Multi-probe spherical near-field test robot system

Abstract

The invention discloses a multi-probe spherical near-field test robot system, which relates to the technical field of near-field test and comprises a time baseline force field detection module, a phase traction energy analysis module, an anti-fact energy backtracking module, a self-adaptive decoupling correction module and a time reversal steady-state regulation and control module. And the time base line force field detection module constructs a force field detection matrix under the constraint condition of establishing a unified time base line, continuously captures weak electromagnetic responses of the metal reflector in the test cabin at different angle positions, and solidifies a capture result into a dynamic sub-resonance risk criterion. Accurate stripping of an energy abnormal source is realized through dynamic sub-resonance identification and anti-fact replay, and real radiation characteristics are kept stable; and closed-loop regulation and control are realized through adaptive decoupling mapping and time reversal compensation, false energy interference is effectively suppressed, and the precision, stability and reliability of a spherical near-field test are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of near-field testing, and in particular to a multi-probe spherical near-field testing robot system. BACKGROUND

[0002] The multi-probe spherical near-field testing robot system is an automatic testing equipment for antenna performance measurement and electromagnetic field distribution acquisition. The core idea is to build a spherical testing environment around the antenna to be tested, and arrange multiple high-precision probes to form a dense and uniform spherical sampling grid, so as to obtain the near-field distribution data of the antenna in different directions. Through the robot control platform, the probes can be flexibly scheduled and accurately positioned in the spherical space, so as to realize the rapid acquisition and stable repetition of large-scale data. Then, the system converts the acquired spherical near-field information into far-field pattern, gain, beam width, side lobe level and other key parameters by using near-far field transformation algorithm. Compared with the traditional single-probe scanning mode, the system significantly shortens the testing period, improves the data integrity and spatial resolution, and has the ability to fully cover the testing of large, wideband or multi-beam antennas, and is commonly used in the fields of satellite communication, radar detection and 5G base station antenna research and development.

[0003] The prior art has the following disadvantages: In the multi-probe spherical near-field testing process of the prior art, there are often unavoidable metal support members or reflectors inside the testing cabin. When the robot probe runs on the spherical path and triggers a large range of angle changes, these metal reflectors may form a low-probability sub-resonance effect under certain spatial position and frequency conditions. Since the sub-resonance has the characteristics of non-linear energy amplification, the local electromagnetic field strength will be abnormally enhanced, resulting in the appearance of false high-energy areas in the near-field distribution. This distortion not only hides the real radiation characteristics of the antenna to be tested, but also is further amplified in the near-far field transformation process, thereby causing serious deviation of the far-field pattern, manifesting as abnormal gain curve, beam direction deviation and abnormal rise of side lobe level, which may eventually lead to misjudgment of the antenna performance, and seriously affect the reliability of the test results and the safety of the engineering application.

[0004] The above information disclosed in the background section is only used to strengthen the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The purpose of the present application is to provide a multi-probe spherical near-field testing robot system to solve the problems in the background.

[0006] In order to achieve the above object, the present application provides the following technical scheme: a multi-probe spherical near-field test robot system, comprising a time baseline force field detection module, a phase traction energy analysis module, a counterfactual energy backtracking module, an adaptive decoupling correction module and a time reversal steady-state regulation module; The time baseline force field detection module, under the constraint condition of establishing a unified time baseline, constructs a force field detection matrix, continuously captures the weak electromagnetic response of the metal reflector in the test cabin at different angle positions, and solidifies the capture result as a dynamic subharmonic resonance risk criterion, which is used to form a reference baseline for subsequent energy field analysis. The phase traction energy analysis module, based on the dynamic subharmonic resonance risk criterion, introduces a phase traction algorithm, injects a micro-scale perturbation energy field in the test space, deeply analyzes the foregoing capture result, extracts the residual trajectory of local electric field mutation, and converts the residual trajectory into a nonlinear amplification factor field to realize accurate positioning of the energy abnormal source. The counterfactual energy backtracking module, under the support of the nonlinear amplification factor field, runs a counterfactual replay chain, time backtracks the residual trajectory, removes false energy components caused by the metal reflector structure, and retains the real radiation characteristics, thereby maintaining the stability of the real radiation field in the near-field distribution. The adaptive decoupling correction module, on the basis of obtaining the real radiation characteristics, introduces adaptive decoupling mapping, dynamically layers the stripped residual trajectory and the real radiation characteristics, generates a correction matrix with directional weight, and uses the correction matrix to suppress the continuous interference of false energy components in the near-far field transformation process. The time reversal steady-state regulation module, under the action of the correction matrix, starts a time reversal phase gating mechanism, injects a conjugate compensation signal to the energy abnormal source area identified in the foregoing, to realize pulse-level reduction of the local electromagnetic field, and writes the corrected energy distribution result to the unified time baseline in real time, thereby forming a complete closed-loop dynamic steady-state regulation process.

[0007] Preferably, the step of constructing the force field detection matrix under the constraint condition of establishing a unified time baseline comprises: Under the constraint condition of establishing a unified time baseline, the time domain of the spherical near-field test environment is initialized synchronously, the clock constraint is implemented on the motion control sequence of the robot probe, the signal sampling node and the reference antenna excitation source, so that all probes respond consistently under the same time reference system. After completing the time baseline synchronization, the force field detection matrix is constructed based on the constraint of spatial geometric relationship, the spatial position information, attitude angle and relative distance of the robot probe are mapped into a multi-dimensional vector space, the weak electromagnetic response at different angle positions is captured, and the energy change trajectory under the unified time baseline is recorded. The time domain and frequency domain joint filtering and characteristic decoupling are performed on each response vector in the force field detection matrix, the stable main response and nonlinear interference components are separated, the coupling effect of the metal reflector is extracted, and the energy anomaly mode is identified; Based on the energy anomaly mode, the dynamic weight update is performed on the force field detection matrix, the response section with the sub-resonance characteristics is solidified as a dynamic sub-resonance risk criterion, and a reference baseline for subsequent energy field analysis is formed.

