Cable motion perception based planar near-field measurement phase fluctuation compensation method and system

Abstract

The application discloses a kind of plane near-field measurement phase fluctuation compensation method and system based on cable motion perception, it is related to data processing technical field, method includes: the axial mechanical strain set of multiple feature perception segments of measurement cable is synchronously acquired and the original near-field complex measurement data of same time;Phase continuous processing is carried out to original data under the condition of calibration, and dynamic additional phase deviation is separated in combination with static reference phase;Accordingly, the elastic medium coupling mapping model representing the joint action of geometric path change and medium phase velocity perturbation is constructed;The measured axial mechanical strain set is substituted into the model, and the real-time phase deviation prediction value is calculated and obtained;Finally, the measured original data is compensated in phase reverse direction according to this, and the reconstructed near-field complex data is obtained.The application has the advantages of high precision, dynamic compensation and stable and reliable.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a planar near-field measurement phase fluctuation compensation method and system based on cable motion sensing. Background Technology

[0002] In high-frequency antenna planar near-field measurements, the probe continuously moves with the two-dimensional scanning mechanism to acquire near-field complex data across the entire plane. The flexible measurement cable connecting the probe and the RF receiving instrument undergoes mechanical deformations such as bending, torsion, and tension. As the test frequency extends to higher frequencies such as millimeter waves, the system's requirements for phase stability increase, and cable disturbances can lead to wavefront phase distortion. When the flexible cable is subjected to mechanical stress, the phase evolution of electromagnetic waves within it is affected by various physical mechanisms. Deformation not only causes changes in the geometric path length of RF signal propagation, but also alters the local dielectric density of the insulating medium inside the cable when it is subjected to axial compression or tension, leading to a drift in the equivalent relative permittivity and consequently a change in the local electromagnetic wave phase velocity. Existing technologies typically equate the error to the rigid spatial displacement or geometric length change of the probe tip, rarely considering the elastic-dielectric physical coupling deviation caused by the deformation of the dielectric medium inside the transmission line.

[0003] Furthermore, the evolution of mechanical deformation is a low-frequency physical process, while the acquisition of radio frequency signals is a microwave high-frequency process. During dynamic scanning, there is a system timing delay between the low-frequency strain state acquired by the mechanical sensor and the high-frequency electromagnetic phase angle captured by the radio frequency instrument. This spatiotemporal difference causes misalignment of heterogeneous data on the time axis, making it difficult to align the mechanical characteristics input to the compensation model with the output radio frequency phase angle label. Intrusive disconnection calibration methods would interrupt continuous scanning tests. Therefore, how to overcome the timing synchronization problem of cross-domain heterogeneous data and integrate the dual physical mechanisms of geometric elongation and dielectric constant perturbation to establish a continuous, non-intrusive compensation model is a technical problem that needs to be solved in this field. This is to avoid sidelobe level distortion and beam pointing offset in the far-field radiation pattern of the antenna, and to ensure the R&D verification cycle and test confidence of high-precision radar and communication antennas. Summary of the Invention

[0004] In view of the technical problems described in the background art, the present invention provides a planar near-field measurement phase fluctuation compensation method and system based on cable motion sensing.

[0005] A planar near-field measurement phase fluctuation compensation method based on cable motion sensing includes: simultaneously acquiring the axial mechanical strain set of the measurement cable in multiple feature sensing segments during planar near-field scanning, as well as the original near-field complex measurement data at the same sampling time; performing phase continuity processing on the original near-field complex measurement data acquired under calibration conditions, and separating the dynamic additional phase deviation by combining the spatial static reference phase; constructing an elastic-medium coupling mapping model based on the axial mechanical strain set and the dynamic additional phase deviation under calibration conditions, the elastic-medium coupling mapping model characterizing the combined effect of the geometric path change caused by axial mechanical strain and the medium phase velocity perturbation on the phase; substituting the axial mechanical strain set acquired under actual measurement conditions into the elastic-medium coupling mapping model to calculate and obtain the real-time phase deviation prediction value; and performing phase inverse compensation on the original near-field complex measurement data acquired under actual measurement conditions based on the real-time phase deviation prediction value to obtain the reconstructed near-field complex data.

[0006] Optionally, each of the plurality of feature sensing segments includes at least one deformation extreme point of the measuring cable during dynamic movement, wherein the deformation extreme point is either the curvature change rate extreme point or the tension gradient extreme point.

[0007] Optionally, the synchronous acquisition process includes: generating a global hardware trigger signal based on a preset spatial sampling position; and synchronously latching the axial mechanical strain set and the original near-field complex measurement data within the allowable synchronization delay time difference according to the global hardware trigger signal.

[0008] Optionally, the upper limit of the synchronization delay time difference is calculated and determined based on the preset limit phase error tolerance, the radio frequency carrier frequency, the total length of the measuring cable under stress, and the maximum axial strain rate of the measuring cable under extreme conditions.

[0009] Optionally, the raw near-field complex measurement data obtained under calibration conditions are subjected to phase continuity processing, and the dynamic additional phase deviation is separated by combining the spatial static reference phase. This includes: calculating the first-order phase difference between adjacent sampling points in space; when the absolute value of the first-order phase difference exceeds the half-cycle judgment threshold, performing integer-cycle numerical offset compensation on the phase sequence to obtain continuous absolute phase data; and subtracting the continuous absolute phase data from the spatial static reference phase of the corresponding spatial coordinates to obtain the dynamic additional phase deviation.

[0010] Optionally, constructing a spring-medium coupling mapping model includes: multiplying each strain value in the axial mechanical strain set with the initial physical length of the corresponding feature sensing segment, and summing the product results to calculate the total geometric path change; calculating the equivalent displacement correction amount characterizing the phase velocity perturbation cancellation effect of the medium based on the product relationship between the equivalent spring-medium coupling constant and the total geometric path change; linearly superimposing the total geometric path change amount and the equivalent displacement correction amount to obtain the equivalent electrical length change amount; and multiplying the equivalent electrical length change amount with the spatial propagation constant of electromagnetic waves in the insulating medium to construct a spring-medium coupling mapping model whose output result is the real-time phase deviation prediction value.

[0011] Optionally, the equivalent elastic-medium coupling constant is used to characterize the relative cancellation effect of dielectric constant drift on phase velocity under unit axial mechanical strain, and the equivalent elastic-medium coupling constant is obtained by least squares fitting of the axial mechanical strain set obtained under calibration conditions and the dynamic additional phase deviation.

[0012] Optionally, it also includes a frequency domain extension step for multi-frequency point measurements: calculating the equivalent medium optical path change independent of frequency using a spring-medium coupling mapping model; converting the equivalent medium optical path change into an independent phase compensation matrix for each frequency point according to the spatial wavenumber factor of each frequency point; and performing phase inverse compensation on the original near-field complex measurement data at the corresponding frequency point according to the phase compensation matrix.

