Reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system and method

Abstract

The application discloses a reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system and method, relates to the field of ground-based synthetic aperture radar interferometry, and comprises a radar host module, an electromechanical reconfigurable extension arm mechanism, a secondary rotating mechanism and an extended antenna unit. In view of physical space displacement errors introduced by mechanical reconfiguration, the host fixed array which is not affected by reconfiguration is taken as an absolute space reference, an error mapping model is constructed in combination with scene high-coherent point echo phases, mechanical tolerance phase errors are compensated in a signal processing domain through reverse inversion, after self-calibration, the system generates a three-dimensional digital elevation model in combination with multi-baseline fusion unwrapping, and finally calculates radar line-of-sight micro-deformation fields superimposed on three-dimensional space coordinates. The application has low cost, high tolerance and sub-millimeter three-dimensional monitoring precision, and is suitable for structural health monitoring of high and steep slopes, dams and buildings.

Description

Technical Field

[0001] This application relates to the field of ground-based synthetic aperture radar interferometry, and in particular to a reconfigurable ground-based MIMO three-dimensional deformation interferometry radar system and method. Background Technology

[0002] Ground-based interferometric synthetic aperture radar (GB-InSAR) plays an irreplaceable role in monitoring sub-millimeter-level micro-deformations in landslides, dams, bridges, and open-pit mine slopes. In existing technologies, first-generation mechanical rail-mounted radars rely on a physical antenna moving along a rail for scanning, resulting in long imaging times and susceptibility to atmospheric phase disturbances leading to decoherence. While second-generation one-dimensional pure solid-state MIMO radars achieve millisecond-level rapid scanning, they still suffer from a fundamental lack of dimension, only capable of two-dimensional imaging (range-azimuth) and unable to distinguish target elevation angle information. When facing steep slopes or complex terrain, two-dimensional imaging is highly susceptible to severe radar layover effects, leading to widespread false alarms or missed detections in deformation monitoring.

[0003] To address the challenge of 3D observation, existing technologies typically employ two approaches: one is to use conventional mechanical solid-aperture radar with a 2D turntable, but this leads to a further increase in scanning time and a significant increase in the risk of atmospheric decoherence; the other is to use ultra-large 2D array MIMO radar, which achieves 3D imaging through a fixed 2D antenna array. However, the 2D array approach results in an exponential increase in the number of RF front-end channels and the computational power required for data processing, leading to extremely high manufacturing costs and making it difficult to widely deploy and apply in practical field engineering.

[0004] Furthermore, if a mechanically reconfigurable structure is adopted to reduce costs, the electromechanical mechanism will inevitably introduce physical spatial displacement errors and mechanical tolerances on the order of millimeters or sub-millimeters during the horizontal extension and vertical deployment reconfiguration process. If reconfigurable three-dimensional deformation interferometric radar is achieved by relying on ultra-high precision machining and reset mechanisms, cost and reliability are difficult to balance, and the impact of reconfiguration tolerances on the interferometric phase may lead to divergence in three-dimensional elevation calculations. Therefore, how to effectively compensate for mechanical reconfiguration errors and achieve high-precision three-dimensional deformation monitoring while reducing hardware complexity is a technical challenge that urgently needs to be solved in this field. Summary of the Invention

[0005] The purpose of this application is to provide a reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system and method, which realizes the switching between two-dimensional high-resolution and three-dimensional elevation observation modes through a physically reconfigurable architecture, and combines a mechanical error self-calibration algorithm based on host reference and high coherence points to achieve sub-millimeter level three-dimensional deformation monitoring in complex scenarios in a low-cost and high-tolerance manner.

[0006] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system, comprising: The radar host module has a basic MIMO transceiver antenna array rigidly arranged on its radiating surface for transmitting and receiving detection signals and serving as the absolute spatial reference of the system. An electromechanical reconfigurable extension arm mechanism, one end of which is hinged to the radar host module via a main rotary joint, is configured to be able to reconfigure the physical space between a horizontally extended state and a vertically deployed state. The length of the extension arm is set based on the working wavelength and angular ambiguity constraints of the radar system. The secondary rotating mechanism is located at the end of the electromechanical reconfigurable extension arm mechanism; An extended antenna unit is mounted on the secondary rotating mechanism; the secondary rotating mechanism is configured to synchronously adjust the spatial polarization direction of the extended antenna unit during the horizontal to vertical reconfiguration process of the electromechanical reconfiguration extension arm mechanism, so as to maintain polarization alignment with the basic MIMO transceiver antenna array.

