A time modulation metasurface false target intelligent generation method and system capable of distributed expansion
By integrating tunable electronic devices and constructing a 1-bit phase-coded modulation mechanism in a time-modulated metasurface unit, and combining it with a particle swarm optimization algorithm, multi-node distributed collaborative expansion was achieved. This solved the problem of intelligent and distributed expansion of false target generation in existing radar jamming technologies, and improved the flexibility and realism of the jamming system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2026-04-30
- Publication Date
- 2026-07-10
AI Technical Summary
Among existing radar jamming technologies, metasurface jamming methods lack intelligent design capabilities, making it difficult to generate realistic false targets in multi-dimensional space. Furthermore, single-platform systems are limited in terms of energy aggregation and spatial freedom, failing to meet the countermeasure requirements of networked radar detection environments.
By integrating tunable electronic devices into time-modulated metasurface units, a 1-bit phase-coded modulation mechanism and modulation waveform library are constructed. Combined with a physical constraint-based particle swarm optimization algorithm, multi-node distributed collaborative expansion is achieved to generate a controllable spurious target cluster.
It enables the controllable generation of false targets in the range dimension and the range-velocity two-dimensional space, improving the flexibility, efficiency and application range of the jamming system, and enhancing the realism and robustness of the false targets.
Smart Images
Figure CN122362299A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of novel artificial electromagnetic metamaterials and radar countermeasures technology, and more specifically to a distributed and scalable method and system for intelligent generation of time-modulated metasurface false targets. Background Technology
[0002] With the rapid development of modern radar detection technology, especially the widespread application of frequency-modulated continuous wave radar in target detection, range estimation, and Doppler velocity measurement, the survival pressure in the battlefield electromagnetic environment is increasing daily. To counter these high-performance detection systems, radar jamming technology has become a key means of ensuring target survival.
[0003] Traditional radar jamming methods are mainly divided into active jamming and passive jamming. Active jamming typically relies on active jammers such as digital radio frequency storage (DRFS) to generate false targets by intercepting, delaying, and relaying radar signals. However, such devices have complex circuit structures, are expensive, and consume a lot of power. More importantly, active jamming sources themselves emit high-intensity electromagnetic energy, posing a very high risk of exposure to modern radar passive detection or anti-radiation missiles. Passive jamming, such as corner reflectors and chaff, while offering better concealment, has fixed scattering characteristics after processing, lacking flexibility and making it difficult to simulate complex dynamic targets with specific motion characteristics. These methods are easily identified and eliminated by advanced signal processing algorithms.
[0004] In recent years, the emergence of electromagnetic metasurfaces has provided a new technological path for radar countermeasures. Metasurfaces, through the arrangement of subwavelength units, can achieve flexible control over the phase, amplitude, and frequency of incident waves. This provides radar jamming with a low-power, lightweight, and highly reconfigurable technique, enabling it to overcome the physical limitations of traditional jamming devices, such as large size, obvious characteristics, and fixed scattering modes. However, existing metasurface jamming methods still face significant bottlenecks in practical applications, as detailed below: On the one hand, existing metasurface time modulation strategies lack intelligent design capabilities, primarily relying on manually set periodic modulation sequences to alter the echo spectrum. This approach can only generate simple, pre-defined false targets, making real-time adjustments difficult to adapt to complex mission requirements. When jamming missions involve multi-dimensional space, such as simultaneously altering range and velocity offsets, and the combination space grows explosively, traditional manually set sequences cannot find the optimal solution within the physically feasible domain. This results in generated false targets often exhibiting unrealistic distribution patterns on radar, failing to achieve deep deception.
[0005] On the other hand, existing systems lack distributed scalability and collaborative capabilities. Current research largely focuses on single-platform, small-aperture applications. Limited by the physical size and electromagnetic reflection efficiency of individual metasurfaces, false targets generated by a single platform often fail to match the energy aggregation of real large targets, making them easily detectable by radar through power detection algorithms. Furthermore, single-platform systems have limited spatial freedom, making it difficult to construct complex, large-scale electromagnetic illusion environments over a wide area. In future networked radar detection environments, single-point jamming methods are insufficient to meet countermeasure requirements. Therefore, overcoming the physical limitations of single platforms and constructing a distributed, scalable collaborative architecture that utilizes multiple discretely deployed metasurface nodes in space to achieve coherent energy synthesis and spatiotemporal pattern coordination is a core technological direction for improving the realism, robustness, and coverage of jamming systems.
[0006] In summary, developing a time-modulated metasurface system that possesses both intelligent reverse design capabilities and supports distributed spatial expansion is of significant scientific and engineering value for achieving high-fidelity, reconfigurable multidimensional radar deception and jamming, and is also a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention
[0007] In view of this, the present invention provides a distributed and scalable method and system for intelligent generation of time-modulated metasurface false targets, in order to solve the problems existing in the current radar countermeasures technology, such as fixed jamming patterns, limited jamming energy of single nodes, and difficulty in constructing customizable false target clusters in the range dimension and range-velocity two-dimensional space.