[0013] A planar near-field measurement phase fluctuation compensation system based on cable motion sensing is also provided. The system includes: a data synchronization acquisition module, used to synchronously acquire the axial mechanical strain set of the measurement cable in multiple feature sensing segments during planar near-field scanning, as well as the original near-field complex measurement data at the same sampling time; a dynamic deviation separation module, used to perform phase continuity processing on the original near-field complex measurement data acquired under calibration conditions, and separate the dynamic additional phase deviation by combining the spatial static reference phase; a mapping model construction module, used to construct an elastic-medium coupling mapping model based on the axial mechanical strain set and the dynamic additional phase deviation under calibration conditions, the elastic-medium coupling mapping model characterizing the combined effect of the geometric path change caused by axial mechanical strain and the medium phase velocity perturbation on the phase; a phase deviation prediction module, used to substitute the axial mechanical strain set acquired under actual measurement conditions into the elastic-medium coupling mapping model to calculate and obtain the real-time phase deviation prediction value; and a data inverse compensation module, used to perform phase inverse compensation on the original near-field complex measurement data acquired under actual measurement conditions based on the real-time phase deviation prediction value, and obtain the reconstructed near-field complex data.

[0014] Optionally, the data synchronization acquisition module is also used to: generate a global hardware trigger signal based on a preset spatial sampling position; and, based on the global hardware trigger signal, synchronously latch the axial mechanical strain set and the original near-field complex measurement data within the allowable synchronization delay time difference.

[0015] The beneficial effects of this invention are reflected in: In the overall planar near-field measurement phase fluctuation compensation method based on cable motion sensing, firstly, the global continuum topology of the cable is obtained through a deformation extremum point layout strategy based on catenary dynamics. A global hardware trigger signal is generated using a field-programmable gate array (FPGA). Within a time difference window controlled by the dynamic strain rate, cross-domain latching of mechanical strain and RF data is achieved, reducing the spatiotemporal misalignment of heterogeneous data caused by bus delay during dynamic scanning and improving the spatiotemporal consistency of calibration data. Furthermore, phase continuity unwinding preprocessing is implemented by calculating the first-order phase difference between adjacent sampling points, solving the phase angle period folding problem caused by half-wavelength crossing in high-frequency microwave measurements. Combined with static reference differential methods, the dynamic additional phase deviation caused by mechanical deformation is extracted. Finally, a dual-physical-field coupling mapping model is established. The method quantifies the increase in electrical length caused by the physical stretching of the cable and incorporates the phase velocity perturbation cancellation effect caused by the density change due to dielectric compression into the equation calculation system, thus achieving decoupling of multi-physics error factors. Furthermore, it utilizes synchronous data to achieve non-intrusive online analytical prediction, maintaining the integrity of continuous scanning without disconnecting the physical RF link, and derives a multi-frequency parallel compensation matrix based on the frequency independence of the equivalent optical path, reducing the testing and calibration time of broadband phased array antennas. In addition, it constructs a complex exponential operator in complex vector space to perform equal-amplitude inverse rotation compensation, canceling the phase distortion accumulated by cable motion while maintaining the signal amplitude intensity, repairing spatial electromagnetic wavefront distortion, and the reconstructed near-field complex dataset reduces the far-field sidelobe level error floor after near-far-field transformation, ensuring the testing accuracy of high-frequency antennas. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0017] Figure 1 This is a schematic diagram illustrating the steps of the planar near-field measurement phase fluctuation compensation method based on cable motion sensing of the present invention. Figure 2 This is a schematic diagram of a portion of step S1 in the planar near-field measurement phase fluctuation compensation method based on cable motion sensing of the present invention. Figure 3 This is a schematic diagram of part of step S2 in the planar near-field measurement phase fluctuation compensation method based on cable motion sensing of the present invention; Figure 4 This is a schematic diagram of part of step S4 in the planar near-field measurement phase fluctuation compensation method based on cable motion sensing of the present invention; Figure 5 This is a schematic diagram of part of step S5 in the planar near-field measurement phase fluctuation compensation method based on cable motion sensing of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0019] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0020] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0021] This invention provides a planar near-field measurement phase fluctuation compensation method based on cable motion sensing, such as... Figure 1 As shown, in one specific embodiment, the method includes: S1. Simultaneously acquire the axial mechanical strain set of the measurement cable in multiple feature sensing segments during planar near-field scanning, as well as the original near-field complex measurement data at the same sampling time.

[0022] S2. Perform phase continuity processing on the raw near-field complex measurement data obtained under calibration conditions, and separate the dynamic additional phase deviation by combining it with the spatial static reference phase.

[0023] S3. Based on the axial mechanical strain set under calibration conditions and the dynamically added phase deviation, a spring-medium coupling mapping model is constructed. This model characterizes the combined effect of the geometric path change caused by axial mechanical strain and the phase perturbation of the medium on the phase.

[0024] S4. Substitute the set of axial mechanical strains obtained under the actual measurement conditions into the elastic-medium coupling mapping model to calculate and obtain the real-time phase deviation prediction value.

[0025] S5. Perform phase inverse compensation on the original near-field complex measurement data obtained under the actual measurement state based on the real-time phase deviation prediction value to obtain the reconstructed near-field complex data.

[0026] In this embodiment, it should be noted that in S1, when performing the data synchronization acquisition step, it is necessary to solve the spatiotemporal misalignment problem between low-frequency mechanical strain acquisition and high-frequency microwave measurement.

[0027] Taking a 5.0-meter-long flexible PTFE measuring cable as an example, engineers divided it into three characteristic sensing segments based on the catenary dynamics model: a 1.5-meter segment near the probe, a 2.0-meter segment in the middle, and a 1.5-meter segment near the instrument. Strain sensing nodes were then deployed at deformation extreme points to reconstruct the global geometric topology. To eliminate inherent delay jitter caused by the bus, the synchronization control unit generated a global hardware trigger signal to perform cross-domain data latching. During this process, the synchronization delay tolerance of the hardware clock was strictly controlled. When the test frequency was 30 GHz, the set limit phase error tolerance was 0.05 radians, and the cable's ultimate axial strain rate was 0.1 Hz, combined with the initial relative permittivity of the insulating medium (2.1) and the equivalent elastic-dielectric coupling constant (0.3), the maximum synchronization delay time difference was calculated to be strictly limited to within 156.9 microseconds. This step eliminated the risk of misalignment caused by timing differences in heterogeneous data during dynamic scanning, ensuring the causal consistency between the mechanical features required by the subsequent model and the RF phase angle tag in the underlying physical spacetime.

[0028] In S2, after acquiring the dataset of synchronous hard correlation, the deviation separation stage aims to solve the common problems of phase angle period folding failure and dynamic error purification in high-frequency microwave measurement.

