222 results about "Radar cross-section" patented technology

The invention discloses an airborne radar identification method based on multi-scale signal decomposition and depth feature fusion, belongs to the technical field of radar target identification, is used for unmanned aerial vehicle radar target identification, and comprises the following steps: decomposing an original dynamic radar cross section signal into a plurality of intrinsic mode components by adopting an adaptive noise complete set empirical mode decomposition method; self-adaptive wavelet soft threshold denoising is carried out on all the components in a unified mode so as to improve the signal-to-noise ratio and suppress background interference; effective components are screened out by calculating correlation coefficients of all intrinsic mode components and original signals, a radar cross section signal sequence after noise reduction is reconstructed, and multilevel feature fusion is carried out; and inputting the feature vector into a stacked auto-encoder deep neural network classification model, and introducing a particle swarm optimization algorithm to optimize the classification model. According to the method, the signal-to-noise ratio of the signal and the recognition accuracy of the classification model in a low signal-to-noise ratio environment are remarkably improved, and high-precision recognition and classification of different types of radar cross section targets are realized.

The invention belongs to the technical field of superconducting wires, and relates to a niobium-tin composite superconducting wire and a preparation method thereof. The invention provides a Nb3Sn composite superconducting wire. The Nb3Sn composite superconducting wire sequentially comprises an Nb3Sn superconducting wire core, a barrier layer, a stable layer, a transition layer, a substrate layer and a functional layer from inside to outside, the transition layer is formed by mixing copper and a dielectric polymer, and the copper content is continuously decreased in a gradient manner from inside to outside; the substrate layer is the dielectric polymer; the functional layer is a plurality of protruding metal microstructures. According to the invention, the functional layer with the broadband electromagnetic stealth function is integrated on the basis of the Nb3Sn superconducting wire rod, so that the radar cross section is obviously reduced while the Nb3Sn superconducting wire rod bears high-density superconducting current and generates a strong magnetic field, and the technical problem that a high-field superconducting magnet system is easy to detect in an electromagnetic environment is solved.

Wireless devices are commonly carried in fabric-based apparel. Printing metamaterial structures on fabric substrates allows for the ability to create fabric metamaterial layers. A reconfigurable RF based fabric system simply by physically removing or adding different fabric-based metamaterial layers to different regions of the apparel. The fabric-based metamaterial can be used in various filtering applications where the control of phase, reflection angle, refraction angle, polarization, absorption, and transmission of the impinged electromagnetic wave can all be manipulated. Additionally, sophisticated metamaterial systems can be created by combining different metamaterial layers separated above each other. A controllable absorber metamaterial system can be made consisting of two layers. The first layer an electronically controllable that can controllably change between a band-pass and band-reject filter in a relevant frequency band and a second absorptive layer. Vehicles with adjustable metamaterial absorber systems, integrated on the outside or inside of the RF transparent fuselage, have the ability to control their radar cross section dynamically for the purposes of evading detection or spoofing their size by looking larger or similar to vehicles of different radar cross section.

The invention discloses an icing monitoring method and system for a corner reflector deployed based on an unmanned aerial vehicle, and relates to the technical field of environment monitoring, and the method comprises the steps: deploying a corner reflector network, collecting radar cross-section characteristics and environment parameters to generate a data packet, and carrying out the icing monitoring based on the generated data packet; calculating a signal-to-clutter ratio, obtaining a standard deviation of target positioning and phase estimation by using a Cramer-Rao lower bound method, generating a dynamic weight by using the standard deviation, obtaining a corner reflector icing thickness estimation value through data fusion, and generating an optimized signal-to-clutter ratio based on the icing thickness estimation value; and carrying out cooperative judgment by utilizing the generated optimized signal-to-clutter ratio and combining the icing thickness and the attitude deviation, triggering combined adjustment based on a judgment result, and after the combined adjustment is triggered, obtaining the SAR image again and carrying out main and auxiliary image registration and interference pair optimization. According to the invention, the sensing precision and the monitoring robustness of the unmanned aerial vehicle on the state of the corner reflector in an icing environment are improved.