[0008] To achieve the above objectives, the present invention provides the following technical solution: A distributed and scalable method for intelligently generating false targets on time-modulated metasurfaces includes the following steps: S1. Integrate adjustable electronic devices in the time-modulated metasurface unit, and switch the time-modulated metasurface unit between at least two discrete electromagnetic states by controlling the bias voltage to achieve dynamic modulation of the complex reflection coefficient. S2. Construct a 1-bit phase coding modulation mechanism based on at least two discrete electromagnetic states, establish a modulation waveform library consisting of different modulation frequencies and / or duty cycles, select the target modulation waveform from the modulation waveform library, and reconstruct the radar echo spectrum to generate preset harmonic components. S3. Apply the target modulation waveform within a single fast-time frequency sweep cycle of the radar to cause a spectral shift in the echo signal, generating false targets distributed along the range dimension. S4. Apply a differentiated time modulation sequence between multiple consecutive radar frames to cause the echo signal to have a Doppler shift in the slow time dimension, generating false targets with a two-dimensional distribution in the range and velocity dimensions. S5. Receive a preset false target template, extract the distance and velocity interval information between targets, generate a candidate modulation parameter set based on the physical mapping relationship between modulation parameters and distance offset and velocity offset and in combination with the modulation waveform library, and optimize the candidate modulation parameter set using a particle swarm optimization algorithm based on physical constraints to obtain the optimal time modulation sequence. S6. Load the optimal time modulation sequence into the metasurface control system to generate a false target corresponding to the preset false target template; S7. Extend the methods described in S1-S6 to a multi-node distributed system, jointly design the time modulation sequence of each node, so that multiple nodes form coherent echo superposition at a preset distance-velocity position, and generate a collaboratively synthesized false target echo at the radar receiver.
[0009] Optionally, in S1, the time-modulated metasurface unit is a reflective structure, including a top metal patch, a dielectric substrate, a metal ground layer, and PIN diodes connected between the top metal patches. The PIN diodes switch between an on state and an off state, so that the time-modulated metasurface unit switches between at least two discrete electromagnetic states.
[0010] Optionally, in S1, the dynamic modulation of the complex reflection coefficient is as follows: In a reflective structure, the modulation period is... Divided into equal parts The reflection coefficient remains constant within each time segment, and the overall reflection coefficient changes over time using a time modulation function. Represented as a piecewise constant function:
[0011] In the formula: Indicates width is A periodic unit rectangular pulse signal, by selecting different reflection coefficients Combining them can alter the harmonic distribution of the echo.
[0012] Optionally, in S2, the modulation waveform library is a square wave modulation waveform library, and multiple square wave modulation waveforms are indexed according to modulation frequency, duty cycle and corresponding distance offset characteristics and velocity offset characteristics. Based on a 1-bit phase-coded modulation mechanism, the time modulation function corresponding to the target modulation waveform selected from the square wave modulation waveform library is... It can be expanded into a harmonic superposition form:
[0013] In the formula: For the first q First harmonic coefficient, The modulation frequency corresponding to the target modulation waveform; When a square wave modulation waveform with a 50% duty cycle is selected as the target modulation waveform, the fundamental and even harmonic components of the echo spectrum are suppressed, and the echo energy is mainly distributed to the odd harmonic components. The spacing between adjacent spectral components is determined by the modulation frequency. Decide.
[0014] Optionally, the specific operation of S3 is as follows: Establish a joint model of the time-modulated metasurface and the frequency-modulated continuous wave radar signal processing chain. When the target surface is covered by the time-modulated metasurface, after sampling and discrete Fourier transform, the radar calculates the range offset. for:
[0015] In the formula: q For intra-frame modulation harmonic order, B For radar frequency modulation bandwidth, c At the speed of light, The modulation frequency corresponding to the target modulation waveform. This refers to the radar's fast frequency sweep period.
[0016] Optionally, in S4, a differentiated time modulation sequence is applied between multiple consecutive radar frames, specifically: When a time-modulated metasurface applies differentiated modulation signals to different fast time frames, the time-varying reflection characteristics introduce dynamic modulation in the slow time dimension, thereby inducing a velocity solution offset. for:
[0017] In the formula: w For inter-frame modulation harmonic order, To adjust the repetition frequency between frames, For radar operating wavelength, This refers to the radar's fast frequency sweep period.