[0029] When performing high-dynamic scanning in the 30 GHz millimeter-wave band, the tiny physical displacement of the probe often exceeds half the operating wavelength, causing multiple folds and jumps in the original complex phase angle output by the RF receiver. By calculating the numerical change in phase between adjacent spatial sampling points, when this change exceeds the half-cycle judgment threshold, a full-cycle numerical bias operation is performed on the truncated phase sequence, thereby smoothly restoring the folded phase to continuous absolute phase data that reflects the accumulation of the true physical electrical length. Subsequently, the pre-measured spatial static reference phase under static electromagnetic conditions is extracted and subtracted from the aforementioned continuous absolute phase data at the corresponding spatial coordinates. This differential logic removes the spatial propagation constant term unrelated to the cable's mechanical motion, extracting the dynamic additional phase deviation purely caused by the cable's dynamic deformation, providing accurate electromagnetic observation tag data for constructing a high-fidelity error mapping equation.

[0030] In S3, based on the purified dynamic additional phase deviation, the mapping model construction process overcomes the limitation of existing single geometric ranging compensation approaches that cannot reflect the microscopic physical changes inside the medium. In this process, a dual physical field coupling mapping model is established, which not only quantifies the increase in electrical length caused by the physical stretching of the cable, but also incorporates the medium phase velocity perturbation caused by the density change due to the compression of the medium into the equation calculation system.

[0031] Specifically, the model multiplies the axial mechanical strain value of each feature-sensing segment by the initial physical length of that segment to obtain the geometric path change. Simultaneously, it uses an equivalent elastic-dielectric coupling constant of 0.3 to characterize the relative cancellation effect of dielectric constant drift under unit strain on electromagnetic wave phase velocity. The calibration data samples are fitted using the least squares method to quantify this macroscopic dielectric property perturbation caused by microscopic material deformation. This calculation logic linearly superimposes the geometric deformation component and the phase velocity perturbation component, achieving decoupling of multi-physics error factors. This step corrects the theoretical calculation deviation caused by neglecting the change in the dielectric properties of the flexible transmission line and establishes the underlying mathematical mapping relationship from mechanical strain parameters to radio frequency phase deviation.

[0032] In S4, after establishing the mapping relationship, the real-time prediction process solves the problems of intrusive calibration methods interrupting the scanning test process and excessive time consumption for repeated calibration at multiple frequency points.

[0033] At a specific sampling moment during the formal testing phase, real-time axial mechanical strain sets of three segments were acquired, with values ​​of 0.001, 0.002, and 0.0005 respectively. By inputting these real-time strain data into a calibrated elastic-medium coupling mapping model, the total geometric path change was first calculated to be 0.00625 meters. Subsequently, combining the equivalent elastic-medium coupling constant of 0.3, a product factor of 0.7 was calculated to characterize the physical cancellation effect. Multiplying the total geometric path change by this factor yielded an equivalent electrical length change of 0.004375 meters, from which the predicted real-time phase deviation of 3.983 radians at the sampling point was obtained. For multi-frequency broadband testing, the equivalent medium optical path change, independent of frequency, was calculated using the mapping model. Then, based on the spatial wavenumber factor of each frequency point, it was converted into an independent phase compensation matrix for each frequency point. This step achieves non-invasive online analytical prediction, improving the testing efficiency of broadband phased array antennas while maintaining scan integrity.

[0034] In S5, after obtaining the real-time phase deviation prediction value, the implementation of the reverse compensation stage solves the technical problem that the spatial electromagnetic wavefront distortion caused by high dynamic scanning cannot be effectively recovered at the back end.

[0035] At the sampling instant, assuming the phase angle of the original near-field complex measurement data of the antenna under test synchronously captured by the RF receiving instrument is 1.200 radians, and due to the 3.983 radians of additional phase fluctuation noise introduced by cable deformation, a complex exponential phase correction operator with a phase angle of -3.983 radians is constructed based on this predicted value. Subsequently, in the complex vector space, the original near-field complex data is multiplied by this phase correction operator. This is equivalent to performing a reverse rotation operation on the phase angle while keeping the true physical strength of the signal amplitude unchanged, thereby restoring the compensated true spatial physical phase angle to -2.783 radians. After performing this complex plane rotation compensation logic on all sampling points in the full plane, the phase distortion accumulated by cable motion is canceled point by point, reconstructing a high-fidelity near-field complex dataset. This step reduces the far-field sidelobe level error floor in subsequent near-field and far-field transformation calculations, ensuring the validity of the high-frequency antenna test data.

[0036] In summary, the planar near-field measurement phase fluctuation compensation method based on cable motion sensing firstly obtains the global continuum topology of the cable through a deformation extremum point layout strategy based on catenary dynamics. A global hardware trigger signal is generated using a field-programmable gate array (FPGA), achieving cross-domain latching of mechanical strain and RF data within a time difference window controlled by the dynamic strain rate. This reduces the spatiotemporal misalignment of heterogeneous data caused by bus delay during dynamic scanning and improves the spatiotemporal consistency of calibration data. Furthermore, phase continuity unwinding preprocessing is achieved by calculating the first-order phase difference between adjacent sampling points, solving the phase angle period folding problem caused by half-wavelength crossing in high-frequency microwave measurements. The dynamic additional phase deviation caused by mechanical deformation is extracted using a static reference differential method. Finally, a dual physical field coupling mapping model based on a spring-dipole structure is established. The method quantifies the increase in electrical length caused by the physical stretching of the cable and incorporates the phase velocity perturbation cancellation effect caused by the density change due to dielectric compression into the equation calculation system, thus achieving decoupling of multi-physics error factors. Furthermore, it utilizes synchronous data to achieve non-intrusive online analytical prediction, maintaining the integrity of continuous scanning without disconnecting the physical RF link, and derives a multi-frequency parallel compensation matrix based on the frequency independence of the equivalent optical path, reducing the testing and calibration time of broadband phased array antennas. In addition, it performs equal-amplitude inverse rotation compensation by constructing a complex exponential operator in the complex vector space, canceling the phase distortion accumulated by cable motion while maintaining the signal amplitude intensity, repairing spatial electromagnetic wavefront distortion, and the reconstructed near-field complex dataset reduces the far-field sidelobe level error floor after near-field and far-field transformation, ensuring the testing accuracy of high-frequency antennas.

[0037] like Figure 2 As shown, in one specific embodiment, S1 includes: S11. The flexible measuring cable is divided into M feature sensing segments. A feature sensing segment refers to the smallest computational unit with independent kinematic monitoring significance after the continuous flexible cable has been physically discretized. Each of the multiple feature sensing segments contains at least one deformation extreme point of the measuring cable during dynamic motion, wherein the deformation extreme point is either a curvature change rate extreme point or a tension gradient extreme point.

[0038] Among them, the number of feature-aware segments The value is determined by discretizing and sampling the curvature envelope of the cable along the preset scanning path. Specifically, finite element analysis is used to simulate the stress distribution cloud map of the cable in the motion space, identifying peaks and troughs with significant strain gradient changes as feature anchor points to ensure the number of segments. It can cover more than 95% of the geometric topology reconstruction accuracy with the lowest sampling dimension; for example, for a specific scan trajectory, by comparing the root mean square error of the reconstruction curves under different number of segments with that of the standard flexible cable dynamics model, when When the number of segments is increased to 3, the error curve tends to be stable and meets the real-time requirements of the calculation, thus determining the optimal number of segments.