[0008] Preferably, in the step of performing time domain and frequency domain joint filtering and characteristic decoupling on each response vector in the force field detection matrix, the energy layering weighting algorithm is used to separate the stable main response and nonlinear interference components, and the coherent superposition method is used to enhance the low signal-to-noise ratio section, so that the extracted coupling effect of the metal reflector maintains phase consistency under multi-frequency point conditions, thereby improving the time sequence continuity and spatial resolution accuracy of the dynamic sub-resonance risk criterion.

[0009] Preferably, the step of introducing the phase traction algorithm based on the dynamic sub-resonance risk criterion comprises: After the dynamic sub-resonance risk criterion is established, the phase space modeling is performed on the energy anomaly section in the force field detection matrix with the unified time baseline as the reference, and the phase evolution curve is established under the phase continuity constraint, so as to realize the accurate mapping of the abnormal time period and spatial position in the phase domain; After the phase space modeling is completed, the micro-scale perturbation energy field is injected in the test space, the micro-amplitude oscillation signal is applied to the reference phase sequence, and the phase and amplitude of the perturbation signal are adjusted in real time according to the energy gradient direction, so as to form a nonlinear response surface reflecting the stability of the electric field; After the micro-scale perturbation energy injection is completed, the time sequence analysis is performed on the electric field intensity changes of each spatial position, the residual trajectory of the local electric field mutation is extracted, and the residual trajectory is screened, fitted and phase gradient backtracked in combination with the dynamic sub-resonance risk criterion; After obtaining the residual trajectory, the phase difference in the residual trajectory is coupled with the energy mutation amplitude to generate a nonlinear amplification factor field with directionality and time evolution properties, so as to realize the accurate positioning of the energy anomaly source.

[0010] Preferably, in the generation process of the nonlinear amplification factor field, the phase difference in the residual trajectory is weighted and fused with the energy mutation amplitude, and the dynamic amplification coefficient distribution is formed through three-dimensional space interpolation and time continuous processing; the dynamic amplification coefficient distribution is cross-compared with the force field detection matrix under the unified time baseline, so as to realize the double mapping of the energy anomaly time sequence characteristics and spatial coordinates, thereby improving the uniqueness and accuracy of the energy anomaly source positioning.

[0011] Preferably, the step of running the counterfactual replay chain under the support of the nonlinear amplification factor field comprises: After the nonlinear amplification factor field is established, the spatial distribution data and time evolution parameters in the nonlinear amplification factor field are read with the unified time baseline as the reference, the electromagnetic field states before and after the energy anomaly occurs are reconstructed, and the reverse evolution sequence with the same time step is formed by interpolation expansion; After the initialization of the counterfactual replay chain is completed, the residual trajectory is taken as the main line of backtracking, the reverse phase integral calculation is performed along the time reversal direction, the energy mutation variable is reversely distributed to the adjacent sampling nodes, and dynamic weight correction is performed under the constraint of the nonlinear amplification factor field to gradually strip the false energy; After the false energy is stripped, the real radiation characteristics obtained by backtracking are verified for time sequence consistency and analyzed for spatial stability, and the structure stability and continuity of the real radiation characteristics are ensured through multidimensional correlation calculation and threshold compensation; After the real radiation characteristics are preserved, the backtracking data is subjected to reverse energy reorganization to align with the unified time baseline, and the space-time closed loop is formed by progressive interpolation to maintain the steady state balance of the dynamic radiation field.

[0012] Preferably, in the process of performing the reverse phase integral calculation along the time reversal direction with the residual trajectory as the main line of backtracking, the energy conservation constraint is implemented on the energy distribution of each time step, and the energy gradient of different spatial positions is adaptively adjusted in combination with the dynamic weight correction parameter of the nonlinear amplification factor field, so as to prevent non-physical oscillation in the backtracking calculation and ensure the continuity and stability of the energy stripping process.

[0013] Preferably, the step of introducing adaptive decoupling mapping on the basis of obtaining the real radiation characteristics comprises: After the real radiation characteristics are obtained and the energy backtracking of the counterfactual replay chain is completed, the real radiation characteristics and the stripped residual trajectory are synchronized and aligned with reference to the unified time baseline, the phase difference, the energy difference and the direction gradient are calculated, the dual data set containing the radiation field characteristics and the interference characteristics is formed, and the energy envelope surface is established as the initial decoupling layer; After the dual data set is formed, adaptive decoupling mapping is carried out based on the energy envelope surface, the residual trajectory is taken as the disturbance layer and the real radiation characteristics are taken as the stable layer, the local phase gradient is used for step-by-step mapping and adaptive adjustment between energy layers, and dynamic layering of radiation energy and interference energy is realized; After obtaining the multi-layer energy distribution, the direction weight of each direction layering result is extracted, the direction correlation coefficient is calculated, and the correction matrix is injected, so as to strengthen the main radiation direction, suppress the interference direction, and dynamically compensate the intermediate interval energy; After the correction matrix is generated, it is applied to the near-far field transformation calculation, the false energy component is directionally weighted and corrected, and the unified time baseline phase consistency is maintained through dynamic backwriting, so as to realize continuous suppression of the false energy and stability of the energy distribution.

[0014] Preferably, in the adaptive decoupling mapping process, the direction weight of the correction matrix is determined by a double threshold screening strategy, wherein the energy component with a direction correlation lower than a first threshold is determined as a false interference direction to be suppressed, the energy component higher than a second threshold is determined as a main radiation direction to be strengthened, and the energy component between the two thresholds is dynamically compensated by smooth interpolation to ensure that the correction matrix maintains continuity and energy conservation of the real radiation characteristics while suppressing interference.

[0015] Preferably, the step of starting the time reversal phase gating mechanism under the action of the correction matrix comprises: After the correction matrix is generated and the near-far field transformation is corrected, the energy anomaly source area identified in the correction matrix is analyzed in the time domain under the constraint of the unified time baseline to determine the spatial coordinates and time nodes of the conjugate compensation signal, and the phase inversion modeling is used to generate the reverse compensation signal with opposite phase to the energy anomaly point; After obtaining the phase inversion result, the pre-synchronization stage of the time reversal phase gating mechanism is started, the conjugate compensation signal is injected into the energy anomaly area according to the reference beat of the unified time baseline, time delay compensation control is used to realize time-space conjugate matching, and the wave front shape and phase distribution of the compensation signal are dynamically adjusted to form a high-coherence destructive effect; After the conjugate compensation signal is injected, the response of the local energy field is monitored in real time, energy residual analysis and phase recovery operations are performed, and secondary conjugate injection is performed according to the weight of the correction matrix to form a local closed-loop iterative control; After the energy reduction and phase recovery are completed, the corrected energy distribution result is written back to the unified time baseline in real time, and an energy steady-state closed loop is formed through multiple write-back and correction cycles to realize dynamic steady-state regulation and long-term stability.