[0018] Optionally, in S5, a physics-constrained particle swarm optimization algorithm is used to optimize the candidate modulation parameter set, specifically as follows: The problem of generating a specific cluster of false targets is abstracted into a high-dimensional discrete sequence optimization problem. The modulation parameter is the modulation frequency corresponding to the modulation waveform in the modulation waveform library or the index of the modulation waveform in the modulation waveform library. It is assumed that each particle corresponds to a candidate inter-frame modulation frequency sequence. ,in For sequence length, For the first i The particle in the first jThe modulation frequency corresponding to each radar frame; extract range offset and velocity offset information according to the preset false target template; generate a set of candidate modulation frequencies that meet the constraints in reverse according to the physical mapping relationship between range offset and velocity offset; and sample and generate initial particles from the frequencies that meet the physical constraints during the initialization phase. The radar range-velocity spectrum data corresponding to each particle is calculated forward using a physical analytical model. The structural similarity index SSIM is used as the fitness function to iteratively update the particle position and velocity, and output the optimal time modulation sequence.
[0019] Optionally, the specific operation of S6 is as follows: Based on the initial distance and radial velocity of the time-modulated metasurface, the coordinate relationship of each target point in the preset false target template is converted into the corresponding distance offset feature and velocity offset feature, which serve as the solution constraint for the optimal time-modulated sequence. The pre-set false target template is reverse-engineered using a particle swarm optimization algorithm based on physical constraints. The optimal time modulation sequence that meets the template requirements is automatically calculated and loaded into the metasurface control system to generate a false target cluster corresponding to the pre-set false target template.
[0020] Optionally, in S7, the distributed system includes multiple spatially distributed time-modulated metasurface nodes, expanding the time modulation sequence of a single node into a multi-node collaborative modulation sequence; the time modulation sequences of each time-modulated metasurface node are jointly designed and synchronized to enable the echo signals of each node at the radar receiver to form coherent superposition at a preset range-velocity position, thereby enhancing the echo energy of false targets and constructing a distributed false target cluster.
[0021] A distributed and scalable intelligent system for generating false targets on time-modulated metasurfaces, comprising executing any one of the above-described distributed and scalable intelligent methods for generating false targets on time-modulated metasurfaces, including: A time-modulated metasurface module is used to achieve dynamic modulation of the complex reflection coefficient through tunable electronic devices; The control drive and synchronization module is used to output intra-frame modulation instructions and inter-frame modulation instructions to the time modulation metasurface module, and to provide a unified time reference in single-node mode or multi-node distributed mode. The modulation waveform library module is used to store a collection of modulation waveforms consisting of different modulation frequencies and / or duty cycles; The time modulation sequence intelligent design module is used to receive a preset false target template, extract the distance and velocity interval information between targets, and generate the optimal time modulation sequence by combining the physical mapping relationship and the modulation waveform library; The distributed collaborative control module is used to expand a single time-modulated metasurface node into multiple spatially discrete time-modulated metasurface nodes, and to jointly optimize and coordinate the time-modulation sequences of each node.
[0022] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a distributed and scalable method and system for intelligent generation of time-modulated metasurface false targets, which has the following beneficial effects: (1) The modulation strategy is programmable and modularly reused by using a time-modulated metasurface and a modulation waveform library; (2) Establish the physical mapping relationship between modulation parameters and range and velocity offset to realize the controllable generation of false targets in the range dimension and the range-velocity two-dimensional space; (3) A smart design method based on physical constraint particle swarm optimization is proposed to realize the automatic solution from target template to modulation sequence; (4) Supports multi-node distributed collaborative expansion, which can realize the energy enhancement of false targets and the construction of complex clusters.