[0039] S12. When the scanning mechanism reaches the preset spatial sampling position, the synchronization control unit generates a global hardware trigger signal. This signal synchronously latches the axial mechanical strain set of each segment and the original near-field complex measurement data. The axial mechanical strain set refers to the sum of the microscopic displacement deformation values ​​generated by each segment along the cable axis at a specific sampling instant.

[0040] S13. Hardware-level trigger synchronization delay boundary conditions must be met. Maximum allowable synchronization delay time difference. The calculation logic is as follows:

[0041] In the formula: The maximum allowable synchronization delay time difference ( ); For the limit phase error tolerance ( ); For the speed of light in free space ( ); For radio frequency carrier frequency ( ); To measure the total length of the cable under stress ( ); The initial relative permittivity of the insulating medium; It is the equivalent elastic-medium coupling constant; To measure the maximum axial strain rate of the cable under extreme operating conditions ( ).

[0042] Among them, the limiting phase error tolerance The value is derived from the design specifications of antenna beam pointing accuracy and sidelobe level stability, and is obtained through the allocation of a comprehensive error budget for the measurement system. Specifically, through a limited number of simulation experiments on antennas in the same frequency band, the correlation between phase ripple amplitude and far-field loss is analyzed, and the error tolerance is set at approximately 50% of the critical value for performance degradation; for example, if system simulation shows that a phase error of 0.1 rad will cause a 1 dB increase in sidelobe level, exceeding the design limit, then... The value is set to 0.05 rad to retain sufficient safety margin.

[0043] Furthermore, the maximum axial strain rate This is based on statistical measurements of the kinematic characteristics of the scanning mechanism, reflecting the dynamic intensity of the cable as it moves with the probe. In pre-experiments, the probe is controlled to execute multiple typical scanning trajectories at its highest design speed. External monitoring equipment records the instantaneous elongation of key cable segments, and the strain time series is subjected to first-order difference calculations. The maximum difference value is extracted as the benchmark. For example, if the maximum cable length increment measured within a 10ms sampling period is 1mm, the corresponding instantaneous strain is 0.001. The value is 0.1s. - ¹, used to define the physical upper limit of the hardware synchronization clock.

[0044] In this embodiment, it should be noted that, in S11, taking a 5.0-meter-long flexible PTFE radio frequency measurement cable as an example, engineers divided it into three feature sensing segments: a 1.5-meter section with violent swinging near the probe, a 2.0-meter section suspended under gravity in the middle, and a 1.5-meter-long torsional section at the root near the testing instrument. Each feature sensing segment refers to the smallest computational unit with independent kinematic monitoring significance after the continuous flexible cable has been physically discretized. Because the force distribution of the cable during movement is extremely uneven, based on the catenary dynamics model, strain sensing nodes are deployed within these three segments to measure the extreme points of the cable's rate of curvature change and tension gradient. This layout logic avoids data redundancy and sensing blind spots caused by uniform point distribution. It can reconstruct the overall geometric topology evolution of the cable with a small number of measurement points, thereby providing physically representative basic mechanical feature inputs for subsequent model calculations, improving the efficiency of front-end mechanical sensing state acquisition and the accuracy of topology reconstruction.

[0045] In S12, after acquiring the spatial layout, cross-domain data hard synchronization is performed. In conventional test architectures, due to the inherent delay in the communication bus transmission mechanism, the time for the instrument to acquire the RF phase angle often lags behind the time for the sensor to acquire the mechanical strain. To eliminate this error, the field-programmable gate array of the synchronization control unit generates a global hardware trigger signal when the scanning mechanism reaches the preset spatial sampling position. This signal synchronously latches the axial mechanical strain set of each segment and the original near-field complex measurement data through an equal-length physical trigger line. The axial mechanical strain set refers to the sum of the microscopic displacement deformation values ​​generated by each segment along the cable axis at a specific sampling instant. Through low-level hardware interrupt intervention, the two heterogeneous data streams of mechanical and electromagnetic data are forcibly aligned at the physical time level, ensuring the causal consistency of mechanical form and RF phase at the same timestamp, and eliminating the risk of mismatch between the input and output labels of the compensation model due to timing differences during dynamic scanning.

[0046] In S13, the two core calculation expressions involved in this specification are addressed. and Its computational logic deeply couples electromagnetic wave transmission line theory with the dynamic properties of flexible materials, aiming to establish the physical boundaries of compensation in the time and spatial domains through first-principles calculations. Specifically, the expression for the synchronous delay boundary condition... The design logic of its operation process is based on the quantitative constraint of the dynamic coherence window. In planar near-field scanning, since mechanical strain is a low-frequency physical quantity that evolves continuously with time, while radio frequency phase is a high-frequency physical quantity, even a slight loss of synchronization between the two in hardware acquisition will lead to the failure of phase deviation prediction.

[0047] Furthermore, the numerator of this formula This represents the maximum allowable electromagnetic travel error margin in the medium space. By multiplying the limiting phase error tolerance by the speed of light constant, a tolerable phase drift boundary is established.

[0048] Furthermore, the denominator constructs a field representing the rate of change of electric length per unit time caused by mechanical motion. Among these, Converting linear frequency to angular frequency reflects the sensitivity of phase to changes in travel. This describes the instantaneous rate of change of the total physical length of the cable under extreme operating conditions. Specifically, it introduces... The factor is used to physically correct the rate of geometric deformation, because the elastic-medium effect causes the phase velocity to change in the same direction, thereby offsetting part of the effect of the change in geometric path.

[0049] Furthermore, by performing a division operation between the numerator and denominator, the formula for maintaining the phase error within a given range is calculated. Within this range, the hardware triggering mechanism must meet the upper limit of time coherence.

[0050] Based on specific application scenario data, when frequency Phase error tolerance speed of light Total cable length Dielectric constant Coupling constant And the maximum axial strain rate At that time, the molecule is The denominator is calculated to be approximately Dividing the two yields Approximately This operational logic solves the timing misalignment problem in heterogeneous data acquisition, establishes mandatory technical indicators for hardware-level triggering synchronization, and realizes the causal correspondence between mechanical sensing data and radio frequency phase data on the physical time axis, providing a data foundation with timing fidelity for high-precision fitting of subsequent models.

[0051] like Figure 3As shown, in one specific embodiment, S2 includes: S21. Calculating the first-order phase difference between spatially adjacent sampling points. The first-order phase difference refers to the numerical change in phase between two adjacent points in the sampling sequence. When the absolute value of the difference exceeds a preset half-cycle judgment threshold, the phase sequence is compensated for an integer-cycle numerical bias to obtain continuous absolute phase data.

