectively expanded, compared with a single-station I SAR which only covers a local area of the total rotation angle of the target, the range resolution is further optimized through multi-station bandwidth synthesis in the range direction, and high-fidelity reconstruction of the target in the complex shape is achieved.

The invention discloses a side slope risk monitoring method and system based on three-dimensional laser and two-dimensional phase sweeping radars, and the method comprises the steps: S1, obtaining a digital elevation model of a side slope through a three-dimensional laser radar, and obtaining a radar imaging result of the side slope through the two-dimensional phase sweeping radars; s2, performing coordinate system unification and projection conversion on the digital elevation model and the radar imaging result to generate a conversion relation lookup table; s3, obtaining a real deformation value of the target based on the digital elevation model, the radar imaging result and the conversion relation lookup table; s4, performing time sequence analysis on the real deformation value of the target, judging the state of the slope, and calculating a tangent angle to determine an early warning level when accelerated deformation is recognized; s5, automatically switching the working mode of the two-dimensional phase sweeping radar according to the early warning level; and S6, in the moving target monitoring mode, tracking and predicting the moving target, and performing collision judgment and target re-identification. The method has the advantages of high precision, intelligence and the like.

The invention belongs to the technical field of slope monitoring and early warning, and provides a slope progressive failure precursor identification method based on deep learning. On the basis of 4D point cloud imaging radar data, surface patches are divided according to slope sections, rock stratum boundaries and the like, attributes are marked, a directional kernel is constructed in the dominant direction and the normal direction, and density, flatness, roughness, edge feeling, pore feeling and other characteristics and state labels are extracted through independent coding of all moments; constructing a normal learning window and a usual trajectory based on environmental conditions, training a conditional variation auto-encoder which only learns a normal form, setting two interpretable dimensions of pore evolution and edge enhancement, and applying direction consistency and state constraint; according to the reconstruction deviation degree and the consistency of adjacent surface patches, the abnormal trend that the density is reduced, the roughness / edge is increased and the pores are increased in the dominant direction is recognized online, and encryption observation is triggered for side slope precursor recognition and early warning; the method does not depend on cross-time displacement regression, and the influence of environmental disturbance can be inhibited.

The invention discloses an efficient pipeline double-DDR-group SAR imaging data storage and transposition system based on an FPGA, and belongs to the technical field of radar imaging signal processing. An efficient DDR group state machine is configured in the system, each DDR has seven different states, two frames of radar data can be processed in total after running for one time, one DDR reads data, then the data is processed and transmitted to the other DDR for data writing, one DDR performs writing operation while reading the other DDR, and the data writing efficiency is greatly improved. High-speed pipeline multi-path parallel data processing is realized, so that time is saved to the greatest extent, and high real-time performance of the whole radar imaging system is ensured.

The invention discloses a radar foresight super-resolution imaging method based on echo energy correction, belongs to the technical field of radar imaging, and aims to solve the problem of imaging errors caused by speed errors of a traditional imaging method on a high-speed motion platform. The speed of the motion platform is accurately estimated based on an echo energy correction criterion, so that the influence of the motion error of the platform on the super-resolution imaging performance is effectively reduced, and the dependence of a traditional method on high-precision external speed measurement equipment is overcome. The method comprises the following steps: firstly, constructing a reconvolution model containing Doppler phase information; secondly, estimating the speed of the platform based on an echo energy correction criterion so as to obtain accurate speed information; then, updating a Doppler phase matrix by using the corrected speed, and correcting a reconvolution echo model; and finally, proposing a sparse super-resolution algorithm based on power weighting, and optimizing the target power and the noise power through alternate iteration to realize robust super-resolution imaging under the motion platform, thereby remarkably improving the target recognition and situation awareness capabilities of the motion platform.

The invention relates to the technical field of campus safety protection, in particular to a method and system for preventing campus bullying by using a laser radar imaging technology, and the method comprises the following steps: obtaining 3D point cloud data of an environment in a monitoring region preset in a campus, and collecting sound data in the monitoring region; processing the 3D point cloud data, generating a three-dimensional environment image and extracting a first behavior feature; processing the sound data, and extracting a second behavior feature; performing multi-modal fusion on the first behavior feature and the second behavior feature to generate a unified behavior feature vector; based on the behavior feature vector, identifying whether a bullying behavior exists in the current scene, and calculating a corresponding behavior risk score; according to the method and the device, whether the preset alarm threshold value is reached or not is judged, and if yes, corresponding alarm and early warning operation is triggered, so that non-intrusive active monitoring of non-appearance privacy leakage of the campus secret corner is realized, and the problems of privacy limitation and blind areas of traditional video monitoring are solved.