[0023] In summary, this invention combines time-modulated metasurfaces, electromagnetic spectrum control mechanisms, and intelligent optimization algorithms, and further extends this to a distributed collaborative architecture, thereby achieving intelligent generation of false targets and significantly improving the system's flexibility, efficiency, and application scope. Attached Figure Description
[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0025] Figure 1 This is a schematic diagram of the overall process of a distributed and scalable time-modulated metasurface false target intelligent generation scheme provided by the present invention; Figure 2 This is a schematic diagram of the time-modulated metasurface unit structure based on 1-bit phase coding described in an embodiment of the present invention; Figure 3 This is a schematic diagram of echo spectrum reconstruction based on a 50% duty cycle square wave drive signal in an embodiment of the present invention; Figure 4 This is a flowchart illustrating the intelligent design of time-modulated sequences based on a physically constrained particle swarm optimization algorithm in an embodiment of the present invention. Figure 5 This is a schematic diagram of a preset complex fake target cluster template in an embodiment of the present invention; Figure 6 This is a schematic diagram illustrating the deployment of the distributed collaborative architecture in a space exploration scenario according to an embodiment of the present invention; Figure 7 This is a schematic diagram illustrating the implementation of false target energy enhancement based on a distributed architecture in an embodiment of the present invention; Figure 8 This is a schematic diagram of a complex fake target cluster implemented based on a distributed architecture in an embodiment of the present invention. Detailed Implementation
[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0027] See Figure 1 This invention discloses a distributed and scalable method for intelligently generating false targets on time-modulated metasurfaces, comprising the following steps: S1. Integrate adjustable electronic devices in the time-modulated metasurface unit, and switch the time-modulated metasurface unit between at least two discrete electromagnetic states by controlling the bias voltage to achieve dynamic modulation of the complex reflection coefficient. S2. Construct a 1-bit phase coding modulation mechanism based on at least two discrete electromagnetic states, establish a modulation waveform library consisting of different modulation frequencies and / or duty cycles, select the target modulation waveform from the modulation waveform library, and reconstruct the radar echo spectrum to generate preset harmonic components. S3. Apply the target modulation waveform within a single fast-time frequency sweep cycle of the radar to cause a spectral shift in the echo signal, generating false targets distributed along the range dimension. S4. Apply a differentiated time modulation sequence between multiple consecutive radar frames to cause the echo signal to undergo Doppler shift in the slow time dimension, generating false targets with a two-dimensional distribution in the range and velocity dimensions. S5. Construct a time modulation sequence intelligent design method based on physical constraint particle swarm optimization. Receive a preset false target template, extract the distance and velocity interval information between targets, generate a candidate modulation parameter set based on the physical mapping relationship between modulation parameters and distance and velocity offsets, and combine it with a modulation waveform library. Optimize the candidate modulation parameter set using a physical constraint particle swarm optimization algorithm to obtain the optimal time modulation sequence. S6. Load the optimal time modulation sequence into the metasurface control system to generate a false target corresponding to the preset false target template; S7. Extend the methods described in S1-S6 to a multi-node distributed system, jointly design the time modulation sequence of each node, so that multiple nodes form coherent echo superposition at a preset distance-velocity position, generate collaboratively synthesized false target echoes at the radar receiver, and realize the enhancement of false target energy and the generation of complex false target clusters.
[0028] Next, for Figure 1 The process shown is described in detail to further understand the technical solution protected by this invention.
[0029] I. Time-Modulated Metasurface Unit
[0030] In step S1 of this embodiment, the time-modulated metasurface is the core hardware for radar jamming in this system. Its key feature is that the adjustable electronic devices integrated in the time-modulated metasurface unit can achieve dynamic programmable control of the phase and amplitude of the reflection or projection coefficients under the drive of an external time-varying control signal.
[0031] This embodiment employs a reflective metasurface unit structure based on 1-bit phase coding, meaning the time-modulated metasurface unit is a reflective structure. For example... Figure 2 As shown, this unit includes a top metal patch, a dielectric substrate, a metal ground layer, and PIN diodes connected between the top metal patches, preferably SMP1340-040LF type devices. The PIN diodes correspond to different equivalent impedance states when switching between on and off states. By adjusting the bias voltage, the time-modulated metasurface unit switches between at least two discrete electromagnetic states. This structure employs a direct surface-fed method, with the two ends of the patch connected to the positive and negative terminals of the control circuit, respectively, to reduce the complexity of the feed network.
[0032] Preferably, within the target operating frequency band, the reflection phase difference between the two states is close to 180°, and the reflection amplitude meets the preset amplitude difference requirement, so as to achieve stable 1-bit phase modulation.
[0033] In the aforementioned reflective architecture, it is assumed that all elements have the same reflection response at the same time, and the overall reflection coefficient changes with time as denoted as . Modulation period Divided into equal parts There are 3 time segments, and the reflection coefficient within each time segment remains constant and is denoted as . The time modulation function of the overall reflectance coefficient changing with time Represented as a piecewise constant function:
[0034] In the formula: Indicates width is A periodic unit rectangular pulse signal, by selecting different reflection coefficients Combining them can alter the harmonic distribution of the echo.
[0035] II. Modulation Waveform Library
[0036] In S2 of this embodiment, the modulation waveform library is a square wave modulation waveform library. Multiple square wave modulation waveforms are indexed according to their modulation frequency, duty cycle, and corresponding range and velocity offset characteristics. S2 utilizes a 1-bit phase-coded metasurface to establish the modulation waveform library and calls square wave drive signals from the library to control the radar echo spectrum, as detailed below: S21. In one embodiment, the reflection phase is... and Switching between two states; based on a 1-bit phase-coded modulation mechanism, a pre-constructed system consisting of multiple different modulation frequencies. Alternatively, a square wave modulation waveform library composed of different duty cycles, each modulation waveform corresponding to different spectral reconstruction characteristics.
[0037] Preferred, a periodic square wave signal with a duty cycle of 50% is selected from the square wave modulation waveform library as the driving command. This can be considered as... In the second-order modulation mode, the time modulation function corresponding to the target modulation waveform is... It can be expanded into a harmonic superposition form:
[0038] In the formula: For the first q First harmonic coefficient, The modulation frequency corresponding to the target modulation waveform.