[0007] Optionally, at least two sets of extended antenna elements are mounted radially spaced on the extended arm mechanism; when the extended arm mechanism is in the vertically extended state, the at least two sets of extended antenna elements together with the basic MIMO transceiver antenna array of the radar host module form a multi-scale interferometric baseline combination, wherein the shorter baseline is configured to provide an unambiguous pitch angle measurement range, and the longer baseline is configured to provide a high-precision pitch elevation resolution.

[0008] Optionally, the main rotary joint and the secondary rotary mechanism adopt a manual indexing rotary device with mechanical limit buckles, or a servo motor drive device with an integrated high-precision angle encoder.

[0009] Secondly, this application provides a signal processing method based on a reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system, the signal processing method comprising: Step S1: Control the system to be in a horizontally extended state, and use the basic MIMO transceiver antenna array and the extended antenna unit to form a horizontally widened virtual array to collect first-state echo data; Step S2: Drive the electromechanical reconfiguration extension arm mechanism to rotate to the vertically deployed state, and simultaneously drive the secondary rotation mechanism to adjust the polarization direction of the extended antenna unit, and collect the second state echo data; Step S3: Using the fixed array coordinates of the basic MIMO transceiver antenna array of the radar host module as the absolute spatial reference, jointly extract the high coherence point echo phase in the target scene, construct a nonlinear phase mapping model including the three-dimensional mechanical displacement error of the extended arm, obtain the residual phase error compensation value in each state through numerical iterative inversion, and perform phase offset compensation on the echo data of the first state and the echo data of the second state, and output the calibrated first state data and the calibrated second state data. Step S4: Input the calibrated first state data into the two-dimensional imaging processing module to generate a high azimuth resolution radar image, and input the calibrated first state data and the calibrated second state data together into the multi-baseline interferometry processing module to perform dewinding operation on the compensated multi-baseline interferometry phase, and combine it with the spatial geometric projection matrix to generate a three-dimensional digital elevation model of the target. Step S5: Based on the micro-phase changes of the three-dimensional digital elevation model and corresponding resolution units obtained at different observation times, calculate the radial deformation field of the target in the radar line of sight under three-dimensional spatial coordinates, and superimpose and map the radial deformation field onto the three-dimensional digital elevation model to output the final deformation monitoring result.

[0010] Optionally, step S3 specifically includes: S31: Select N permanent scattering points PS with high signal-to-noise ratio and uniform spatial distribution within the field of view of the target scene as virtual spatial beacons; S32: For each PS point, the energy of the PS point in the reference image generated by the host base array is traced back to the original MIMO channel domain, and the original complex observation phase of the PS point in all equivalent transmit and receive channels in the first state echo data and the second state echo data is extracted respectively. S33: Construct a first phase mapping model corresponding to the horizontal extension state and a second phase mapping model corresponding to the vertical unfolding state respectively; the first phase mapping model and the second phase mapping model express the theoretical phase center coordinates of each equivalent channel as the superposition of ideal design coordinates and unknown three-dimensional mechanical displacement deviation vector. Using the original complex observation phases of the N PS points, construct nonlinear overdetermined equation sets about the three-dimensional mechanical displacement deviation vector of the first state and the three-dimensional mechanical displacement deviation vector of the second state respectively. S34: Solve the overdetermined equations respectively to obtain the three-dimensional mechanical displacement deviation vector of the first state and the three-dimensional mechanical displacement deviation vector of the second state, and calculate the theoretical phase deviation of each channel affected by the extension arm in the corresponding state to generate the first state compensation phase and the second state compensation phase. S35: Apply the first state compensation phase to the complex image domain of the first state echo data, apply the second state compensation phase to the complex image domain of the second state echo data, complete the physical topology digital reset of the virtual array, and output the calibrated first state data and the calibrated second state data.

[0011] Optionally, solving the overdetermined system of equations in step S34 specifically involves: Using the channels of the basic MIMO transceiver antenna array as zero-displacement references, the maximum likelihood estimation method, weighted least squares method, or Levenberg-Marquardt algorithm is used to perform global optimization in the multidimensional parameter space to solve for the mechanical displacement deviation vector that achieves the best consistency match between the phase center position of each channel of the reconstructed full array and the physical phase observation values ​​of N spatial beacon points.

[0012] Optionally, in step S4, the unwinding operation of the compensated multi-baseline interference phase specifically includes: By using a short baseline composed of adjacent extended antenna elements on the same rigid extended arm, sparse interference fringes are extracted to determine the absolute elevation range of the target and obtain the short baseline result. Using the long baseline formed by the radar main module base array and the antenna at the end of the extended arm, dense interference fringes are extracted to obtain the long baseline phase ambiguity; By using a multi-baseline phase fusion mechanism, the short baseline results are used to constrain the long baseline phase ambiguity to obtain an integer phase ambiguity solution. The target pitch angle is then inverted using the spatial geometric projection matrix to generate the three-dimensional digital elevation model.