[0052] The half-cycle determination threshold is determined by the boundary between the spatial sampling step size and the signal-to-noise ratio of the system's phase measurement noise, aiming to accurately identify the point where phase winding occurs. This threshold is typically set at... Near the radius of curvature, the specific value is obtained by performing variance analysis on multiple sets of no-load measurement data under static conditions, combined with the assumption of continuity of phase change in the Nyquist sampling theorem, and taking 90% of the mean of the phase jump; for example, if the standard deviation of the normal phase fluctuation caused by slight cable jitter between adjacent sampling points is 0.2 rad, while the theoretical jump caused by phase winding is 6.28 rad, then the threshold is set to... (Approximately 3.14 rad) ensures that the algorithm can eliminate random noise and effectively capture the real phase folding phenomenon.

[0053] S22. Subtract the continuous absolute phase data from the corresponding spatial static reference phase. The spatial static reference phase refers to the ideal field phase distribution measured in advance under static electromagnetic conditions. The dynamic additional phase deviation separated by the subtraction is the equivalent electrical length fluctuation caused by the mechanical motion of the cable.

[0054] In this embodiment, it should be noted that after obtaining the hard-synchronized dataset in S21, phase continuity processing is performed. At the 30 GHz test frequency band, even minute displacements of the probe during the scanning process can easily cause the original phase output by the RF receiver to fluctuate between positive and negative values. Truncation and transitions occur between them. The first-order phase difference between adjacent sampling points is calculated according to the spatial sequence. The first-order phase difference refers to the numerical change in phase between two adjacent points in the sampling sequence. When the absolute value of this difference exceeds a preset half-cycle judgment threshold, the algorithm determines that phase wrapping has occurred, and then positive and negative values ​​are applied to the current and subsequent phase sequences. The calculation logic smoothly transforms the folded phase angle into continuous absolute phase data that reflects the continuous accumulation of physical electrical length, eliminating the interference of phase ambiguity on error extraction and providing mathematically continuous benchmark data support for subsequent stripping of the spatial propagation constant.

[0055] In step S22, after phase continuity is achieved, the dynamic additional phase deviation extraction begins. In actual measurements, continuous absolute phase data includes the path phase of electromagnetic waves propagating in free space and the error phase caused by cable deformation. A pre-measured spatial static reference phase under static electromagnetic conditions is extracted and subtracted from the aforementioned continuous absolute phase data at corresponding spatial coordinate points. Since the spatial coordinates of the two sets of data are consistent, the propagation constant term in free space is canceled out during the subtraction process, and the remaining value is the dynamic additional phase deviation. This processing logic eliminates the interference of the test environment and antenna radiation characteristics on error extraction, purifies the electromagnetic observation label characterizing the dynamic stress state of the cable, and enables the subsequent coupled mapping model to fit a single physical causal relationship between mechanical deformation and phase distortion, thus improving the mapping accuracy of the model calibration.

[0056] In one specific implementation, S3 includes: establishing a spring-and-channel coupling mapping model, wherein the first... Real-time phase deviation prediction value of each sampling point The calculation logic is as follows:

[0057] in, Real-time phase deviation prediction value ( ); For the first Initial physical length of each segment ( ); For the first Each segment in The axial mechanical strain value at time; This is the equivalent elastic-medium coupling constant; all other variables are defined above.

[0058] It should be noted that in the formula The term corresponds to the geometric path change, and includes the equivalent elastic-medium coupling constant. The product term characterizes the dielectric phase velocity perturbation. Dielectric phase velocity perturbation refers to the minute deviation in electromagnetic wave propagation speed caused by changes in the internal dielectric density due to cable stress. The equivalent elastic-dielectric coupling constant is used to characterize the phase cancellation effect of dielectric constant drift under unit axial mechanical strain.

[0059] In this embodiment, it should be noted that in S3, after extracting the dynamic deviation, a projectile-medium physical model is constructed to overcome the limitation that a purely geometric ranging model cannot cover the microscopic physical changes within the medium. Specifically, regarding the expression of the projectile-medium dual-physical-field coupling mapping model in S3... Its operational logic is based on a deep analysis of the physical properties of the flexible transmission line continuum.

[0060] Furthermore, the pre-electron coefficient Essentially, it is the spatial propagation constant of electromagnetic waves in an insulating medium, which maps spatial displacement to phase rotation angle.

[0061] Furthermore, the summation sign In the internal operations, by... By accumulating the local deformations of each feature-sensing segment, a manifold reconstruction of the non-uniform deformation along the entire cable path is achieved. In each segment... Inside, operation terms Accurately describes the segmentation in The amount of geometric path change caused by stretching or bending at any given moment.

[0062] However, simply considering geometric elongation leads to insufficient compensation because when the cable experiences axial mechanical strain, the internal dielectric density changes, causing a shift in the relative permittivity and altering the wave phase velocity along that path. To address this complex dielectric perturbation problem, the model introduces coupling terms. In this logic, This represents the positive contribution of physical path growth to the phase, while This quantitatively characterizes the reverse cancellation effect of the phase velocity slowdown caused by the change in the refractive index of the medium on the phase. Through this product-like logical setup, this model transforms the microscopic medium perturbation, which is originally difficult to observe directly, into a correction factor linearly related to macroscopic strain, achieving a high-precision physical mapping from the mechanical deformation field to the electromagnetic phase field.

[0063] In the above application scenarios, let's assume The initial physical lengths of the three feature sensing segments at time t are respectively , , The corresponding axial mechanical strain values ​​are respectively , , The model first calculates the total geometric path change as follows: Then multiply it by the correction factor. The equivalent change in electrical length is obtained as follows: Ultimately, the spatial propagation constant is approximately... Calculation This calculation process solves the problem of phase calculation residuals caused by neglecting the polarization effect of the medium in existing ranging models, and realizes full-parameter, non-invasive analysis of the dynamic phase of the measuring cable, providing theoretical support that conforms to the intrinsic laws of material mechanics for eliminating phase distortion in near-field scanning.

[0064] It should also be noted that the perturbation effect of the medium density on the phase velocity is quantified through parameter coupling fitting. In the formula... The term corresponds to the geometric path change, and includes the equivalent elastic-medium coupling constant. The product term characterizes the dielectric phase velocity perturbation. The dielectric phase velocity perturbation refers to the minute deviation in electromagnetic wave propagation speed caused by the change in internal dielectric density due to cable stress. Using the strain set and dynamic additional phase deviation data obtained under calibration conditions, the formula is solved using the least squares algorithm, and the equivalent elastic-medium coupling constant is obtained through fitting. The specific value is 0.3. The equivalent elastic-dielectric coupling constant is used to characterize the phase cancellation effect of dielectric constant drift under unit axial mechanical strain. This calculation logic transforms the microscopic dynamic drift of the high-frequency dielectric constant, which is difficult to measure directly, into a macroscopically calculable dimensionless constant, avoiding the introduction of invasive dielectric probes in the test and closing the loop in the parameter solution process of the dual-physics coupling model.