[0016] In the above technical solution, the technical effects and advantages provided by the present application are: By constructing a force field detection matrix under the constraint of a unified time baseline and combining a dynamic subharmonic risk criterion, the present application realizes continuous capture and intelligent identification of weak electromagnetic responses of a metal reflector at multiple angle positions, thereby establishing a self-calibrating energy analysis baseline in time and space dimensions. Through the synergistic effect of phase traction calculation and counterfactual replay chain, the energy anomaly source can be accurately located and false energy components can be automatically stripped, so that the real radiation characteristics still maintain high stability and consistency in complex test environments. Therefore, the anti-interference ability and data fidelity of spherical near-field measurement are significantly improved, local energy amplification-induced pattern distortion, beam deviation and sidelobe anomaly are effectively avoided, and high-precision recovery and reliable measurement of antenna radiation performance under complex reflection conditions are realized.

[0017] The present application realizes the closed-loop regulation and control of dynamic stability under the action of the energy correction matrix by introducing the adaptive decoupling mapping and time reversal phase gating mechanism, so that the influence of the energy anomaly source is compensated and inhibited in real time. The method can continuously correct the false energy component in the near-far field transformation process, realize the pulse-level reduction of the local electromagnetic field and the maintenance of the phase consistency of the overall radiation field. Through this closed-loop compensation mechanism, the system can still maintain stable spatial resolution and direction accuracy under the conditions of high-frequency broadband and multi-probe collaborative testing, thereby significantly improving the repeatability, reliability and engineering applicability of the test results. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0019] Figure 1 A module schematic diagram of a multi-probe spherical near-field test robot system of the present application. DETAILED DESCRIPTION

[0020] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations may, however, be implemented in many different forms and should not be construed as limited to the examples set forth herein; rather, these example implementations are provided so that this disclosure will be thorough and complete, and will fully convey the gist of each example to those skilled in the art.

[0021] The present application provides a multi-probe spherical near-field test robot system as shown in Figure 1 The present application provides a multi-probe spherical near-field test robot system as shown in The time baseline force field detection module, under the constraint condition of establishing a unified time baseline, constructs a force field detection matrix, continuously captures the weak electromagnetic response of the metal reflector in the test cabin at different angle positions, and solidifies the capture result as a dynamic subharmonic resonance risk criterion, which is used as a reference baseline for subsequent energy field analysis; The specific implementation steps are as follows: Firstly, the time-domain synchronous initialization of the entire spherical near-field test environment is performed under the constraint condition of establishing a unified time baseline. By strictly clock-constraining the motion control sequence of the robot probe, the signal sampling nodes, and the reference antenna excitation source, all probes are consistent in response under the same time reference system to ensure that the subsequent energy sampling has a unified time reference. In this process, nanosecond-level synchronization accuracy is achieved through a high-precision time distribution link, and time delay calibration is performed using a reference signal, so that the phase and amplitude information of each probe can be consistent in the full spatial range when capturing the weak electromagnetic response of the metal reflector. The establishment of such a unified time baseline not only provides a time constraint condition for the subsequent construction of the force field detection matrix, but also eliminates systematic errors caused by multi-channel sampling delay, thereby laying a stable time foundation for subsequent sub-resonance risk identification.

[0022] After completing the time baseline synchronization, the force field detection matrix is constructed based on the spatial geometric relationship as the constraint basis. By mapping the spatial position information, attitude angle, and relative distance between the robot probe and the metal reflector into a multi-dimensional vector space, a force field sampling structure covering angle, distance, and phase distribution is formed. In this stage, each sampling point corresponds to an electromagnetic response vector, which contains amplitude, phase, and timestamp information of the probe at that position. By continuously controlling the probe to move along the spherical path, the probe captures the weak scattering signal of the metal reflector at different angle positions and records the energy change trajectory under the unified time baseline. To enhance the capture accuracy, a multi-frequency point scanning method is used for repeated sampling of the target area, so that the weak response characteristics at different frequencies are fully analyzed, thereby achieving high-density capture of sub-resonance precursor signals.

[0023] After obtaining the electromagnetic response data at multiple angles and multiple frequency points, the joint filtering and feature decoupling of each response vector in the aforementioned force field detection matrix are performed in the time domain and frequency domain. The stable main response and nonlinear interference components are separated by energy layering and weighting algorithm, and the low signal-to-noise ratio section is enhanced using coherent superposition. On this basis, the electromagnetic response curve of each sampling point is phase-normalized and energy-differentially calculated to extract the weak coupling effect of the metal reflector under specific angle conditions. By projecting the energy distribution of these weak coupling responses to the continuous domain of the time baseline, an energy change curve about angle, frequency, and time can be formed, and the mutation points of the curve represent the regions where sub-resonance excitation may exist. Further, through multi-dimensional clustering analysis of these mutation points, potential energy anomaly patterns at different spatial positions can be identified, providing data basis for subsequent criterion solidification.

[0024] Based on the identified energy anomaly pattern, the entire force field detection matrix is dynamically updated, and the response section with sub-resonance characteristics is solidified as a dynamic sub-resonance risk criterion in a weighted manner. The criterion takes a unified time baseline as the core, and encapsulates the energy response characteristics, phase shift trend and frequency dependence at different spatial positions into a set of dynamic reference system. Through this solidification method, the risk criterion can be directly referenced in subsequent energy field analysis, and the new test data can be compared and corrected in real time, so as to quickly identify the potential sub-resonance interference caused by the metal reflector. The risk criterion not only has time sequence coherence and spatial resolution, but also can be used as an initial constraint condition in subsequent phase traction calculation, providing accurate time and space definition for the injection of micro-scale disturbance energy field.