The invention discloses a multilayer wave-absorbing material design method, system, medium and equipment, and the method comprises the steps: building a multilayer wave-absorbing material model through electromagnetic simulation software, taking a radar cross-sectional area RCS as an optimization target, and controlling FEKO to be within a specified target frequency band; sampling electromagnetic parameters in a value range by adopting a Latin hypercube sampling algorithm, performing parameterized simulation on the multilayer wave-absorbing material model, extracting radar cross-sectional area (RCS) values to form a parameter-RCS data set, generating an electromagnetic parameter-RCS data set, training a convolutional neural network, and obtaining a multi-layer wave-absorbing material model; establishing a nonlinear mapping model from the electromagnetic parameters to a radar cross-sectional area (RCS); embedding a proxy model obtained by training into a Bayesian optimization framework, applying an expected improved function to guide a search space, automatically optimizing an electromagnetic parameter combination, and performing FEKO full-wave simulation verification; if the RCS value of the optimization result is lower than the preset threshold value, iteration continues until the performance requirement is met, and the optimal electromagnetic parameter combination is output.

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

The invention discloses a large-scale cluster target electromagnetic scattering analysis method and system based on a parallel equivalence principle, and the method specifically comprises the steps: carrying out the geometric modeling and equivalent surface construction of each target unit in a cluster target, and generating discrete surface element information; starting a parallel computing process, and distributing a target-equivalent face by adopting a greedy algorithm; a calculation process group corresponding to each sub-domain is partitioned according to a two-dimensional Cartesian coordinate grid, a transfer operator matrix between the sub-domains is partitioned according to the same two-dimensional calculation process grid, global parallel iterative solution circulation is carried out, and the equivalent surface flow of the sub-domain is updated; and the converged equivalent surface flow of each sub-domain is used as an equivalent source, and the radar cross section RCS of the whole cluster target in the specified observation direction is synthesized through far-field radiation integration. The method has good parallel expandability and calculation efficiency, is suitable for complex and diverse cluster target scenes, reduces memory requirements and calculation time overhead, improves calculation efficiency, and is high in engineering practicability.

The invention provides a radar waveform optimization method, system and device, a medium and a program product, and the method comprises the steps: transmitting a basic radar signal employing a basic waveform, and receiving an original echo signal formed by the reflection of a target; extracting a radar cross-sectional area of a target from the original echo signal to obtain a target RCS; traversing an RCS allowable range corresponding to each target type in the feature database, and determining a matching result; determining waveform control parameters of the radar waveform; an optimized radar signal employing the optimized waveform is generated and transmitted. According to the scheme, traversal matching is carried out on the target radar cross-sectional area measured in real time and the RCS allowable range in the feature database, adaptive optimization of the radar transmitted waveform on the current target RCS is realized, in addition, the candidate PRF is systematically traversed in the PRF feasible range corresponding to the target type, and the target type is more accurate. The adaptive matching of the PRF parameter with the current target RCS and the propagation condition is realized.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products are provided for object detection over a wireless network. A method performed by a wireless transmit / receive unit (WTRU) includes receiving, from a wireless network, a configuration that includes a configured target profile for a target and information indicative of an identification of the target, wherein the configured target profile comprises a radar cross section profile associated with the target; receiving at least one signal from the wireless network; generating a measured profile based on the at least one signal; determining that the at least one signal was reflected by the target based at least in part on the information indicative of the identification of the target and a comparison between the configured target profile and the measured profile; and performing sensing measurements associated with the target using the at least one signal based at least in part on the determination.

The invention provides a broadband absorption and transmission integrated frequency selective surface with a high selection characteristic, which comprises a first loss layer, a second loss layer and a frequency selection layer, and is characterized in that the first loss layer and the second loss layer realize a transmission band with the high selection characteristic and the broadband characteristic at the same time by using dual-order resonance; the second loss layer and the frequency selection layer are cascaded to realize the absorption and transmission integrated characteristic, and the first loss layer is used for improving the low-frequency and high-frequency wave absorption characteristics and expanding the wave absorption bandwidth. Under the combined action of the first loss layer, the second loss layer and the frequency selection layer, wave transmission within the frequency band of 7.72-11.89 GHz and wave absorption within the frequency band of 1.96-7.12 GHz and the frequency band of 12.95-17.33 GHz are achieved. The antenna has high selection characteristics and broadband characteristics, can effectively suppress interference of external electromagnetic waves of other frequency bands or electromagnetic waves of a frequency band close to a communication frequency band on communication, can reduce the radar cross section of a target, and facilitates target stealth.