[0065] like Figure 4 As shown, in one specific embodiment, S1 includes: S41. Substituting the real-time acquired axial mechanical strain set into the calibrated elastic-medium coupling mapping model, and resolving the real-time phase deviation prediction value of the current sampling position in real time.

[0066] S42. For multi-frequency broadband measurements, the equivalent medium optical path change independent of frequency is calculated using a mapping model, and then converted into an independent phase compensation matrix for each frequency point based on the spatial wavenumber factor of each frequency point.

[0067] In this embodiment, it should be noted that in S41, after the model calibration is completed, mapping substitution analysis is performed. At a specific sampling time... The real-time axial mechanical strain values ​​of the three segments were obtained. The values ​​are 0.001, 0.002, and 0.0005, respectively. Substituting this data into the mapping model, the sum of the products of the strain of each segment and the initial physical length is first calculated to obtain the total geometric path change of 0.00625 meters. Subsequently, combined with the equivalent elastic-medium coupling constant of 0.3, the product factor characterizing the cancellation effect of 0.7 is calculated, and the product of the two yields the equivalent electrical length change of 0.004375 meters. Combining the frequency and dielectric constant, the real-time phase deviation prediction value at this sampling position is finally calculated. The value is 3.983 radians. This step achieves non-invasive online microsecond-level prediction, ensuring the integrity of continuous scanning tests without disconnecting the physical radio frequency link, and converting multi-dimensional mechanical sensing data into a single-dimensional electromagnetic compensation scale in real time.

[0068] In S42, frequency domain extrapolation is performed for the test scenario of broadband phased array antennas. Since the physical medium change caused by the spring-and-dielectric effect exhibits non-dispersive characteristics within a certain bandwidth, a mapping model is used to first calculate the equivalent optical path length change, which is independent of the radio frequency. This change reflects the equivalent electrical length of the cable in free space. Subsequently, based on the space wavenumber factor derived from the reciprocal of the wavelength at each test frequency, this common optical path length change is directly converted into an independent phase compensation matrix for each test frequency.

[0069] Specifically, for any first in broadband measurement One frequency point to be tested First, the equivalent medium optical path change, which is independent of frequency, is calculated. Its calculation logic is as follows: ,in It characterizes the equivalent electrical length change obtained by linearly superimposing the total geometric path change caused by axial mechanical strain and the equivalent displacement correction.

[0070] Subsequently, based on the spatial wavenumber factor of the frequency to be measured... The equivalent medium optical path change Converted to real-time phase deviation prediction value at this frequency point The conversion algorithm model is as follows: .

[0071] Perform this operation on all the frequency points to be measured, and the resulting set of real-time phase deviation prediction values ​​for each frequency point constitutes an independent phase compensation matrix for each frequency point to be measured.

[0072] in, For the first The frequency points to be tested are at The real-time phase deviation prediction value (rad) at time t, the set of these prediction values ​​constitutes the independent phase compensation matrix for each frequency point to be measured; For the first The space wavenumber factor (rad / m) of the frequency to be measured in the insulating medium. For the first The radio frequency carrier frequency (Hz) of each frequency point to be tested; The speed of light in free space (m / s); The initial relative permittivity of the insulating medium; The equivalent optical path length change (m) is independent of frequency and represents the equivalent electrical length change obtained by linearly superimposing the total geometric path change caused by axial mechanical strain and the equivalent displacement correction.

[0073] This frequency extrapolation calculation logic based on the physical equivalent optical path allows for the calculation of phase compensation values ​​for all frequency points in sweep mode by performing only one calibration of the mechanical strain to optical path at the center frequency. This step eliminates the need for collecting calibration data at each frequency point individually, thus improving the overall data processing throughput of broadband antenna array testing.

[0074] like Figure 5 As shown, in one specific embodiment, S1 includes: S51. Constructing a complex exponential phase correction operator based on the real-time phase deviation prediction value. The phase correction operator is defined in the complex plane as a phase correction operator with a unit amplitude value and a phase angle of θ. The general mathematical expression for a complex vector is: .

[0075] S52. Perform a complex dot product between the original near-field complex measurement data and the phase correction operator. Phase inverse compensation cancels out the error term caused by cable movement by performing an equal-amplitude reverse rotation in the complex domain.

[0076] S53. Reconstruct the compensated sampling data to build the reconstructed near-field complex data. The reconstructed data eliminates the influence of random oscillations and can be directly used for subsequent beam pointing and far-field transformation calculations.

[0077] In this embodiment, it should be noted that in S51, after obtaining the predicted value, the reverse compensation stage begins. First, a compensation operator is generated to construct a mathematical operation body for error correction. Based on the real-time phase deviation prediction value of 3.983 radians, a complex exponential phase correction operator is constructed using Euler's formula. This operator is defined in the complex domain as a complex vector with a unit amplitude value and a phase angle of -3.983 radians. The computational logic for constructing this operator is to transform the phase error value to be subtracted into a rotating vector on the complex plane, thereby transforming the phase angle addition and subtraction operations of complex data into complex multiplication operations that are easier to implement in a digital signal processor. This step provides a mathematical tool for subsequent actual compensation operations, ensuring that while correcting the phase angle, the original amplitude information of the measured signal, i.e., the physical energy intensity, does not undergo numerical attenuation or change, thus maintaining the original fidelity of the RF amplitude data.

[0078] In S52, after constructing the correction operator, phase inverse compensation is performed to eliminate electromagnetic wavefront distortion that has occurred at the sampling point. The original near-field complex measurement data captured by hard synchronization at the sampling instant is extracted, assuming its original phase angle measurement value is 1.200 radians. This original complex data is then multiplied by a complex dot product with the phase correction operator having a phase angle of -3.983 radians. Let the original near-field complex measurement data at time tk be... The data after phase inversion compensation is Its calculation logic is as follows:

[0079] Assuming the original phase angle measurement is 1.200 radians, The value is 3.983 radians. Substituting this into the above formula is equivalent to performing a reverse rotation of the original phase angle in the polar coordinate system while keeping the signal amplitude constant. The real physical phase angle in space after the rotation is restored to -2.783 radians. Through this reverse cancellation logic, the phase noise injected by the mechanical deformation of the cable is corrected point by point at the back end of the data link, restoring the true phase state of the RF signal when it reaches the probe aperture in space, thus reducing the background of the fundamental numerical error for reconstructing near-field data.

[0080] In S53, the final step is to reconstruct the near-field complex data, completing the global aggregation and output preparation of the compensated data. The near-field complex data of each sampling point on the entire plane, after the aforementioned inverse rotation compensation, are extracted and reassembled into a matrix according to the original spatial trajectory coordinates of the two-dimensional scanning mechanism, constructing the reconstructed near-field complex dataset. Since each grid point in this dataset has undergone analytical and correction processing using the elastic-medium coupling model, the phase distribution discontinuity and wavefront distortion caused by cable sway are macroscopically eliminated. This calculation and aggregation logic generates near-field data with phase consistency, reducing the background error of the far-field sidelobe level in subsequent near- and far-field fast Fourier transform calculations, correcting potential beam pointing offsets, and ensuring the physical authenticity and engineering confidence of the 30 GHz millimeter-wave phased array antenna radiation characteristic test results.