[0039] S22. When a square wave modulation waveform with a 50% duty cycle is selected as the target modulation waveform, the fundamental and even harmonic components of the echo spectrum are suppressed, and the echo energy is mainly distributed to the odd harmonic components. The spacing between adjacent spectral components is determined by the modulation frequency. Decision, such as Figure 3 As shown.
[0040] Therefore, by selecting modulation waveforms with different modulation frequencies or duty cycles from the modulation waveform library, it is possible to control the position of the echo spectrum and the distribution of harmonics.
[0041] III. Controllable Generation of False Targets in the Distance Dimension
[0042] In S3 of this embodiment, a joint model of the time-modulated metasurface and the frequency-modulated continuous wave radar signal processing chain is established to achieve controlled offset of the radar range-direction beat frequency signal, as follows: S31, Frequency Modulated Continuous Wave Radar in each fast time frame period Internal emission linear frequency modulation signal Its modulation frequency is Target echo signal The intermediate frequency signal is obtained after mixing and low-pass filtering. The initial distance to the target is determined by calculating its frequency difference. The estimate.
[0043] S32. When the target surface is covered by a time-modulated metasurface, the received signal is subject to a dynamic modulation function. Function, modulated interference intermediate frequency signal It manifests as the superposition of multiple modulation frequency harmonic components:
[0044] In the formula: The intermediate frequency of the original target. For the metasurface modulation frequency, These are the coefficients of the Fourier series. v Let c be the radial velocity of the target, and c be the speed of light. For carrier frequency.
[0045] After sampling and discrete Fourier transform, the spectral line shift directly leads to the range shift calculated by the radar. for:
[0046] In the formula: q For intra-frame modulation harmonic order, B For radar frequency modulation bandwidth, c At the speed of light, The modulation frequency corresponding to the target modulation waveform. This refers to the radar's fast frequency sweep period.
[0047] By controlling the square wave modulation frequency It can achieve programmable control over the distance and position of false targets.
[0048] IV. Controllable Generation of False Targets in the Distance-Velocity Two-Dimensional Space
[0049] In S4 of this embodiment, a multi-dimensional modulation model combining intra-frame and inter-frame modulation is established to achieve coordinated control of radar echoes in the range and velocity dimensions, as detailed below: S41, Frequency Modulated Continuous Wave Radar analyzes continuous wave... M The Doppler frequency is extracted by analyzing the phase changes of the fast frame echoes at specific distance spectral lines. In the unmodulated state, the first... m The slow-time signal of a frame is represented as The position of its velocity spectral line after discrete Fourier transform is Reflects the true radial velocity of the target v .
[0050] S42. When a time-modulated metasurface applies differentiated modulation signals to different fast time frames, its time-varying reflection characteristics introduce a dynamic modulation function in the slow time dimension. ,Will Expand into Fourier series form ,in To adjust the repetition frequency between frames, it is defined as , To control the number of fast frames within a cycle.
[0051] Position of the disturbed velocity spectral line after discrete Fourier transform Generate offset The resulting velocity calculation offset for:
[0052] In the formula: w For inter-frame modulation harmonic order, To adjust the repetition frequency between frames, For radar operating wavelength, This refers to the radar's fast frequency sweep period.
[0053] By setting the inter-frame modulation rules and inter-frame repetition frequency This allows for control over the velocity characteristics of false targets. Combined with intra-frame modulation in step S32, a two-dimensional false target distribution that is jointly controllable in both the range and velocity dimensions can be formed.
[0054] V. Optimal Time Modulation Sequence
[0055] In S5 of this embodiment, a physically constrained particle swarm optimization (PC-PSO) intelligent design method is established based on the time-modulated metasurface, the modulation waveform library, and the physical analytical model of the FMCW radar to achieve the reverse design of the modulation sequence of complex false target clusters, as detailed below: S51. The problem of generating a specific cluster of false targets is abstracted into a high-dimensional discrete sequence optimization problem. The modulation parameter is preferably the modulation frequency corresponding to a certain modulation waveform in the modulation waveform library or the index identifier of that modulation waveform in the modulation waveform library. Assume that each particle corresponds to a candidate inter-frame modulation frequency sequence. ,in For sequence length, For the first i The particle in the first j The modulation frequencies corresponding to each radar frame, the modulation frequencies being from a discrete set F Selected from the options.
[0056] Based on the preset false target template, the distance offset and velocity offset information are extracted. Based on the physical mapping relationship of distance offset and velocity offset in steps S31 and S41, a set of candidate modulation frequencies that meet the constraints is generated in reverse. In the initialization stage, initial particles are generated by sampling from the frequencies that meet the physical constraints to reduce invalid searches.