The invention provides an RCS (radar cross section) solving method of a uniaxial anisotropic medium based on a moment method. The method comprises the following steps of: modeling a uniaxial anisotropic scatterer or a target model to be simulated in COMSOL; the surface of the scatterer is subjected to triangular mesh generation, and the size of a mesh is determined according to the wavelengths of electromagnetic waves inside and outside the scatterer; after the parameters of the scatterer and the background medium thereof are set, the grid is imported into the moment method for solving, and compared with a finite element method for solving the problem, the background medium of electromagnetic wave radiation and the interior of the scatterer do not need to be subjected to grid subdivision, and the degree of freedom only exists on the surface of the scatterer; the degree of freedom and memory used for solving the integral equation are far smaller than those used by a finite element method, and the method shows excellent calculation efficiency and calculation precision in actual examples.

A system to be carried by a vehicle may include a dual-function antenna structure that includes a substrate and an array of antenna elements carried thereby. A beam forming network may be coupled to the dual-function antenna structure. A radar detector to be carried by the vehicle may be configured to detect radar signals directed to the vehicle. A controller may be configured to control the dual-function antenna structure to switch between a steerable phased array communication mode and a low radar cross section (RCS) mode responsive to the radar detector.

The invention relates to a radar cross section data-based electromagnetic parameter inversion method with robustness. The method comprises the steps of obtaining radar cross section data, namely RCS data of a three-dimensional airplane model, and performing preprocessing to obtain a preprocessed data set; constructing an inversion model based on a Transform and CNN (Convolutional Neural Network) hybrid architecture; constructing a forward modeling model based on depth Gaussian process regression; independently training the inversion model and the forward model, and then carrying out joint training; and evaluating the inversion prediction model subjected to joint training optimization according to the evaluation index. According to the method, the problems of morbidity, multiplicity and high-dimensional complexity in electromagnetic parameter inversion are effectively solved, and the prediction precision is improved; the multi-solution problem in the electromagnetic inversion problem is effectively solved, and the overall prediction precision is improved; and a sparse variation strategy is used, so that the calculation cost is effectively reduced, the calculation complexity of the model is reduced, the loss can be smoothly adjusted, and the stability of joint training is improved.

The invention belongs to the technical field of radar stealth testing, and particularly relates to a method for obtaining background scattering by measuring the RCS of a cone and a related device. The method comprises the following steps: mounting an eccentric cone on a low-scattering bracket, and enabling the mounting center of the eccentric cone to coincide with the rotating center of a rotary table of the low-scattering bracket; transmitting radar waves to the eccentric cone, rotating the turntable by a set angle at a fixed step length, and collecting echo signals of the eccentric cone rotating by the set angle; and performing fitting based on the acquired echo signal to obtain a background signal. According to the method, an eccentric cone is used as a calibration carrier, a high-signal-to-noise-ratio circular track is formed on a complex plane when the eccentric cone rotates, an optimal circle model is fitted by adopting an RANSAC method, and abnormal value elimination and background estimation are synchronously realized.

The invention discloses a radar low-altitude target recognition method based on a multi-dimensional feature nonlinear coupling network, and relates to the technical field of radar target intelligent recognition. The method comprises the following steps: inputting a distance-Doppler (RD) image into a trained nonlinear coupling network, and obtaining a prediction probability of at least one candidate category corresponding to a target; according to a candidate category obtained through a radar cross section (RCS) value of a target, the prediction probability of the candidate category is adjusted, the target category of the target is determined to be the candidate category with the maximum prediction probability, and the nonlinear coupling network comprises a feature extraction enhancement module, a feature decoupling fusion module, a feature modeling module and a prediction module. Therefore, the identification precision, the anti-interference capability and the robustness of the radar low-altitude target can be improved.