[0081] This invention also provides a planar near-field measurement phase fluctuation compensation system based on cable motion sensing. The system is used to implement a planar near-field measurement phase fluctuation compensation method based on cable motion sensing. The system includes: The data synchronization acquisition module is used to synchronously acquire the axial mechanical strain set of the measurement cable in multiple feature sensing segments during planar near-field scanning, as well as the original near-field complex measurement data at the same sampling time; The dynamic deviation separation module is used to perform phase continuity processing on the raw near-field complex measurement data acquired under calibration conditions, and to separate the dynamic additional phase deviation by combining it with the spatial static reference phase. The mapping model construction module is used to construct a spring-medium coupling mapping model based on the axial mechanical strain set and dynamic additional phase deviation under the calibration state. The spring-medium coupling mapping model characterizes the combined effect of the geometric path change caused by axial mechanical strain and the phase velocity perturbation of the medium on the phase. The phase deviation prediction module is used to substitute the axial mechanical strain set obtained under the actual measurement state into the elastic-medium coupling mapping model to calculate and obtain the real-time phase deviation prediction value. The data inverse compensation module is used to perform phase inverse compensation on the original near-field complex measurement data obtained under the actual measurement state based on the real-time phase deviation prediction value, and obtain the reconstructed near-field complex data.

[0082] In one specific implementation, the data synchronization acquisition module is further configured to: generate a global hardware trigger signal based on a preset spatial sampling position; and, based on the global hardware trigger signal, synchronously latch the axial mechanical strain set and the original near-field complex measurement data within the allowable synchronization delay time difference.

[0083] To further clarify the operating mechanism and physical quantification process of the technical solution of this invention, the following analysis will be conducted in detail on the underlying derivation logic of the planar near-field measurement phase fluctuation compensation method and system based on cable motion sensing, using a scenario containing specific parameters and data.

[0084] To enable researchers and engineers in this field to intuitively and accurately understand the specific implementation path of the projectile-medium dual physics field coupling model and hardware hard synchronization mechanism described in this specification, a method for... A planar near-field scanning test scenario for a millimeter-wave phased array antenna is presented, providing a quantitative explanation of the physical mechanism and execution steps of this solution across the entire chain. In this test scenario, the test system utilizes a single antenna with a total force-bearing length... for The initial relative permittivity of the flexible radio frequency measurement cable with polytetrafluoroethylene (PTFE) insulation under stress-free conditions. Labeled as Considering the physical differences between cable batches and their sensitivity to ambient temperature, The value is obtained based on the in-situ calibration after the measurement system is assembled. By placing the cable in a static environment, a swept-frequency transmission test is performed using a standard component of known physical length. The signal group delay is measured using the time-domain analysis function of a network analyzer, and then the accurate value of the initial relative permittivity with system consistency is obtained by reverse deduction. For example, based on a nominal material value of 2.1, five static consistency tests are performed, and a weighted average is applied to remove outliers, ultimately determining the cable's relative permittivity under this specific measurement environment. The value is 2.13, thus eliminating the initial model deviation caused by uneven material batches.

[0085] In the system deployment phase corresponding to S1 (data synchronization acquisition step), engineers, based on the catenary dynamics model, will... The cables are divided into The feature perception segment consists of a violently swaying segment near the probe. The middle section of the suspended gravity section and the root torsion section near the test instrument Fiber Bragg grating (FBG) strain sensing nodes were precisely deployed inside the outer sheath of each segment.

[0086] During system initialization and parameter configuration, it is essential to first establish strict time boundaries for heterogeneous data acquisition, corresponding to the hardware-level hard synchronization delay tolerance determination in S1. Since the scanning mechanism generates transient mechanical shocks during cornering and reversal, the maximum axial strain rate of the measuring cable under this test condition is set. for At the same time, in order to ensure The required phase error tolerance for the far-field transformation accuracy of the radiation pattern in the frequency band is set to [value missing]. (about The speed of light in free space is known. for Furthermore, preliminary material testing indicates that the equivalent elastic-dielectric coupling constant of this batch of cables is... for Substituting the above parameters into the physical limit equation for the maximum synchronization delay time difference of the system. Perform the calculation. The calculation process is as follows: Molecular part ; denominator Dividing the two yields ,Right now This means that the clock offset between the FPGA-triggered strain gauge and the RF vector network analyzer must be controlled within a certain range. If the low-frequency state of mechanical strain cannot match the high-frequency phase angle of electromagnetic waves, subsequent compensation will fail.

[0087] After satisfying the aforementioned hard synchronization boundary conditions, the system enters the dynamic calibration phase corresponding to S2 (deviation separation step) and S3 (mapping model construction step). After acquiring a stress-free spatial static reference phase using a quasi-static slow scan, the system increases the scan speed to the actual operating rate. Through high-speed acquisition, because the cable moves more than half a wavelength with the probe, the original phase changes multiple times. The system calculates the first-order difference of the phase angle between adjacent sampling points and performs folding when the difference exceeds a threshold. Offset unwinding completes the phase continuity unwinding process. Then, the continuous absolute phase data is subtracted from the static reference phase matched to the spatial coordinates to extract the dynamic additional phase deviation. Using these calibration sample data, the system performs least-squares fitting on the dual-physics coupling equations of the projectile and dielectric, verifying and solidifying the aforementioned equivalent projectile-dielectric coupling constant. The accuracy.

[0088] The system then switched to dealing with the unknown. The formal testing of the millimeter-wave phased array antenna corresponds to S4 (real-time prediction step). This occurs at a specific sampling moment when the probe moves to the limit acceleration point at the edge of the coordinate system. The global hardware trigger signal, with an error of only tens of nanoseconds, latches the set of axial mechanical strains at the current moment: the strain is most intense in the section near the probe. Middle suspension section The root segment experiences the least stress. The system inputs this real-time strain data into the formula of the pre-constructed elastic-medium coupling mapping model. Analytical calculations are then performed. First, the spatial propagation constant is calculated. Next, calculate the sum of the inner products of the strain and physical length of each segment, which is the total geometric path change. .

[0089] If the system compensates solely based on the total geometric path change without considering dielectric constant perturbations, the resulting phase deviation will be However, according to first principles, cables are subject to... During cumulative equivalent stretching, the density of the internal polytetrafluoroethylene medium locally increases, leading to an increase in the relative permittivity. This slows down the phase velocity of the electromagnetic wave at this point, resulting in a cancellation effect in the phase evolution. In the model... This product factor quantifies this physical cancellation effect. Multiplying the total geometric path change by this coefficient yields the equivalent electrical length change. The final calculated real-time phase deviation prediction value is obtained. .

