362 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 provides a vortex electromagnetic wave radar multipath virtual image suppression method and system, and relates to the technical field of radar imaging virtual image suppression, and the method comprises the steps: adjusting the circular ring radiuses corresponding to different modes in a uniform concentric circular ring array according to the prior information of a target pitch angle, and obtaining the radar emission configuration of main lobe alignment; performing time domain sampling on the multi-path vortex radar echo signal in each mode to form a two-dimensional radar echo matrix; analyzing the obtained two-dimensional radar echo matrix and the MISO system echo after phase compensation by using an azimuth dimension point spread function to obtain dual-system imaging features; and performing modal domain FFT and time domain pulse compression processing on the multipath echo features under the MISO and MIMO systems by using fast Fourier transform and pulse compression, and finally outputting a virtual image suppressed synthetic radar image. The multi-path virtual image suppression method has the beneficial effects that the suppression of the multi-path virtual image is realized by utilizing the characteristic that the real image positions of the imaging results are completely the same and the virtual image positions are different under the multi-transmitting and single-receiving systems.

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.

A radar system comprises a physical radar array including a plurality of physical transmit antennas, each configured to transmit a respective signal having a wavelength λ. The physical radar array further comprises a plurality of physical receive antennas, each configured to receive each of the respective transmitted signals. At least one of the plurality of physical receive antennas is positioned at a different elevation than the other receive antennas. In some embodiments at least one of the plurality of physical transmit antennas is positioned at a different elevation than the other transmit antennas. In some embodiments the radar system further comprises a neural network arranged to receive data from the physical radar array and to generate or update data for one or more missing virtual antennas, generate a new fraction of the virtual antennas, generate the full set of virtual antennas, or directly generate the processed data.

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 an unmanned aerial vehicle intelligent identification device based on FAST site dangerous rock inspection. The unmanned aerial vehicle intelligent identification device comprises an unmanned aerial vehicle, a laser radar, a surveying and mapping camera and a D-RTK mobile station, after the unmanned aerial vehicle takes off, inertial navigation calibration is firstly carried out at the high altitude, the unmanned aerial vehicle flies upwards in a bow-shaped circulation mode from the foot of a mountain body at the station site 1H, dangerous rock point cloud data of the high and steep slope around the station site are rapidly obtained through a laser radar and a surveying and mapping camera carried by the unmanned aerial vehicle, the three-dimensional geometrical characteristics of the dangerous rock mass are extracted, and the isolated dangerous rock mass of the high and steep slope is intelligently and efficiently recognized. Through laser radar imaging equipment carried by the unmanned aerial vehicle, high-density point cloud data of the high and steep slope around the station site is rapidly obtained, three-dimensional geometric features of the dangerous rock mass are extracted, and the isolated dangerous rock mass of the high and steep slope can be accurately, intelligently and efficiently identified. The method is of great significance to stable and reliable operation and scientific achievement output of a 500-meter-caliber spherical radio telescope (FAST) which is a national important scientific and technological infrastructure.

The invention belongs to the technical field of radar signal processing and imaging, and particularly relates to a distributed MIMO radar imaging method based on multi-technology fusion, which comprises the following steps: S1, constructing a distributed MIMO radar array: constructing a distributed array consisting of L identical MIMO radar units, each unit comprising M transmitting antennas and N receiving antennas; the multi-radar synchronous imaging method is characterized in that each radar unit adopts an offset frequency orthogonalization design, signals of each radar unit and different transmitting antennas in the same unit are mutually orthogonal in a time domain and a frequency domain by elaborately setting the offset frequency of each transmitting antenna, a virtual array is equivalent to a uniform linear array, and multi-radar synchronous imaging is realized by utilizing a high-precision synchronous control mechanism. According to the method, the equivalent aperture is greatly expanded through cooperative work of the distributed MIMO radar arrays, so that the angular resolution is remarkably improved, the accuracy and reliability of echo signals are guaranteed by adopting a unique orthogonal signal design, and the imaging stability is improved.

The present invention discloses a high-resolution imaging method for a scanning radar under low signal-to-noise ratio conditions, comprising: Step 1: Modeling the echo signal of the scanning radar and initializing the scattering point power matrix; Step 2: Calculating the covariance matrix according to the scattering point power matrix; Step 3: Modeling the radar imaging problem as a least-squares problem by using the covariance matrix and calculating the least-squares solution of the target scattering intensity; Step 4: Calculating the scattering point power matrix according to the least-squares solution of the target scattering intensity; Step 5: Removing the smaller values in the scattering point power matrix to update it; Step 6: Repeating the operations of Step 2 to Step 5 until the maximum number of iterations is reached. The present invention applies the iterative adaptive method based on the least-squares method to scanning radar imaging, and removes the smaller values in the scattering point power matrix during the iteration process, making the target signal more prominent, improving the azimuth resolution under low signal-to-noise ratio conditions, and enhancing the imaging effect.