The invention discloses a multispectral compatible camouflage and radiant heat management device and a multispectral camouflage system based on the same, relates to the field of multispectral camouflage materials and heat management, and aims to solve the problems of poor spectrum compatibility, narrow bandwidth, insufficient heat management and high angle sensitivity in the prior art. A phase change material layer is arranged on the metal substrate layer, and a phase regulation and control layer of a chessboard structure is arranged on the phase change material layer. According to the invention, the radar scattering cross section is large, the specular reflectance is very low, the performance can still be maintained in the incidence angle range of 0-30 degrees, the reflectance is not sensitive to the incidence angle and the polarization state, laser stealth, radar stealth and infrared camouflage can be realized, the spectrum compatibility is good, the bandwidth is wide, dynamic heat dissipation in a non-window can be realized, and the performance is stable. And the heat management effect is achieved.

The invention discloses a stealth coating material for aviation aircrafts. According to the invention, a three-layer composite structure design is adopted; the intelligent sensing layer is composed of graphene quantum dots and a piezoelectric nanofiber composite network, so that real-time sensing of electromagnetic wave signals is realized; the tunable metamaterial layer comprises a liquid crystal elastomer matrix and nickel-titanium alloy nanowires dispersed in the liquid crystal elastomer matrix, and electromagnetic parameters of the material are dynamically adjusted by applying an electric field or a temperature field; vanadium dioxide nanoparticles, a photonic crystal structure and carbon nanotube aerogel are integrated in the multispectral stealth layer, and radar, infrared and visible light multispectral synergistic stealth is achieved. The coating is further integrated with a microencapsulation repairing agent and an intelligent control system, and has the self-repairing and self-adaptive adjusting functions. Compared with the prior art, 0.1-40 GHz ultra-wide frequency band radar wave absorption is achieved, the radar cross section is reduced by 25-30 dB, the infrared radiation characteristic is reduced by 80% or above, the surface density is only 1.2-1.5 kg / m, the weight is reduced by 65% compared with a traditional coating, and a key material technical support is provided for a new generation of stealth aircrafts.

Methods and apparatus are disclosed for communicating infrastructure information to a vehicle via ground penetrating radar. A vehicle includes an antenna positioned to broadcast radio waves downward of the vehicle, a ground penetrating radar system, and an active safety module. The ground penetrating radar system determines types of reflectors and spatial relationships between the reflectors from radar cross sections detected by the antenna, and generates a signal from the shapes and spatial relationships. The active safety module determines environmental data from the signal, and autonomously controls the vehicle from the environmental data.

The invention provides a satellite-borne SAR radiometric calibration precision evaluation method and system, a medium and equipment, and belongs to the technical field of radiometric calibration, and the method comprises the steps: recognizing and analyzing an error source which affects the calibration precision; selecting a flat area as a calibration field according to the error source; arranging a plurality of standard calibration devices with known radar cross sections in an imaging band according to the satellite top crossing position and the wave position; controlling the satellite-borne SAR to irradiate the selected area at a specified wave position, acquiring and processing scene echo data, and generating an SAR image; according to the SAR image and a known radar cross section, calculating a radar cross section measurement value; and evaluating the satellite-borne SAR radiometric calibration precision according to the measured value of the scattering sectional area and the true value of the scattering sectional area. According to the method, multiple types of error sources in the radiometric calibration link are identified and analyzed, the calibration field is selected and multiple standard calibration devices are arranged based on the error sources, and the actually measured data are compared with the true value, so that the accuracy and credibility of radiometric calibration precision evaluation are improved.

The application discloses a broadband low radar scattering cross section antenna loaded with an ATFSS, which comprises three layers of dielectric plates, namely, an upper layer plate, a middle layer plate and a lower layer plate, the upper surface and the lower surface of the upper layer plate are attached with wave absorbing structures, the lower surface of the middle layer plate is attached with a band-pass FSS structure, the upper surface of the lower layer plate is attached with a patch antenna, the lower surface of the lower layer plate is a metal ground plate, coaxial line feeding is adopted, and the upper layer plate, the middle layer plate and the lower layer plate are all air cavities. The broadband low radar scattering cross section antenna adopts the wave absorbing structure with a multi-resonance structure and the band-pass FSS structure, can realize the integrated characteristics of wave absorption and wave transmission, and the wave absorbing structure and the band-pass FSS can be loaded as a coating above the microstrip patch antenna to realize the RCS reduction in a wide frequency band under the condition of ensuring the normal radiation of the antenna.