The invention provides a multilayer medium efficient imaging method suitable for frequency modulation continuous wave ice radar data, and belongs to the field of frequency modulation continuous wave ice radar imaging. Comprising the steps of multi-layer medium signal model construction, improved distance-Doppler algorithm implementation, distance migration accurate correction and azimuth focusing processing. According to the method, a multi-layer medium signal model containing refractive index and propagation velocity changes is established for the problem of target distance distortion caused by propagation velocity differences of electromagnetic waves in different media such as ice and snow; based on the model, a traditional distance-Doppler algorithm process is improved, distance migration caused by multiple layers of media is accurately corrected by introducing a medium-dependent distance migration factor, and efficient azimuth focusing is achieved. And finally, a high-resolution ice layer internal structure image can be generated, and the method is suitable for polar region large-range ice cover detection and rapid processing of a large amount of ice radar data.

The invention relates to an SAR image fusion method, device and equipment in a terahertz frequency band bunching mode, and the method comprises the steps: carrying out the preprocessing of a terahertz bunching mode video, and enabling a reference image and a to-be-fused image to be projected to a ground plane through combining the linearity and interpolation of a radar imaging digital elevation model, thereby obtaining a corresponding projection image; constructing an anisotropic diffusion scale space image for the two types of projection images, generating a Harris function scale space image according to the anisotropic diffusion scale space image, extracting extreme points, constructing SIFT feature descriptors of the two types of images based on the extreme points, obtaining an initial feature matching point pair set through similarity comparison, obtaining an optimized point pair set after multiple times of screening, and obtaining an anisotropic diffusion image through the optimized point pair set. And calculating an image conversion affine matrix by least square matching, fusing the to-be-fused image and the reference image according to the matrix to obtain a fused image, updating the image as the reference image, and repeatedly fusing the reference image with the next to-be-fused image until all frames are fused to obtain a final fused image. By adopting the method, the quality of the fused image can be effectively improved.

The invention relates to the technical field of target detection and positioning, and discloses an unmanned aerial vehicle docking taper sleeve target detection and positioning method based on a laser imaging radar, and the method comprises the steps: calibrating a coordinate system: calibrating the internal parameters of the laser imaging radar based on an annular target, the pose of the annular target in a laser imaging radar coordinate system is calculated through a direct linear transformation method, and after optimization through a beam adjustment method, the unmanned aerial vehicle and the annular target coordinate system are set to be in a translation-only relation; calculating rotation and translation matrixes of the laser imaging radar and the unmanned aerial vehicle coordinate system to form a pose relation between the two; target detection: acquiring an intensity image and a distance image of a taper sleeve target through a laser imaging radar, and performing model training in a complex environment in combination with a target detection algorithm to generate a detection model; and pose resolving: calculating the center-of-mass coordinate of the taper sleeve target, and outputting the position information of the taper sleeve target under the unmanned aerial vehicle coordinate system. The detection and positioning capability of the docking taper sleeve target of the unmanned aerial vehicle can be improved.

The invention discloses an FISTA plug-and-play sparse radar imaging method based on adaptive regulation and control, which combines FISTA with deep learning prior, introduces reinforcement learning to carry out adaptive parameter regulation and control, and aims to significantly improve the automation degree, convergence rate and cross-scene robustness of an imaging process. The method is especially suitable for processing challenges of coexistence of different sampling rates, noise levels and scene complexity, and can effectively solve the problems that a traditional method depends on manual parameter adjustment, the calculation overhead is high, and the generalization ability is weak. According to the method, selection modeling of key hyper-parameters (such as step length, de-noising intensity and momentum coefficient) and a stop criterion is used as a Markov decision process, and an intelligent agent makes a decision adaptively according to a current reconstruction state, so that the problem is solved, and an advanced solution is provided for efficient and reliable radar imaging processing.