[0057] S52. For each particle in the population, the radar range-velocity map data corresponding to each particle is calculated forward using the physical analytical model, and the structural similarity index SSIM is used as the fitness function:
[0058] In the formula: For the preset target template, For the first i The algorithm generates the corresponding results for each particle. It iteratively updates the particle position and velocity based on the fitness value. After satisfying a preset number of iterations or convergence conditions, it outputs the optimal time modulation sequence corresponding to the particle with the highest fitness, and uses this sequence as the control command for the metasurface, such as... Figure 4 As shown.
[0059] VI. Generation of Fake Target Clusters
[0060] In S6 of this embodiment, the intelligent design method of 1-bit phase-coded metasurface and time-modulated sequence is used to realize the driven production of target templates with complex geometric configurations, as follows: S61. Input a preset false target template into the intelligent design system. The preset false target template can be a regular array, an irregular array, or a complex geometric configuration template, such as... Figure 5 As shown, the system uses the initial distance and radial velocity of the time-modulated metasurface as a reference, and converts the coordinate relationship of each target point in the preset false target template into corresponding distance offset feature quantities and velocity offset feature quantities, which serve as the solution constraints for the optimal time-modulated sequence.
[0061] S62. The pre-set false target template is reverse-engineered using a particle swarm optimization algorithm based on physical constraints. The optimal time modulation sequence that meets the template requirements is automatically calculated and loaded into the metasurface control system to generate a false target cluster corresponding to the pre-set false target template.
[0062] VII. Multi-node distributed collaborative expansion
[0063] In S7 of this embodiment, the distributed system includes multiple spatially distributed time-modulated metasurface nodes, expanding the time modulation sequence of a single node into a multi-node collaborative modulation sequence; the time modulation sequences of each time-modulated metasurface node are jointly designed and synchronized to enable the echo signals of each node at the radar receiver to form coherent superposition at a preset range-velocity position, thereby enhancing the echo energy of false targets and constructing a distributed false target cluster.
[0064] Specifically, a distributed multi-platform coherent scattering and joint control model is established using a 1-bit phase-coded metasurface and time-modulated sequence intelligent design method to achieve collaborative design of multiple metasurface nodes and synthesis of spurious targets. The steps are as follows: S71. Assume that the following are discretely deployed in space. Y A time-modulated metasurface platform, such as Figure 6 As shown, each metasurface platform independently calls a specific modulation waveform from the modulation waveform library within each radar frame and applies the corresponding modulation signal. The total signal at the radar receiver... For the superposition of echoes from various platforms:
[0065] In the formula: Y The number of time-modulated metasurface nodes for spatial discrete deployment. For the first y The metasurface in the first... n The unmodulated echo signal of the frame, Let be the time modulation function of the metasurface within this frame.
[0066] S72. The representation of the intelligent design algorithm is extended from a single-node vector to a multi-node cooperative matrix. Each row of the matrix corresponds to the complete modulation sequence of a hypersurface node, and the entire matrix represents the global cooperative control strategy of the system. During the optimization process, the algorithm comprehensively considers the spatial differences of each node relative to the preset false target position and automatically generates differentiated modulation sequences for each node to achieve multi-node cooperative control.
[0067] S73. Under multi-node collaborative conditions, by jointly designing the modulation waveforms and their corresponding modulation sequences selected by each node from the modulation waveform library, multiple metasurface nodes can form a coherent superposition at a preset distance-velocity position, thereby achieving the enhancement of the false target's energy, such as... Figure 7 As shown; simultaneously, multi-node control sequences can be uniformly optimized by combining preset complex target templates to generate complex fake target clusters, such as... Figure 8 As shown.
[0068] Furthermore, embodiments of the present invention also provide a distributed and scalable time-modulated metasurface false target intelligent generation system, which can be applied to computer terminals or various mobile devices, specifically including: The time-modulated metasurface module is used to dynamically modulate the complex reflection coefficient through adjustable electronic devices. Specifically, the time-modulated metasurface module includes several periodically arranged metasurface units. Each metasurface unit integrates dynamically adjustable electronic devices, which switch between different discrete electromagnetic states under the action of an external control circuit, thereby modulating the complex reflection coefficient of the incident electromagnetic wave in time.
[0069] The control drive and synchronization module is used to output intra-frame modulation instructions and inter-frame modulation instructions to the time modulation metasurface module, and to provide a unified time base and differentiated drive control in single-node mode or multi-node distributed mode.
[0070] The modulation waveform library module is used to pre-construct a set of modulation waveforms consisting of different modulation frequencies and / or duty cycles and timing parameters; the set of modulation waveforms is preferably a square wave modulation waveform library, which can be called by the control drive and synchronization module and serves as a source of candidate parameters for intelligent design of time modulation sequences.