[0090] Finally, the system enters the data reconstruction process corresponding to S5 (reverse compensation step). In the previous... At the moment of sampling, the vector network analyzer hard-synchronizes and captures the raw near-field complex measurement data of the antenna under test. Assume its phase angle measurement in complex form is The deformation of the cable at this moment introduces a high [pressure / pressure]. The additional phase hysteresis noise causes the system to generate a phase angle of... Complex exponential phase correction operator By performing a complex dot product of the original data with this operator in the complex plane, it is equivalent to performing a reverse rotation of the angle while keeping the amplitude constant. After correction, the true spatial physical phase angle of the compensated near-field complex data is restored to... The above steps are executed in a microsecond-level loop at tens of thousands of sampling points across the entire plane, effectively compensating for the high-frequency phase distortion caused by the dynamic deformation of the flexible cable, and providing data support for the subsequent output of high-confidence antenna far-field parameters.

[0091] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0092] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0093] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A planar near-field measurement phase fluctuation compensation method based on cable motion sensing, characterized in that, The methods include: Simultaneously acquire the axial mechanical strain set of the measurement cable in multiple feature sensing segments during planar near-field scanning, as well as the original near-field complex measurement data at the same sampling time; The raw near-field complex measurement data acquired under calibration conditions are processed to achieve phase continuity, and the dynamic additional phase deviation is separated by combining the spatial static reference phase. Based on the axial mechanical strain set and dynamic additional phase deviation under the calibration state, a spring-medium coupling mapping model is constructed. The spring-medium coupling mapping model characterizes the combined effect of the geometric path change caused by axial mechanical strain and the phase perturbation of the medium on the phase. The phase perturbation of the medium refers to the small deviation of the electromagnetic wave propagation speed caused by the change in the internal medium density due to the force on the cable. The construction of the elastic-medium coupling mapping model includes: multiplying each strain value in the axial mechanical strain set with the initial physical length of the corresponding feature sensing segment, and summing the product results to calculate the total geometric path change; calculating the equivalent displacement correction amount characterizing the phase velocity perturbation cancellation effect of the medium based on the product relationship between the equivalent elastic-medium coupling constant and the total geometric path change; linearly superimposing the total geometric path change amount and the equivalent displacement correction amount to obtain the equivalent electrical length change amount; and multiplying the equivalent electrical length change amount with the spatial propagation constant of electromagnetic waves in the insulating medium to construct an elastic-medium coupling mapping model whose output result is the real-time phase deviation prediction value. Among them, the equivalent elastic-medium coupling constant is used to characterize the relative cancellation effect of dielectric constant drift on phase velocity under unit axial mechanical strain, and the equivalent elastic-medium coupling constant is obtained by least squares fitting of the axial mechanical strain set obtained under calibration state and the dynamic additional phase deviation. Substitute the set of axial mechanical strains obtained under actual measurement conditions into the elastic-medium coupling mapping model to calculate and obtain the real-time phase deviation prediction value; Phase inverse compensation is performed on the original near-field complex measurement data obtained under the actual measurement state based on the real-time phase deviation prediction value to obtain the reconstructed near-field complex data.

2. The planar near-field measurement phase fluctuation compensation method based on cable motion sensing according to claim 1, characterized in that, Each of the multiple feature sensing segments contains at least one deformation extreme point of the measuring cable during dynamic movement, which is either the curvature change rate extreme point or the tension gradient extreme point.

3. The planar near-field measurement phase fluctuation compensation method based on cable motion sensing according to claim 1, characterized in that, The synchronous acquisition process includes: A global hardware trigger signal is generated based on a preset spatial sampling position; Based on the global hardware trigger signal, within the allowable synchronization delay time difference, the axial mechanical strain set and the original near-field complex measurement data are synchronously latched.

4. The planar near-field measurement phase fluctuation compensation method based on cable motion sensing according to claim 3, characterized in that, The upper limit of the synchronization delay time difference is calculated and determined based on the preset limit phase error tolerance, the radio frequency carrier frequency, the total length of the measuring cable under stress, and the maximum axial strain rate of the measuring cable under extreme conditions.

5. The planar near-field measurement phase fluctuation compensation method based on cable motion sensing according to claim 1, characterized in that, The raw near-field complex measurement data acquired under calibration conditions are processed to achieve phase continuity. Combined with a spatial static reference phase, dynamic additional phase bias is separated, including: Calculate the first-order phase difference between adjacent sampling points in space; When the absolute value of the first-order phase difference exceeds the half-cycle determination threshold, the phase sequence is compensated for integer-cycle numerical bias to obtain continuous absolute phase data. The dynamic additional phase deviation is obtained by subtracting the continuous absolute phase data from the corresponding spatial static reference phase.

6. The planar near-field measurement phase fluctuation compensation method based on cable motion sensing according to claim 1, characterized in that, It also includes a frequency domain extension step for multi-frequency measurements: The frequency-independent equivalent medium optical path change is calculated using the elastic-medium coupling mapping model. Based on the spatial wavenumber factor of each frequency point to be measured, the equivalent medium optical path change is converted into an independent phase compensation matrix for each frequency point to be measured. Phase inverse compensation is performed on the original near-field complex measurement data at the corresponding measured frequency point based on the phase compensation matrix.

7. A planar near-field measurement phase fluctuation compensation system based on cable motion sensing, used to implement the planar near-field measurement phase fluctuation compensation method based on cable motion sensing as described in any one of claims 1 to 6, characterized in that, The system includes: The data synchronization acquisition module is used to synchronously acquire the axial mechanical strain set of the measurement cable in multiple feature sensing segments during planar near-field scanning, as well as the original near-field complex measurement data at the same sampling time; The dynamic deviation separation module is used to perform phase continuity processing on the raw near-field complex measurement data acquired under calibration conditions, and to separate the dynamic additional phase deviation by combining it with the spatial static reference phase. The mapping model construction module is used to construct a spring-medium coupling mapping model based on the axial mechanical strain set and dynamic additional phase deviation under the calibration state. The spring-medium coupling mapping model characterizes the combined effect of the geometric path change caused by axial mechanical strain and the phase velocity perturbation of the medium on the phase. The phase deviation prediction module is used to substitute the axial mechanical strain set obtained under the actual measurement state into the elastic-medium coupling mapping model to calculate and obtain the real-time phase deviation prediction value. The data inverse compensation module is used to perform phase inverse compensation on the original near-field complex measurement data obtained under the actual measurement state based on the real-time phase deviation prediction value, and obtain the reconstructed near-field complex data.

8. The planar near-field measurement phase fluctuation compensation system based on cable motion sensing according to claim 7, characterized in that, The data synchronization acquisition module is also used for: A global hardware trigger signal is generated based on a preset spatial sampling position; Based on the global hardware trigger signal, within the allowable synchronization delay time difference, the axial mechanical strain set and the original near-field complex measurement data are synchronously latched.

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