The invention discloses a radar imaging detection satellite constellation design method, which comprises the following steps of: decomposing a constellation into a plurality of orbit surfaces, uniformly describing each orbit surface through four parameters, constructing an asymmetric constellation structure, and establishing a multi-target optimization model for solving by taking the total cost of the constellation, the maximum revisit time and the detection performance as targets. Non-dominated quantizer sorting is introduced in the sorting process, and satellite constellation design is completed. According to the method, single-satellite-based optimization of the salted fish is converted into orbital plane-based optimization, the optimization variable dimension is remarkably reduced, the method is particularly suitable for large-scale constellation design comprising hundreds of satellites, meanwhile, the Pareto frontier is obtained through non-dominated sorting, various constellation configuration schemes emphasizing different performances are provided, and the method is suitable for large-scale constellation design. Compared with an existing constellation design method, the problems that the to-be-optimized parameters are increased along with the number of satellites, and efficiency is low are solved, the scheme output by the algorithm is more reasonable through the improved sorting mode, and the method can be used for constellation design.

The embodiment of the invention provides a near-field MIMO radar data processing method based on multistage background suppression and target enhancement, and is applied to the technical field of radar signal processing. The method comprises the following steps: acquiring a real-time background template and a real-time image frame of a target scene; calculating to obtain differential image data corresponding to the real-time image frame based on the real-time background template and the real-time image frame; performing Gaussian filtering processing on the difference image data to obtain Gaussian filtering image data; performing morphological processing on the Gaussian filtering image data to obtain morphological image data; performing target enhancement processing on the morphological image data to obtain target enhanced image data corresponding to the real-time image frame; and outputting the target enhanced image data. The technical effect of improving the radar imaging precision is achieved.

An imaging method using a doppler radar wherein the pointing direction in transmission (dei) is modified from recurrence to recurrence; each detection block of duration T comprises a periodic repetition of a number C of pointing cycles, each of these cycles comprising a number P of recurrences, the set of these P recurrences covering the De pointing directions (dei) of the set; the order of the pointings is modified in a pseudo-random manner from pointing cycle to pointing cycle during a same detection block so as to create an irregular time interval between two pointings in a same direction; at least one beam is formed in reception on each recurrence in a direction included in the transmission-focused angular domain in the pointing direction corresponding to the recurrence.

The application discloses a complex lunar surface scattering coefficient image simulation method and system based on multiple data jointing, and the method comprises the following steps: firstly, terrain camera data is used to acquire terrain height data of a special geological structure of the moon as model geometric information input; secondly, a lunar soil weathering layer electromagnetic scattering model is established by using a vector radiation transfer theory and a lunar surface stone double-component method to simulate the interaction between electromagnetic waves and lunar rocks, the lunar surface, weathering layer particles and the subsurface; finally, a radar imaging mechanism is simulated based on a mapping projection algorithm, the scattering coefficient on each scattering facet is calculated by using the electromagnetic scattering model, and the scattering coefficient is mapped to an imaging area by using a ray tracing method, a shadow judgment method and the like, so that the scattering echo of each region of the complex lunar surface is rapidly estimated, and the fast scattering coefficient image simulation is realized.

The invention relates to the technical field of coherent laser radar detection and imaging, in particular to a Doppler tomography laser radar imaging device based on carrier phase noise compensation and an optimization method. Phase noise is accurately estimated through a double-reference channel structure, an image quality evaluation index is adopted as a parameter optimization basis and a compensation effect judgment standard, target echo phase noise is accurately compensated, and therefore high-resolution Doppler tomography of a high-speed spinning target at the rotating speed of 30 Hz is achieved under the condition that the optical path difference exceeds the distance of 80 times of the laser coherence length. The method is designed for the broadband characteristic of the echo signal of the Doppler tomography laser radar, and has the characteristics of high compensation precision, wide distance dynamic range, low manufacturing cost and the like.

The invention discloses a ground-based imaging radar moving target interference elimination method based on a range profile clutter map. The method comprises the following steps: generating a clutter map of a one-dimensional range profile by using a CACM-CFAR algorithm; comparing the generated range profile clutter map with the current one-dimensional range profile, and accurately judging interfered pixels by combining amplitude and phase thresholds; the static clutter estimation value of the corresponding pixel in the range profile clutter map is adopted to replace and correct the interfered pixel; and azimuth focusing is realized by using a BP imaging method, and moving target interference elimination in radar imaging is completed. The technology can effectively eliminate the amplitude phase interference of the moving target on the radar image.