[0025] Through this series of operations, a complete closed-loop process from time unification, spatial sampling, energy identification to risk solidification is realized, so that the near-field test can still maintain a high-reliability measurement baseline in the presence of complex reflector environment.

[0026] The phase traction energy analysis module, based on the dynamic sub-resonance risk criterion, introduces phase traction calculation to inject a micro-scale disturbance energy field in the test space, deeply analyzes the foregoing capture results, extracts the residual trajectory of local electric field mutation, and converts the residual trajectory into a nonlinear amplification factor field to realize accurate positioning of the energy abnormal source. The specific implementation steps are as follows: After the establishment of the foregoing dynamic sub-resonance risk criterion, the energy anomaly section in the force field detection matrix is phase-space modeled with reference to the unified time baseline. The phase evolution trajectory of these anomaly sections is extracted as the basis of the initial phase distribution, and the pre-processing stage of the phase traction calculation is introduced on this basis. The core of this stage is to constrain the continuity of the electric field phase distribution in the test space, so that the phase gradient of adjacent sampling points maintains an analyzable smooth relationship in the time and space dimensions. Through this phase continuity constraint, a set of phase evolution curves that can be pulled is established, which provides an accurate phase carrier for the injection of disturbance energy in the subsequent process. In this process, the corresponding abnormal period and spatial position in the dynamic sub-resonance risk criterion are accurately mapped to the phase domain through high-resolution phase difference calculation and time delay compensation, ensuring that each phase traction is targeted at the real energy distortion source.

[0027] After the phase space modeling is completed, a micro-scale perturbation energy field is injected in the test space to reveal the nonlinear response characteristics of the electric field distribution under the sub-harmonic resonance effect. The injection of the perturbation energy field does not directly change the overall electromagnetic energy, but by applying a micro-oscillation signal to the reference phase sequence, it induces subtle fluctuations in the local electric field response. Through this controlled perturbation method, the energy-sensitive area hidden near the metal reflector can be excited without destroying the overall field stability. During the injection process, the phase and amplitude of the perturbation signal are adjusted in real time according to the energy gradient direction in the dynamic sub-harmonic resonance risk criterion, so that it produces a controllable interference effect with the original energy field under the unified time baseline. By monitoring the phase response changes under different perturbation amplitudes, a nonlinear response surface reflecting the stability and sensitivity of the electric field can be constructed. This response surface can reveal the electromagnetic energy accumulation path caused by sub-harmonic resonance, providing a reference boundary for the extraction of residual trajectories in the next step.

[0028] After the micro-scale perturbation energy injection is completed, the phase evolution curve generated by the aforementioned phase traction algorithm is used to perform time series analysis on the electric field intensity changes at each spatial location to extract the residual trajectories of local electric field mutations. This process identifies point sets that exhibit nonlinear jumps in time or space by calculating the difference sequence of the electric field distribution before and after perturbation, and connects these point sets into continuous residual paths. Since each residual trajectory corresponds to a possible energy anomaly source, the abnormal feature parameters solidified in the dynamic sub-harmonic resonance risk criterion need to be combined during the extraction process to screen and fit the residual trajectories. Through multi-scale wavelet decomposition, high-frequency noise components can be stripped, leaving only the substantial mutation trajectories caused by sub-harmonic resonance effects. Further, by performing phase gradient backtracking on these residual trajectories, the propagation direction and diffusion range of the perturbation energy in space can be recovered, enabling preliminary inference of the spatial location of the energy anomaly source. The key in this stage is to maintain phase continuity and energy conservation, so that the residual trajectories not only reflect transient energy changes, but also embody the cumulative effects in the nonlinear amplification process.

[0029] After obtaining the residual trajectory, the residual trajectory is converted into a nonlinear amplification factor field based on a nonlinear dynamic model to represent the spatial amplification characteristics of the energy anomaly source. The conversion process generates an amplification coefficient reflecting the local energy density change rate by coupling the phase difference and energy amplitude in the residual trajectory. By interpolating and continuously processing these amplification coefficients in three-dimensional space, a nonlinear amplification factor field with directionality and time evolution properties is formed. This factor field can quantitatively describe the energy amplification intensity and distribution range in the subharmonic region and enable accurate positioning of the energy anomaly source. To improve positioning accuracy, the nonlinear amplification factor field is cross-compared with the force field detection matrix on a unified time baseline, enabling dual mapping of the energy anomaly's timing characteristics and spatial coordinates, thereby ensuring the uniqueness and stability of the positioning results.

[0030] On this basis, the input conditions of the phase traction algorithm are continuously updated to dynamically correct the nonlinear amplification factor field after each disturbance iteration, gradually converging to the central region of the real energy source. The final nonlinear amplification factor field not only reveals the nature of energy distortion caused by subharmonic resonance but also provides high-precision spatial constraints for subsequent counterfactual replay and energy correction processes, enabling accurate identification and self-correction in the presence of complex reflectors, thereby achieving high-resolution positioning and stable correction of the energy anomaly source.

[0031] The counterfactual energy backtracking module, supported by the nonlinear amplification factor field, runs a counterfactual replay chain to time backtrace the residual trajectory, remove false energy components caused by metal reflector structures, and retain real radiation characteristics, thereby maintaining the stability of the real radiation field in the near-field distribution. The specific implementation steps are as follows: After the nonlinear amplification factor field is established, the initialization process of the counterfactual replay chain is started with reference to the unified time baseline. The spatial distribution data and time evolution parameters in the nonlinear amplification factor field are read to reconstruct the electromagnetic field state at each time before and after the energy anomaly occurs. The key to this initialization process is to map the energy gain coefficient and phase offset information in the nonlinear amplification factor field to the time dimension of the original residual trajectory, enabling the counterfactual replay chain to accurately backtrace on the unified time baseline. In this stage, the time stamps of each residual trajectory node are interpolated and expanded to rearrange the continuous energy response sequence into a reverse evolution sequence with equal time steps and maintain spatial consistency with the force field detection matrix. The processed data can truly reflect the causal process of energy anomaly formation, thereby laying a calculable spatiotemporal foundation for subsequent false energy removal. At this point, the nonlinear amplification factor field is no longer just a static description quantity but becomes a dynamic constraint core in the counterfactual replay chain, guiding the time backtracking process to follow the real physical laws.