The invention discloses a tracking system and method based on millimeter wave radar end-to-end multi-target detection, and mainly solves the problems of low detection precision and poor tracking stability of pedestrians, non-motor vehicles and motor vehicles in a complex traffic scene in the prior art. The system comprises a radar signal processing unit, a radar detection and identification network and a DeepSORT tracking module. The radar detection and identification network adopts a hybrid architecture comprising an encoder and a decoder, and the encoder comprises a 3D CNN network and an expansion convolution DAM module; the decoder comprises a T-W / SW-MSA module and a full connection layer, according to the DeepSORT tracking module, a radar cross section RCS value and micro-Doppler radar physical characteristics are introduced, cascade matching and confirmation of a new trajectory state are added, so that the stability and robustness of target tracking are improved, and long-term stable tracking of a target is achieved by fusing a target detection result and combining a Hungary algorithm and a Kalman filtering technology. The method is high in detection precision and good in tracking stability, and can be used for intelligent traffic and automatic driving.

This invention discloses a method for obtaining the wide-angle single-station RCS of a medium target based on a compressed sensing algorithm. The steps are as follows: setting a wide-angle uniform incident plane wave illuminating the medium target; defining RWG basis functions and calculating the excitation vector for each incident angle; performing sparsification and compression on the excitation vectors respectively; generating the PMCHWT equations for the target surface and solving to obtain the compressed induced electromagnetic current matrix; recovering the original induced electromagnetic current matrix from each column of the compressed induced electromagnetic current matrix using the OMP algorithm; and calculating the radar cross section of the medium target based on the induced electromagnetic current vectors. This invention can obtain the RCS result at any angle with fewer PMCHWT equation solutions and combined with the OMP recovery algorithm, reducing the solution time for the wide-angle RCS of the medium target while ensuring accuracy.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products are provided for object detection over a wireless network. A method performed by a wireless transmit / receive unit (WTRU) includes receiving, from a wireless network, a configuration that includes a configured target profile for a target and information indicative of an identification of the target, wherein the configured target profile comprises a radar cross section profile associated with the target; receiving at least one signal from the wireless network; generating a measured profile based on the at least one signal; determining that the at least one signal was reflected by the target based at least in part on the information indicative of the identification of the target and a comparison between the configured target profile and the measured profile; and performing sensing measurements associated with the target using the at least one signal based at least in part on the determination.

The invention discloses a wave-absorbing metasurface low-profile wide-angle RCS (radar cross section) reduction tight coupling dipole antenna. The array is composed of a radiation layer, a middle layer, a wave-absorbing metasurface layer and a metal ground layer. The top layer of the radiation layer is a dipole antenna, and the tail ends of radiation arms of the dipole antenna are loaded with coupling patches through metal through holes; the middle layer is a dielectric substrate; the top layer of the wave-absorbing metasurface layer is a pair of symmetrical trident-shaped resistive films loaded with metal through holes, and the bottom layer of the wave-absorbing metasurface layer is a dielectric substrate; the metal ground layer is located at the lowermost layer. According to the invention, the wave-absorbing metasurface is embedded in the tight coupling dipole array antenna to replace a traditional metal ground, so that a low-profile structure is realized. According to the antenna, within the frequency band of 7-14 GHz, the wave absorbing efficiency is higher than 75% when electromagnetic waves are incident at the wide angle of 0-60 degrees, meanwhile, good radiation performance and wide-angle scanning capacity are kept, and the radar cross section is remarkably reduced. The method can be popularized to the low radar cross section design of a traditional antenna, and is suitable for radar and wireless communication systems.

The application discloses an end-to-end high-dynamic target recognition method based on a self-attention mechanism, relates to the field of high-dynamic target recognition, and can effectively extract time sequence change features, has a high-dynamic target recognition algorithm with high reasoning speed, and can still realize robust recognition performance in a complex scene with multiple targets and high noise. The technical scheme of the application comprises the following steps: step one: obtaining radar scattering cross section data of a high-dynamic target, pre-processing, and dividing into time sequence segments of different scales as multi-scale samples. Step two: deep feature extraction is performed on the multi-scale time sequence data to obtain feature encoding of different scales of the target RCS, which is recorded as deep RCS features. Step three: the deep RCS features are classified to obtain a target recognition result.