The present application relates to the technical field of satellite remote sensing monitoring, in particular, the present application relates to a kind of method for monitoring uninhabited islands by satellite remote sensing, the present application obtains target island optical image and cloud data by optical and meteorological satellite, predicts cloud cover probability, dispatches radar satellite when threshold value, compares the effective area of optical image with benchmark demand, difference reaches preset proportion when triggering radar imaging, extract the coastline feature point set from historical image, calculate spatial distribution entropy to filter subset, build optimized affine transformation matrix to compensate radar image, obtain new optical image when cloud cover is low, calculate the coastline feature point error of calibration radar image and new optical image, carry out secondary compensation, generate global time series monitoring data, improve the monitoring continuity and data consistency under cloud cover scene, applicable to the dynamic monitoring of uninhabited islands.

The application discloses a vortex electromagnetic wave radar forward-looking imaging method and system based on a concentric circular array design, a storage medium and an electronic device, and specifically comprises the following steps: establishing a new system radar imaging model according to a radar working mode; designing a concentric circular array and a vortex mode transmitting function; deriving a return model; obtaining distance direction high-resolution information of a target; performing distance correction, phase decoupling and Bessel amplitude compensation on the azimuth direction of the return, and coherently superimposing the compensated return to reestablish a dual relationship between a mode and an azimuth angle; and finally, realizing vortex electromagnetic wave radar forward-looking two-dimensional imaging through fast Fourier transform on the azimuth direction. The forward-looking imaging can increase the observation time of a region of interest, keep the region of interest in a main lobe range, enhance the strength of a return, increase return information, and effectively improve the azimuth direction resolution.

This invention discloses a method and system for de-flattening preprocessing, belonging to the field of radar imaging. The method includes: acquiring a main radar image and a secondary radar image, each containing several main image scattering points and several secondary image scattering points; calculating the secondary image scattering points corresponding to the main image scattering points to form several scattering point pairs; performing a flat-ground phase acquisition action to obtain an ideal flat-ground phase, thereby forming an ideal flat-ground phase map and completing the de-flattening preprocessing process. The flat-ground phase acquisition action includes: calculating the main image Doppler history and the secondary image Doppler history of the scattering point pairs; determining the main image focusing time that meets a preset time threshold to calculate the main image slant range, thereby determining the secondary image focusing time that meets the preset time threshold, and calculating the secondary image slant range based on the secondary image focusing time; and obtaining the ideal flat-ground phase of the scattering point pairs based on the main image slant range and the secondary image slant range. The de-flattening preprocessing method disclosed in this invention can effectively reduce the processing error of de-flattening preprocessing methods.

The invention discloses an anomalous body positioning method and system combining borehole transient electromagnetic and geological radar, and relates to the technical field of mine safety detection, and the method comprises the steps: synchronously collecting the borehole transient electromagnetic data and geological radar data of an ore body to be analyzed, and generating a borehole transient electromagnetic imaging graph and a borehole geological radar imaging graph; two-dimensional coordinates of a target abnormal point in the borehole geological radar imaging graph are extracted, and the corresponding target apparent resistivity is determined; drawing an apparent resistivity contour map based on the target apparent resistivity in a target radial sectioning map of the borehole transient electromagnetic imaging map, and determining a plurality of candidate three-dimensional coordinates of a target abnormal point; at least one target feature point is selected from the borehole geological radar imaging graph, and the feature apparent resistivity corresponding to the target feature point is determined; and drawing a feature circle based on the target feature points, and screening the plurality of candidate three-dimensional coordinates to obtain coordinates of the geological anomalous body. According to the invention, the technical problem of insufficient positioning precision and reliability in the prior art is solved.

Embodiments of the present application provide a receiving device, a laser radar, an imaging system, and a related method. The receiving device is connected to a receiving array, the receiving array comprises N receiving units, and each receiving unit is used for detecting a photon signal and outputting a pulse signal; and the receiving device comprises a combiner and a speed limiter. The combiner is connected to the receiving array and is used for performing signal combination processing on N received pulse signals respectively output by the N receiving units, and outputting a first combined pulse signal, the first combined pulse signal comprising K pulse signals among the N pulse signals. The speed limiter is used for performing pulse deletion processing on the received first combined pulse signal on the basis of a signal processing rate or a preset time interval, and outputting a second combined pulse signal, wherein the second combined pulse signal comprises M pulse signals among the K pulse signals. By implementing the embodiments of the present application, the hardware volume can be reduced and the resource consumption can be reduced without limiting the photon event processing scale.