[0032] After the initialization of the counterfactual replay chain, the residual trajectory is taken as the main line of backtracking, and the field distribution state before the energy anomaly occurs is gradually recovered along the time reversal direction. By introducing the reverse phase integral calculation at each time step, the energy mutation recorded in the residual trajectory is allocated to the adjacent sampling nodes in reverse, thereby gradually weakening the aggregation effect of abnormal energy. In this process, the nonlinear amplification factor field plays a role in dynamic amplification weight correction, enabling the energy stripping process to automatically adjust the backtracking strength for different energy gradients at different spatial positions. In order to prevent the occurrence of non-physical oscillation phenomena during the energy backtracking process, an energy conservation constraint is applied to each reverse calculation result to ensure that the cumulative energy of the counterfactual replay is equivalent to the original distribution in time sequence. Through this step-by-step inversion and constraint correction, the false energy components caused by the metal reflector structure can be peeled off layer by layer in time without destroying the continuity and integrity of the real radiation characteristics. After multiple iterations of backtracking, the abnormal energy is compressed in time and tends to zero, while the real radiation energy distribution gradually reveals a stable spatial form.

[0033] After the false energy components are gradually stripped, the real radiation characteristics obtained by backtracking are verified for temporal consistency and spatial stability. In this phase, the consistency of the electric field amplitude distribution and phase distribution before and after backtracking is used to judge the degree of maintenance of the real radiation field in time evolution. By calculating the multi-dimensional correlation coefficient and phase deviation rate, it can be quantitatively evaluated whether the energy stripping leads to structural deviation of the real radiation characteristics. When the correlation coefficient of a certain spatial region is detected to be lower than the threshold value, the counterfactual replay chain will automatically call the original weight parameters in the nonlinear amplification factor field to fine-tune the energy distribution of that region to compensate for the numerical drift that may occur during the backtracking process. At the same time, to ensure spatial consistency, the real radiation characteristics are fitted and reconstructed in a three-dimensional coordinate system to maintain smooth transition within the spherical sampling range. Through this feedback verification mechanism, the counterfactual replay process can remove false energy while always maintaining the stability and physical reasonableness of the real radiation characteristics. The verified near-field distribution will serve as the trusted input data for subsequent energy correction and pattern reconstruction.

[0034] After the real radiation characteristics are stably reserved, the time series data after the backtracking is completed is reversed and the near-field distribution is re-aligned with the unified time baseline in the time dimension. This process ensures that the real radiation characteristics after stripping are synchronized with the initial test time axis by mapping the backtracked energy distribution results back to the original test sequence in a time-reversed manner. In order to prevent energy mutations during the write-back process, a gradual interpolation strategy is introduced on each time slice to make the energy change show a continuous convergence trend. By combining the dynamic constraints of the nonlinear amplification factor field, the electromagnetic field after false energy stripping forms a stable closed loop in time and space, thereby constructing a dynamic radiation field distribution with self-balancing ability. At this time, the complete operation process of the counterfactual replay chain realizes the whole process linkage from energy anomaly identification, reverse time series backtracking, false energy stripping to real radiation preservation.

[0035] Through this method, not only the low-probability sub-resonance interference caused by the metal reflector structure is eliminated, but also the near-field distribution can still maintain high stability and repeatability in the presence of complex reflection environment.

[0036] The adaptive decoupling correction module, on the basis of obtaining the real radiation characteristics, introduces adaptive decoupling mapping to dynamically layer the residual trajectory after stripping and the real radiation characteristics, generate a correction matrix with directional weight, and use the correction matrix to suppress the continuous interference of false energy components in the near-far field transformation process; The specific implementation steps are as follows: First, after obtaining the real radiation characteristics and completing the energy backtracking of the counterfactual replay chain, the real radiation characteristics and the residual trajectory after stripping are synchronized and aligned with the unified time baseline as a reference. By calculating the phase difference, energy difference and directional gradient of the two in the time domain and the spatial domain respectively, a set of dual data sets containing the intrinsic characteristics of the radiation field and the residual characteristics of the interference are formed. In this stage, in order to ensure the accuracy of data layering, a layering criterion based on energy continuity needs to be established, that is, while ensuring the phase stability of the real radiation characteristics, the spatial distribution of the residual trajectory is nonlinearly mapped to form a separable energy envelope surface in the region intersected with the real radiation characteristics. This envelope surface serves as the initial decoupling layer to guide the subsequent generation of directional weight. By calculating the gradient change rate of residual energy at different angle positions, the diffusion trend of false energy interference in spatial distribution can be identified, and preliminary directional allocation parameters are provided for decoupling mapping, so that each energy component has a clear spatial attribution relationship in subsequent dynamic layering.

[0037] Secondly, after the construction of the dual data set is completed, the main operation process of adaptive decoupling mapping based on the aforementioned energy envelope surface is carried out. This process takes the dynamic hierarchical idea as the core, and through the residual trajectory after stripping as the disturbance layer and the real radiation feature as the stable layer, step-by-step mapping between energy layers is carried out on the unified time baseline. In this process, the local phase gradient recorded in the residual trajectory is used as the initial condition of the mapping weight, and the energy coupling relationship in different spatial directions is adaptively adjusted. Specifically, in each mapping iteration, by calculating the derivative value of the energy difference in each direction, the phase offset between the false energy and the real energy is fine-tuned, so that they tend to be linearly independent in the mapping space. Through continuous iteration and update, the energy distribution is gradually divided into multiple layers that do not interfere with each other, and each layer represents an energy transmission channel in a specific direction. At this time, the real radiation feature forms a stable principal component in space, and the residual trajectory is compressed into multiple directional subsidiary components, thereby realizing the preliminary decoupling of the radiation energy and the interference energy. This adaptive mapping method not only maintains synchronization with the unified time baseline in time, but also can adjust the weight in real time according to the dynamic changes of the interference distribution in space, and embodies the self-adjusting ability to complex field environment.