[0071] The time modulation sequence intelligent design module is used to receive a preset false target template, extract the distance and velocity interval information between targets, and generate the optimal time modulation sequence by combining the physical mapping relationship and the modulation waveform library; The distributed collaborative control module is used to expand a single time-modulated metasurface node into multiple spatially discrete time-modulated metasurface nodes, and to jointly optimize and coordinate the time modulation sequences of each node to achieve multi-node echo superposition, false target energy enhancement, and complex false target cluster generation.
[0072] Furthermore, the time-modulated metasurface unit is a reflective structure, including a top metal patch, a dielectric substrate, and a bottom metal ground plane, with adjustable electronic devices connected between the top metal patches; preferably, the adjustable electronic device is a PIN diode, which is controlled by a bias voltage to switch between a conducting state and a cutoff state, so that the metasurface unit switches between at least two discrete reflection states, thereby achieving 1-bit phase encoding control.
[0073] Furthermore, the modulation waveforms stored in the modulation waveform library module are indexed according to their modulation frequency, duty cycle, and corresponding distance and velocity offset characteristics, enabling the intelligent design module to quickly filter a set of candidate modulation parameters that meet physical constraints based on a preset target template.
[0074] Furthermore, the time modulation sequence intelligent design module incorporates a physical constraint particle swarm optimization algorithm. Taking a preset false target template as input, it generates a set of candidate modulation parameters based on the physical mapping relationship between distance offset and velocity offset, and outputs the optimal time modulation sequence using a structural similarity index as a fitness function.
[0075] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.
[0076] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A distributed and scalable method for intelligently generating false targets on time-modulated metasurfaces, characterized in that, Includes the following steps: S1. Integrate adjustable electronic devices in the time-modulated metasurface unit, and switch the time-modulated metasurface unit between at least two discrete electromagnetic states by controlling the bias voltage to achieve dynamic modulation of the complex reflection coefficient. S2. Construct a 1-bit phase coding modulation mechanism based on at least two discrete electromagnetic states, establish a modulation waveform library consisting of different modulation frequencies and / or duty cycles, select the target modulation waveform from the modulation waveform library, and reconstruct the radar echo spectrum to generate preset harmonic components. S3. Apply the target modulation waveform within a single fast-time frequency sweep cycle of the radar to cause a spectral shift in the echo signal, generating false targets distributed along the range dimension. S4. Apply a differentiated time modulation sequence between multiple consecutive radar frames to cause the echo signal to have a Doppler shift in the slow time dimension, generating false targets with a two-dimensional distribution in the range and velocity dimensions. S5. Receive a preset false target template, extract the distance and velocity interval information between targets, generate a candidate modulation parameter set based on the physical mapping relationship between modulation parameters and distance offset and velocity offset and in combination with the modulation waveform library, and optimize the candidate modulation parameter set using a particle swarm optimization algorithm based on physical constraints to obtain the optimal time modulation sequence. S6. Load the optimal time modulation sequence into the metasurface control system to generate a false target corresponding to the preset false target template; S7. Extend the methods described in S1-S6 to a multi-node distributed system, jointly design the time modulation sequence of each node, so that multiple nodes form coherent echo superposition at a preset distance-velocity position, and generate a collaboratively synthesized false target echo at the radar receiver.
2. The method for intelligently generating distributed and scalable time-modulated metasurface false targets according to claim 1, characterized in that, In S1, the time-modulated metasurface unit is a reflective structure, including a top metal patch, a dielectric substrate, a metal ground layer, and PIN diodes connected between the top metal patches. The PIN diodes switch between an on state and an off state so that the time-modulated metasurface unit switches between at least two discrete electromagnetic states.
3. The method for intelligently generating distributed and scalable time-modulated metasurface false targets according to claim 2, characterized in that, In S1, the dynamic modulation of the complex reflection coefficient is specifically as follows: In a reflective structure, the modulation period is... Divided into equal parts The reflection coefficient remains constant within each time segment, and the overall reflection coefficient changes over time using a time modulation function. Represented as a piecewise constant function: In the formula: Indicates width is A periodic unit rectangular pulse signal, by selecting different reflection coefficients Combining them can alter the harmonic distribution of the echo.
4. The method for intelligently generating distributed and scalable time-modulated metasurface false targets according to claim 1, characterized in that, In S2, the modulation waveform library is a square wave modulation waveform library. Multiple square wave modulation waveforms are indexed according to modulation frequency, duty cycle and corresponding distance offset characteristics and velocity offset characteristics. Based on a 1-bit phase-coded modulation mechanism, the time modulation function corresponding to the target modulation waveform selected from the square wave modulation waveform library is... It can be expanded into a harmonic superposition form: In the formula: For the first q First harmonic coefficient, The modulation frequency corresponding to the target modulation waveform; When a square wave modulation waveform with a 50% duty cycle is selected as the target modulation waveform, the fundamental and even harmonic components of the echo spectrum are suppressed, and the echo energy is mainly distributed to the odd harmonic components. The spacing between adjacent spectral components is determined by the modulation frequency. Decide.