The invention relates to the technical field of radar imaging, in particular to a chaotic MIMO through-the-wall radar imaging device and method based on 2D-SCF, and mainly overcomes the defects of the existing MIMO through-the-wall radar imaging technology in the aspects of signal detection and imaging quality. The device comprises a signal transmitting circuit and a signal receiving circuit, the signal transmitting circuit comprises a signal generator, a power amplifier, a single-pole two-throw radio frequency switch and a transmitting antenna which are connected in sequence, and the signal receiving circuit comprises a receiving antenna, a single-pole eight-throw radio frequency switch, a low-noise amplifier and a data acquisition processor which are connected in sequence. And the data acquisition processor is connected with the reference signal output end of the signal generator. The device generates a chaos modulation pulse width-position signal through the signal generator and takes the chaos modulation pulse width-position signal as a detection signal, has the advantages of high range resolution, low self-correlation side lobe, strong anti-interference and the like, and adopts a 2D-SCF algorithm to suppress an image grid side lobe, thereby effectively improving the imaging capability and imaging quality of the MIMO through-the-wall radar.

The invention relates to the technical field of radar imaging, and particularly discloses a baseline-assisted scene partition SAR imaging method and system, and the method comprises the steps: obtaining more than two SAR images of a monitoring region through setting more than one baseline; strong scattering points of each SAR image are determined; estimating the offset of a strong scattering point of the main image under each baseline; determining a plane area and a slope area according to the offset; respectively imaging the plane area and the slope area; and splicing the images of the plane area and the slope area. According to the principle that imaging projection coordinates of target points of a flat ground area and a slope area can deviate under different base lines due to different elevations, division of the flat ground area and the slope area of a monitoring scene is completed. And finishing imaging processing on the flat ground area by adopting a flat ground hypothesis principle. And for the slope region, an approximate optimal imaging surface is constructed by taking the image entropy as an evaluation index. And splicing the flat ground area image and the slope area image to obtain a high-resolution and low-error SAR image.

The present application relates to the interference method for generating radar false target, belongs to the technical field of antenna radar scattering. The method is: radar transmits electromagnetic wave to detect target; electromagnetic wave reaches echo control structure; modulation signal generator generates specific modulation signal and sends to the control structure; modulation signal on the control structure and electromagnetic wave signal are convolved in frequency domain to realize frequency spectrum shift; radar receives and processes electromagnetic echo signal, and multiple harmonic false targets appear in one-dimensional distance direction; the present application proposes to adjust the radar false target interference by controlling the frequency of modulation signal generator according to the needs, can realize the energy attenuation in one-dimensional distance direction, and a single radar target becomes many false targets, and the imaging radar can be effectively passively interfered by making the radar target fuzzy and generating many false targets.

The invention particularly relates to a low-cost express parcel forbidden object detection method based on radar imaging, and the method comprises the steps: transmitting a linear frequency modulation signal to a conveying belt through a transmitting antenna, and receiving a point target echo signal reflected by a target on the conveying belt through a receiving antenna; performing signal integration processing on the point target echo signal to obtain a complete target echo signal corresponding to the target; performing imaging processing based on the complete target echo signal to obtain a millimeter wave imaging result corresponding to the target; and performing classification identification processing on the millimeter wave imaging result by using a trained identification model to obtain a contraband identification result corresponding to the target. According to the invention, nondestructive detection of contraband in the parcel can be realized, and the detection efficiency is improved.

The application provides a polarization SAR image simulation method for forests under complex terrain conditions, comprising the following steps: (1) setting parameters of a polarization SAR imaging process, including radar imaging parameters, forest parameters and terrain parameters; (2) generating a corresponding terrain model according to the terrain parameters; (3) constructing a forest model according to the forest parameters; (4) calculating a polarization SAR image according to the forest parameter model, and finally simulating the polarization SAR image of the forest under the complex terrain conditions. The method can improve the simulation of the polarization SAR image of the forest under the complex terrain conditions, can be used for understanding the remote sensing mechanism, testing new applications and designing the inversion algorithm of the forest structure, and can further explore the influence of the terrain on the polarization SAR image imaging process.