[0038] Third, after the multi-layer energy distribution is obtained by adaptive decoupling mapping, the directional weight extraction is carried out on each directional layering result to generate a correction matrix with spatial orientation characteristics. In this stage, by statistically analyzing the amplitude response, phase response and their stability with angle change of each layered energy region, the directional correlation coefficient is calculated and injected into the corresponding elements of the correction matrix as the weight parameter. In order to ensure the preservation ability of the correction matrix to the real radiation feature, a double-threshold screening strategy is introduced in the weight extraction process, that is, when the directional correlation is lower than the first threshold, it is considered as a false interference direction and is suppressed, when it is higher than the second threshold, it is considered as a main radiation direction and is strengthened, and the directions in the middle interval are dynamically compensated by smooth interpolation. The correction matrix generated in this way not only reflects the energy distribution characteristics of each direction in space, but also reflects the decay trend of the interference in the time dimension, thereby having dynamic spatiotemporal weight properties. Each row of the matrix corresponds to a correction factor of a spatial direction, and each column corresponds to an energy adjustment parameter of a time node, so that adaptive update can be carried out according to real-time measurement data in the near-far field transformation process. Through this process, the continuous interference of false energy is quantized as controllable directional weight, and forms a mathematically operable correction basis.

[0039] Finally, after the completion of the correction matrix generation, it is applied to the near-far field transformation calculation to achieve continuous suppression of false energy components. The process first performs matrix multiplication operation on the near-field sampling data of the real radiation characteristics by multiplying the correction matrix with the near-field sampling data, and then performs directional weighting correction on the energy and phase of each sampling point, so that the false energy is actively attenuated before transformation to the far-field domain. Then, when performing spherical wave expansion, the directional weight factor of the correction matrix is introduced into the spherical basis function, so that the basis wave coefficients of the false interference direction are adaptively suppressed, and the basis wave coefficients of the real radiation direction are enhanced, so as to strengthen the main lobe shape of the real radiation characteristics in the transformation result. In order to maintain energy conservation, after each near-far field transformation, the weight distribution of the correction matrix is dynamically written back to keep the phase consistent with the unified time baseline, and the closed-loop energy correction is realized. In this way, the false energy is weakened in the spatial frequency domain and the time domain, and the real radiation characteristics are always stable in the whole transformation process. Finally, the near-far field transformation result regulated by the correction matrix shows the characteristics of smooth gain curve, accurate beam direction and natural attenuation of sidelobe level in the direction diagram, which significantly improves the authenticity and reliability of the antenna near-field test.

[0040] Through the above steps, the adaptive decoupling mapping and the correction matrix together constitute a dynamically learning energy correction mechanism, so that the system can still automatically identify, layer and suppress false energy in a complex reflector environment, realize high-fidelity restoration of near-far field mapping and stable maintenance of real radiation characteristics.

[0041] The time reversal steady-state regulation module, under the action of the correction matrix, starts the time reversal phase gating mechanism, injects a conjugate compensation signal to the energy abnormal source region identified in the foregoing, to realize pulse-level reduction of the local electromagnetic field, and writes back the corrected energy distribution result to the unified time baseline in real time, thereby forming a complete closed-loop dynamic steady-state regulation process; The specific implementation steps are as follows: After the correction matrix is generated and the near-far field transformation correction is completed, the energy anomaly source area identified in the correction matrix is analyzed in time domain mapping with the unified time baseline as the constraint, so as to determine the accurate spatial coordinates and time nodes of the conjugate compensation signal to be applied. This step takes the direction weight of the correction matrix as the input basis, identifies the area where the energy mutation slope is significantly greater than the background radiation smoothness threshold by calculating the time sequence derivative of the energy distribution in each direction, and defines these areas as local energy anomaly points. After determining the anomaly points, the electromagnetic field phase corresponding to the anomaly points is inversed and modeled, so that the phase distribution changes from forward propagation to reverse propagation state, so as to realize phase conjugate superposition when the subsequent compensation signal is injected. At this time, a set of reverse compensation signals with completely opposite phase and controlled amplitude to the energy anomaly points can be generated through the phase inversion calculation synchronized with the unified time baseline, to establish the initial conditions for realizing the local electromagnetic field pulse level reduction. In this process, the correction matrix not only provides the spatial direction constraint, but also ensures the compensation signal to be accurately aligned with the peak position of the abnormal energy in time domain through the time domain coupling parameter, thereby laying the foundation for dynamic synchronization of conjugate injection.

[0042] After obtaining the phase inversion result of the target area, the pre-synchronization stage of the time inversion phase gating mechanism is started, and the conjugate compensation signal is injected into the energy anomaly area according to the reference beat of the unified time baseline, so as to realize the double conjugate matching of time domain and space domain. The key of this stage is to control the time delay compensation, so that the propagation path of the conjugate signal is completely opposite to the propagation direction of the original abnormal energy, so as to realize the reverse superposition at the moment when the peak value of the abnormal energy arrives. In order to avoid the compensation process causing new interference effect, the injection amplitude of the conjugate signal is adaptively adjusted, so that the energy density is inversely proportional to the transient intensity of the abnormal energy, so as to realize the quantitative cancellation of the pulse level. During the injection process, the wavefront shape and phase distribution of the compensation signal are dynamically adjusted through real-time feedback of the phase inversion result and the correction matrix, so as to ensure that it forms a high coherence cancellation effect in the local area. Through the synergistic effect of time inversion and phase gating, the local electromagnetic field intensity of the energy anomaly source area can be quickly attenuated in a very short time, so as to realize accurate spatial energy reduction without affecting the stability of the surrounding real radiation field.

[0043] After the completion of the conjugate compensation signal injection, the response of the local energy field is monitored in real time, and energy residual analysis and phase recovery operations are performed on the unified time baseline. In this stage, the evolution curves of the electric field amplitude and phase of the abnormal energy area are continuously sampled to determine whether the compensation effect meets the set suppression threshold. When the local energy is detected to be below the background noise level, the phase recovery algorithm is executed to remap the phase information of the original radiation field to the reduced energy area, thereby repairing the phase distortion caused by the compensation signal injection. To ensure overall energy conservation, an energy balance constraint based on time integration is introduced during the phase recovery process to compensate for the energy loss in the local reduction area, ensuring the continuity and physical consistency of the entire field distribution in space. At the same time, by comparing with the direction weight recorded in the correction matrix, the secondary interference points with energy residues are subjected to secondary conjugate injection, forming a local closed-loop iterative control, so that the energy abnormal source is completely suppressed in time and space. This step not only ensures the efficiency of conjugate compensation, but also enables the system to have self-healing ability under complex reflection conditions, thereby preventing energy abnormalities from repeatedly occurring in multiple measurements.