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 belongs to the technical field of radar imaging, and particularly relates to a radar sparse three-dimensional imaging and resource scheduling method based on ring array nesting, which comprises the following steps of: establishing a sparse imaging model under an OFDM (Orthogonal Frequency Division Multiplexing) framework; providing a sparse two-dimensional imaging method; proposing a pitch angle reconstruction method based on phase interference; calculating imaging parameters required by resource allocation in the multi-target imaging scene; and establishing an adaptive resource scheduling optimization model and providing a solving method. According to the radar sparse three-dimensional imaging method based on circular ring array nesting, three-dimensional high-resolution imaging is achieved under the condition that a small number of radar resources are consumed. And a self-adaptive resource scheduling algorithm is provided, so that a multi-target imaging self-adaptive resource scheduling model is established by taking time saving, improvement of array element and frequency band utilization rates and balance of radiation intensity of a mode selected by each target as optimization targets, and reasonable allocation of limited radar resources is realized.

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 invention discloses a large-scale hybrid beam forming array construction method based on a passive beam forming network, and belongs to the field of radio frequency systems. According to the method, the array is divided into a plurality of active sub-modules (each sub-module comprises a radiation unit array, a passive beam forming network, a multi-channel radio frequency module and a digital-to-analog conversion module), and the layered beam forming technology of a digital baseband processing module is combined, so that the balance of high performance and low complexity is realized. The method specifically comprises the following steps: 1) dividing a coverage space into a plurality of sub-regions by using a passive beam forming network, localizing a digital beam forming matrix into a block diagonal matrix, and reducing the calculation amount; 2) a large-scale array is constructed through flexible expansion of sub-modules, and full-aperture gain is ensured; and 3) the radio frequency channels of the idle sub-regions are dynamically turned off so as to save energy consumption. In scenes such as 5G / 6G millimeter wave communication, radar imaging and the like, the system power consumption and the calculation complexity are remarkably reduced, and meanwhile, the performance of a full-digital beam forming array is approached.

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 invention belongs to the technical field of radar imaging, and relates to a three-dimensional imaging method, device and equipment of a ground-based synthetic aperture radar. The method comprises the following steps: acquiring echoes of a ground-based synthetic aperture radar, and projecting the echoes to the same imaging area grid in each receiving channel to obtain a two-dimensional radar image of each receiving channel; constructing a pitching direction array flow pattern; pixels of all the two-dimensional radar images in the same distance-azimuth unit form a pixel vector; taking the pitch direction array flow pattern pixel vector as input to obtain a plurality of target pitch direction estimation results; projecting each target pitching direction estimation result to a space rectangular coordinate system through coordinate transformation to obtain a corresponding height estimation result, and further obtaining a three-dimensional point cloud result of the imaging scene; and clustering the three-dimensional point cloud result, and then carrying out noise reduction processing to obtain a three-dimensional point cloud image. According to the invention, super-resolution three-dimensional imaging can be realized, and the imaging quality is improved.

The invention discloses a discrete imaging method and device for a ground penetrating radar system, terminal equipment and a storage medium, and relates to the technical field of detection radar imaging, and the method comprises the steps: obtaining a plurality of antennas of a common midpoint antenna array, and carrying out the integration and superposition of initial signals collected at different collection points in a detection region, generating a discrete signal of each antenna pair on each acquisition point, and determining the two-way travel time and the inclination factor of a detection target detected by each antenna pair at each acquisition point according to the discrete signal, and carrying out migration integration according to the coordinate position of each acquisition point, the discrete signal of each antenna pair, the two-way travel time of the corresponding detection target and the inclination factor, generating a two-dimensional imaging result of the depth profile of each acquisition point, and finally splicing the two-dimensional imaging results of the acquisition points to obtain the depth profile of the detection target. And generating an underground three-dimensional model of the detection area. Therefore, the problem that the underground imaging result of the existing handheld radar ground penetrating system is not ideal can be effectively solved.

The invention discloses a system and a method for realizing space beam dynamic pointing based on a multi-area distributed dynamic adjustable metasurface, and belongs to the technical field of electromagnetic wave regulation and control. The system comprises a multi-region distributed metasurface structure and a controller, and the metasurface structure is divided into a passive implementation mode and an active implementation mode: the passive metasurface dynamically switches an activation region by using a high-speed single-pole multi-throw switch through a unit structure which is pre-divided into a plurality of independent regions and presets 0 / pi phase response; the active metasurface adopts a controllable switch element array integrated with a PIN diode or an adjustable capacitor, and the on-off state is controlled through a multi-pole single-throw switch so as to adjust the phase response. And the controller periodically switches the metasurface state in the time dimension to realize full-space rapid scanning in the beam direction. The method breaks through the flexibility limitation of the traditional beam forming technology, has the advantages of low cost, high real-time performance and full-space coverage, and can be applied to a wireless communication base station antenna array and radar imaging equipment.

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.