5. The method for intelligently generating distributed and scalable time-modulated metasurface false targets according to claim 1, characterized in that, The specific operation of S3 is as follows: A joint model of the time-modulated metasurface and the frequency-modulated continuous wave radar signal processing chain is established. When the target surface is covered by the time-modulated metasurface, the range offset calculated by the radar after sampling and discrete Fourier transform is... for: In the formula: q For intra-frame modulation harmonic order, B For radar frequency modulation bandwidth, c At the speed of light, The modulation frequency corresponding to the target modulation waveform. This refers to the radar's fast frequency sweep period.
6. The method for intelligently generating distributed and scalable time-modulated metasurface false targets according to claim 1, characterized in that, In S4, a differentiated time modulation sequence is applied between multiple consecutive radar frames, specifically as follows: When a time-modulated metasurface applies differentiated modulation signals to different fast time frames, the time-varying reflection characteristics introduce dynamic modulation in the slow time dimension, thereby inducing a velocity solution offset. for: In the formula: w For inter-frame modulation harmonic order, To adjust the repetition frequency between frames, For radar operating wavelength, This refers to the radar's fast frequency sweep period.
7. The method for intelligently generating distributed and scalable time-modulated metasurface false targets according to claim 1, characterized in that, In S5, a physics-constrained particle swarm optimization algorithm is used to optimize the candidate modulation parameter set, specifically as follows: The problem of generating a specific cluster of false targets is abstracted into a high-dimensional discrete sequence optimization problem, and the modulation parameter is the modulation frequency corresponding to the modulation waveform in the modulation waveform library or the index identifier of the modulation waveform in the modulation waveform library. Assume each particle corresponds to a candidate inter-frame modulation frequency sequence ,in For sequence length, For the first i The particle in the first j The modulation frequency corresponding to each radar frame; Based on the preset false target template, the distance offset and velocity offset information are extracted. Based on the physical mapping relationship between the distance offset and velocity offset, a set of candidate modulation frequencies that meet the constraints is generated in reverse. In the initialization stage, the initial particles are generated by sampling from the frequencies that meet the physical constraints. The radar range-velocity spectrum data corresponding to each particle is calculated forward using a physical analytical model. The structural similarity index SSIM is used as the fitness function to iteratively update the particle position and velocity, and output the optimal time modulation sequence.
8. The method for intelligently generating distributed and scalable time-modulated metasurface false targets according to claim 1, characterized in that, The specific operation of S6 is as follows: Based on the initial distance and radial velocity of the time-modulated metasurface, the coordinate relationship of each target point in the preset false target template is converted into the corresponding distance offset feature and velocity offset feature, which serve as the solution constraint for the optimal time-modulated sequence. The pre-set false target template is reverse-engineered using a particle swarm optimization algorithm based on physical constraints. The optimal time modulation sequence that meets the template requirements is automatically calculated and loaded into the metasurface control system to generate a false target cluster corresponding to the pre-set false target template.
9. The method for intelligently generating distributed and scalable time-modulated metasurface false targets according to claim 1, characterized in that, In S7, the distributed system includes multiple spatially distributed time-modulated metasurface nodes, which expand the time modulation sequence of a single node into a multi-node collaborative modulation sequence. The time modulation sequences of each time-modulated metasurface node are jointly designed and synchronized to enable the echo signals of each node at the radar receiver to form coherent superposition at a preset range-velocity position, thereby enhancing the echo energy of false targets and constructing a distributed false target cluster.
10. A distributed and scalable time-modulated metasurface false target intelligent generation system, characterized in that, The method for intelligently generating distributed and scalable time-modulated metasurface false targets as described in any one of claims 1-9 includes: A time-modulated metasurface module is used to achieve dynamic modulation of the complex reflection coefficient through tunable electronic devices; The control drive and synchronization module is used to output intra-frame modulation instructions and inter-frame modulation instructions to the time modulation metasurface module, and to provide a unified time reference in single-node mode or multi-node distributed mode. The modulation waveform library module is used to store a collection of modulation waveforms consisting of different modulation frequencies and / or duty cycles; The time modulation sequence intelligent design module is used to receive a preset false target template, extract the distance and velocity interval information between targets, and generate the optimal time modulation sequence by combining the physical mapping relationship and the modulation waveform library; The distributed collaborative control module is used to expand a single time-modulated metasurface node into multiple spatially discrete time-modulated metasurface nodes, and to jointly optimize and coordinate the time-modulation sequences of each node.