[0044] After the completion of local energy reduction and phase recovery, the corrected energy distribution results are written back to the unified time baseline in real time to form a complete closed-loop dynamic steady-state regulation process. This writing process takes the final output of the time reversal phase gating mechanism as the core, and remaps the reduced and corrected electromagnetic field distribution back to the unified space-time reference frame, ensuring the time sequence consistency of the test system in the subsequent sampling and calculation phase. Through this writing mechanism, all corrected energy information forms a continuous historical chain with the original near-field sampling data, enabling the subsequent near-far field transformation to be performed based on the unbiased time baseline. In this process, the system compares the time-domain stability indicators of the energy distribution before and after correction, calculates the steady-state error, and adjusts the time reversal parameters based on the error value to dynamically optimize the compensation mechanism. Through multiple writing and correction cycles, an energy steady-state closed loop centered on the unified time baseline is formed, enabling the entire test process to have self-calibration, self-repair, and long-term stability characteristics.

[0045] Finally, the time reversal phase gating mechanism, under the continuous action of the correction matrix, reduces the false energy in the test space to a pulse level, maintains the stability and repeatability of the real radiation characteristics, and ensures the phase continuity of the near-field distribution and the physical consistency of the far-field pattern, thereby maintaining high-fidelity and high-resolution antenna performance measurement results in the presence of complex metal reflection environments.

[0046] The present application realizes continuous capture and intelligent identification of weak electromagnetic response of a metal reflector at a multi-angle position by constructing a force field detection matrix under unified time baseline constraints and combining a dynamic subharmonic risk criterion, thereby establishing a self-calibrating energy analysis baseline in the time and space dimensions. Through the synergistic effect of phase traction calculation and counterfactual replay chain, the energy anomaly source can be accurately located and false energy components can be automatically stripped, so that the real radiation characteristics remain highly stable and consistent in a complex test environment. Thus, the anti-interference ability and data fidelity of spherical near-field measurement are significantly improved, and distortion of the directional diagram, beam deviation and sidelobe anomaly caused by local energy amplification are effectively avoided, realizing high-precision recovery and reliable measurement of the antenna radiation performance under complex reflection conditions.

[0047] The present application realizes dynamic and stable closed-loop regulation under the action of an energy correction matrix by introducing adaptive decoupling mapping and time reversal phase gating mechanisms, so that the influence of the energy anomaly source is compensated and inhibited in real time. This method can continuously correct false energy components during near-far field transformation, realize pulse-level reduction of the local electromagnetic field and maintain the phase consistency of the overall radiation field. Through this closed-loop compensation mechanism, the system can still maintain stable spatial resolution and directional accuracy under high-frequency broadband and multi-probe collaborative testing conditions, thereby significantly improving the repeatability, reliability and engineering applicability of the test results.

[0048] The above only describes certain exemplary embodiments of the present application by way of illustration, and it is needless to say that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present application. Therefore, the above figures and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present application.

Claims

1. A multi-probe spherical near-field test robot system, characterized by, The time baseline force field detection module, the phase traction energy analysis module, the counterfactual energy backtracking module, the adaptive decoupling correction module and the time reversal steady-state regulation module are included. The time baseline force field detection module, under the constraint condition of establishing a unified time baseline, constructs a force field detection matrix, continuously captures the weak electromagnetic response of the metal reflector in the test cabin at different angle positions, and solidifies the capture results as dynamic subharmonic resonance risk criteria. The phase traction energy analysis module, based on the dynamic subharmonic resonance risk criteria, introduces a phase traction algorithm, injects a micro-scale perturbation energy field into the test space, deeply analyzes the capture results, extracts the residual trajectory of the local electric field mutation, and converts the residual trajectory into a nonlinear amplification factor field. The counterfactual energy backtracking module, under the support of the nonlinear amplification factor field, runs a counterfactual replay chain, time-series backtracks the residual trajectory, removes the false energy components caused by the metal reflector structure, and retains the real radiation characteristics. The adaptive decoupling correction module, based on the obtained real radiation characteristics, introduces adaptive decoupling mapping, dynamically layers the decoupled residual trajectory and the real radiation characteristics, generates a correction matrix with directional weights, and uses the correction matrix to suppress the continuous interference of false energy components in the near-far field transformation process. The time reversal steady-state regulation module, under the action of the correction matrix, starts the time reversal phase gating mechanism, injects a conjugate compensation signal to the identified energy abnormal source area, realizes pulse-level reduction of the local electromagnetic field, and writes the corrected energy distribution results to the unified time baseline in real time.

2. A multi-probe spherical near-field test robot system according to claim 1, characterized in that, The step of constructing the force field detection matrix under the constraint condition of establishing a unified time baseline includes: Under the constraint condition of establishing a unified time baseline, the time-domain synchronization of the spherical near-field test environment is initialized, the clock constraint is implemented on the motion control sequence of the robot probe, the signal sampling node and the reference antenna excitation source, so that all probes respond consistently under the same time reference system; After completing the time baseline synchronization, the force field detection matrix is constructed based on the constraint of spatial geometric relationship, the spatial position information, attitude angle and relative distance of the robot probe are mapped into a multi-dimensional vector space, the weak electromagnetic response at different angle positions is captured, and the energy change trajectory under the unified time baseline is recorded; The response vectors in the force field detection matrix are subjected to time-domain and frequency-domain joint filtering and characteristic decoupling, the stable main response and nonlinear interference components are separated, the coupling effect of the metal reflector is extracted, and the energy abnormal mode is identified; Based on the energy abnormal mode, the dynamic weight of the force field detection matrix is updated, and the response section with subharmonic resonance characteristics is solidified as the dynamic subharmonic resonance risk criteria.

3. A multi-probe spherical near-field test robot system according to claim 2, wherein, In the step of time-domain and frequency-domain joint filtering and characteristic decoupling of the response vectors in the force field detection matrix, the energy layering weighting algorithm is used to separate the stable main response and nonlinear interference components, and the coherent superposition method is used to enhance the low signal-to-noise ratio section, so that the extracted coupling effect of the metal reflector maintains phase consistency under multi-frequency conditions.