This invention belongs to the field of computational electromagnetics numerical simulation and provides a simulation method for electromagnetic scattering of thin-coated targets based on Schur complement preconditions. First, for the IBC scattering target to be solved, equivalent surface current and equivalent surface magnetic current are introduced as independent unknowns. The electromagnetic scattering solution equation is established using SDIE and then discretized. Next, the impedance matrix is ​​decomposed into near-field and far-field matrices using an octree structure. For the near-field matrix, key operator sub-blocks are explicitly assembled and extracted. Then, approximate operators in block diagonal form and Schur complement operators are constructed and approximately inverted. Simultaneously, the diagonal product of intermediate blocks is pre-calculated and stored based on the approximate operators. Finally, the constructed preconditions are applied to the GMRES iterative solver. When the iteration error reaches the preset convergence criterion, the current and magnetic current distributions on the target surface are output. Further calculations of radiation characteristic parameters such as the target's radar cross section are then performed, achieving low-cost, high-efficiency, and easily parallelizable electromagnetic simulation solutions.

This invention relates to the field of RCS testing technology, specifically to an image-domain-based near-field anomalous scattering filtering method. The method first obtains a raw near-field image by near-field imaging of the acquired near-field swept data. Second, based on set anomalous scattering judgment conditions, the anomalous scattering centers are identified and extracted. Then, using a point target as a reference object, the scattering field distribution in the determined filtering area is simulated and reconstructed to generate a new near-field image. Finally, it is determined whether the new near-field image meets the anomalous scattering judgment conditions. If not, a filtered near-field image is generated. By identifying and removing scattering centers that do not belong to the test target from the two-dimensional image generated by the near-field imaging, near-field clutter suppression and higher-precision radar cross section testing are achieved.

The present invention relates to a phased array tracking method based on four-dimensional joint weighted dynamic pre-switching, and belongs to the field of phased array communication technology. The present invention includes: updating the spatiotemporal correlation parameters to the target historical motion trajectory database, generating the target state prediction value based on the UKF prediction method; starting the four-dimensional joint gradual weighting program, performing linear phase interpolation in the time delay dimension, and generating a phase-continuous control signal; solving the mutual coupling matrix, establishing a cross-array phase mapping model based on cubic spline interpolation, and compensating for the residual phase error; dynamically adjusting the number of effective array elements participating in beam synthesis according to the real-time radar scattering cross section, generating the final beam pointing signal, and completing the stable relay tracking of the current cycle. The present invention solves the problems of phase jump and signal attenuation during multi-array switching, and is suitable for continuous tracking of UAVs in high-speed moving scenarios.

The invention provides a honeycomb chessboard array broadband RCS reduction metasurface device, and relates to the field of electromagnetic signal detection, the method comprises a metal grounding layer, a unit layer and a packaging layer, the unit layer is arranged on the metal grounding layer, the unit layer comprises a first type of metasurface unit and a second type of metasurface unit, and the packaging layer is arranged on the first type of metasurface unit and the second type of metasurface unit. The first type of metasurface units and the second type of metasurface units are arranged in a mixed mode according to a specific period rule, the first type of metasurface units comprise a plurality of first patch units, each first patch unit comprises a plurality of first rectangular metal patches, and the second type of metasurface units comprise a plurality of second patch units. Each second patch unit comprises a second rectangular metal patch and a third metal patch, the third metal patch surrounds the second rectangular metal patch, the shape of the third metal patch is a semi-hexagonal ring, and the packaging layer is arranged on the unit layer. Through the first type of metasurface units and the second type of metasurface units, it is ensured that efficient and stable radar cross section (RCS) reduction performance is achieved within the X-waveband range.

The present application relates to a kind of radar scattering cross section test methods based on deep learning and ISAR imaging inversion, the method includes using ISAR imaging test mode to obtain target and calibration body broadband radar scattering echo signal, calibration processing and applying filter-inverse projection imaging algorithm to carry out ISAR imaging, application completes the deep learning model of accurate extraction ISAR image scattering signal area, application FFT transform-interpolation integral ISAR imaging inversion algorithm high-precision inversion reconstruction RCS value, change ISAR imaging aperture center azimuth angle traversal acquisition target all azimuth angle RCS data.The radar scattering cross section test method based on deep learning and ISAR imaging inversion provided by the present application solves the accurate extraction ISAR image scattering area and ISAR image high-precision inversion reconstruction RCS and other test practical problems, expands RCS data acquisition method.