4. The multi-probe spherical near-field test robot system of claim 1, wherein, The step of introducing the phase traction algorithm based on the dynamic subharmonic resonance risk criteria includes: After the dynamic subharmonic risk criterion is established, the phase space modeling is performed on the energy abnormal section in the force field detection matrix with the unified time baseline as the reference, and the phase evolution curve is established under the phase continuity constraint; After the phase space modeling is completed, the micro-scale perturbation energy field is injected in the test space, the micro-amplitude oscillation signal is applied to the reference phase sequence, and the phase and amplitude of the perturbation signal are adjusted in real time according to the energy gradient direction to form a nonlinear response surface reflecting the stability of the electric field; After the micro-scale perturbation energy injection is completed, the time series analysis is performed on the electric field intensity change at each spatial position, the residual trajectory of the local electric field mutation is extracted, and the residual trajectory is screened, fitted and phase gradient backtracked in combination with the dynamic subharmonic risk criterion; After the residual trajectory is obtained, the phase difference in the residual trajectory is coupled with the energy mutation amplitude to calculate a nonlinear amplification factor field with directionality and time evolution properties.

5. A multi-probe spherical near-field test robot system according to claim 4, wherein, In the generation process of the nonlinear amplification factor field, the phase difference in the residual trajectory is weighted and fused with the energy mutation amplitude, and the dynamic amplification coefficient distribution is formed through three-dimensional space interpolation and time continuous processing; the dynamic amplification coefficient distribution is cross-compared with the force field detection matrix under the unified time baseline to realize the dual mapping of the energy abnormal timing characteristics and the spatial coordinates.

6. The multi-probe spherical near-field test robot system of claim 1, wherein, The steps of running the counterfactual replay chain under the support of the nonlinear amplification factor field include: After the nonlinear amplification factor field is established, the spatial distribution data and time evolution parameters in the nonlinear amplification factor field are read with the unified time baseline as the reference, the electromagnetic field state before and after the energy anomaly occurs is reconstructed, and the reverse evolution sequence with isochronous steps is formed through interpolation expansion; After the initialization of the counterfactual replay chain is completed, the residual trajectory is taken as the backtracking main line, the reverse phase integral calculation is performed in the time inversion direction, the energy mutation quantity is reversely distributed to the adjacent sampling nodes, and the dynamic weight correction is performed under the constraint of the nonlinear amplification factor field to gradually strip the false energy; After the false energy is stripped, the real radiation characteristics obtained by backtracking are verified for timing consistency and analyzed for spatial stability, and the structure stability and continuity of the real radiation characteristics are ensured through multidimensional correlation calculation and threshold compensation; After the real radiation characteristics are retained, the backtracking data is subjected to reverse energy reorganization to align it with the unified time baseline, and the time-space closed loop is formed through gradual interpolation to maintain the steady-state balance of the dynamic radiation field.

7. A multi-probe spherical near-field test robot system according to claim 6, characterized in that In the process of performing the reverse phase integral calculation along the time inversion direction with the residual trajectory as the backtracking main line, the energy conservation constraint is implemented on the energy distribution of each time step, and the energy gradient of different spatial positions is adaptively adjusted in combination with the dynamic weight correction parameters of the nonlinear amplification factor field.

8. The multi-probe spherical near-field test robot system of claim 1, wherein, The steps of introducing the adaptive decoupling mapping on the basis of the real radiation characteristics include: After the real radiation characteristics are obtained and the counterfactual replay chain energy backtracking is completed, the real radiation characteristics and the stripped residual trajectory are synchronized and aligned in data with the unified time baseline as the reference, the phase difference, the energy difference and the direction gradient are calculated, the dual data set containing the radiation field characteristics and the interference characteristics is formed, and the energy envelope surface is established as the initial decoupling layer; After forming the dual data set, based on the energy envelope surface, adaptive decoupling mapping is carried out, with residual trajectory as the disturbance layer and real radiation characteristics as the stable layer, and local phase gradient is used for step-by-step mapping and adaptive adjustment between energy layers, so as to realize dynamic layering of radiation energy and interference energy; After obtaining the multi-layer energy distribution, the directional weight of each direction is extracted, the directional correlation coefficient is calculated, and the correction matrix is injected, so as to strengthen the main radiation direction, suppress the interference direction, and dynamically compensate the intermediate interval energy; After the correction matrix is generated, it is applied to the near-far field transformation calculation, the false energy component is directionally weighted and corrected, and the unified time baseline phase is kept consistent through dynamic backwriting.

9. A multi-probe spherical near-field test robot system according to claim 8, characterized in that, In the adaptive decoupling mapping process, the directional weight of the correction matrix is determined by a double-threshold screening strategy. Energy components with a directional correlation lower than a first threshold are determined as false interference directions and are suppressed, energy components higher than a second threshold are determined as main radiation directions and are strengthened, and energy components between the two thresholds are dynamically compensated by smooth interpolation.

10. A multi-probe spherical near-field test robot system according to claim 8, wherein, The steps of starting the time reversal phase gating mechanism under the action of the correction matrix include: After the correction matrix is generated and the near-far field transformation is corrected, the energy anomaly source area marked in the correction matrix is analyzed in the time domain, the spatial coordinates and time nodes of the conjugate compensation signal are determined, and the reverse compensation signal with opposite phase to the energy anomaly point is generated through phase inversion modeling; After obtaining the phase inversion result, the pre-synchronization stage of the time reversal phase gating mechanism is started, the conjugate compensation signal is injected into the energy anomaly area according to the reference rhythm of the unified time baseline, time delay compensation control is realized to achieve time-space conjugate matching, and the wave front shape and phase distribution of the compensation signal are dynamically adjusted to form a high-coherence destructive effect; After the conjugate compensation signal is injected, the response of the local energy field is monitored in real time, energy residual analysis and phase recovery operations are performed, and secondary conjugate injection is performed according to the weight of the correction matrix to form a local closed-loop iterative control; After the energy reduction and phase recovery are completed, the corrected energy distribution result is backwritten to the unified time baseline in real time, and energy steady-state closed loop is formed through multiple backwriting and correction cycles.

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