[0013] Optionally, an atmospheric phase calibration step may be included between steps S5 and S4: Using the calibrated first state data and the calibrated second state data, atmospheric disturbance phase components in the scene background region are extracted, an atmospheric phase spatiotemporal variation model is constructed, and spatial interpolation compensation is performed to eliminate the interference of atmospheric decoherence on the microscopic phase variation.

[0014] Optionally, in step S1, the equivalent aperture size of the horizontally widened virtual array is determined by the horizontal extension length of the extended arm. Its design meets the azimuth angular resolution requirements, and the number of physical antenna channels is equivalently extended to the product of the number of transmit and receive channels through MIMO virtual array synthesis technology.

[0015] Optionally, the radar line-of-sight radial deformation field is calculated based on the calibrated microscopic phase difference and the radar operating wavelength through an interferometric phase-displacement conversion relationship.

[0016] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system and method, which has the following significant advantages: Architecture Restructuring Reduces Costs and Mutual Coupling: The electromechanical reconfiguration extension arm enables the physical switching between "horizontal high-resolution two-dimensional observation" and "vertical three-dimensional elevation mapping," avoiding the exponential cost increase and antenna mutual coupling problem caused by the massive radio frequency channels of traditional two-dimensional area array MIMO radar, and achieving three-dimensional observation capability with extremely low hardware complexity.

[0017] Polarization alignment ensures signal quality: The secondary rotating mechanism synchronously adjusts the polarization direction of the extended antenna when the arm rotates, ensuring strict matching of transmit and receive polarization in both horizontal and vertical states, thus avoiding echo amplitude attenuation and phase distortion caused by polarization mismatch.

[0018] Full-state mechanical error self-calibration: Innovatively using a rigid host array as the absolute spatial reference, an overdetermined phase equation is constructed using scene permanent scatterers (PS points). This mechanism treats mechanical tolerances as parameters to be solved, completing the "precise reset" of the virtual array topology in the digital signal processing domain. This significantly reduces the reliance on high-precision mechanical reset mechanisms, enabling the system to maintain phase consistency while allowing for millimeter-level mechanical tolerances.

[0019] Multi-scale baseline fusion deambiguity: In the vertical state, short baselines (multiple antennas on the extended arm) are used to determine the unambiguous elevation range, and long baselines (from the main unit to the end of the arm) are used to provide high sensitivity. The elevation ambiguity problem of traditional single-baseline interferometric radar is completely solved by fusion dewinding.

[0020] Tightly coupled processing chain: The data flow of each processing step is strictly closed-loop. The calibrated data is directly used for 3D DEM construction. The real spatial coordinates of the 3D DEM are used as the geometric reference for radial deformation calculation. Finally, the sub-millimeter deformation field with real 3D topology is output, which completely solves the monitoring blind spot caused by the overlapping effect and meets the structural health monitoring needs of complex engineering scenarios such as steep slopes and dams. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a signal processing method based on a reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system, as provided in an embodiment of this application. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0025] Example 1: System Hardware Architecture This embodiment provides a reconfigurable ground-based MIMO deformation interferometric radar system with three-dimensional imaging capabilities. The core of the system consists of four parts: Radar main unit module: Internally integrates a rigid and fixed basic MIMO transceiver antenna array (e.g., 8 transmit and 16 receive). The relative positions of each unit are factory-calibrated and remain stable, serving as the origin of the absolute spatial coordinate system and the phase reference for the entire system.

[0026] Electromechanical reconfigurable extendable arm mechanism: Made of high-strength carbon fiber or aerospace-grade aluminum, one end is hinged to the radar main module via a main rotary joint. The arm length is optimized based on the radar operating frequency band (such as Ku-band or Ka-band) and azimuth / elevation ambiguity constraints. The extendable arm supports switching between two operating modes: 0° (horizontal extension) and 90° (vertical deployment).

[0027] Secondary Rotation Mechanism and Extended Antenna Units: A secondary rotation mechanism is mounted at the end of the extender arm, on which extended antenna units (preferably arranged in two or more groups at radial intervals) are fixed. When the extender arm performs horizontal-to-vertical reconfiguration, the secondary rotation mechanism rotates synchronously according to feedback from the angle encoder, ensuring that the radiating polarization surface of the extended antenna unit is always parallel to the polarization direction of the host base array, thus eliminating polarization mismatch loss.

[0028] This application innovatively divides the system into a "rigidly arranged radar main array" and "non-rigidly moving extended antenna elements." The radar main array not only transmits and receives detection signals, but also serves as an "absolute spatial zero-position displacement reference" in the digital processing domain. Since the displacement deviation of each equivalent channel of the main array is rigidly locked to zero, this mechanism essentially locks the key degrees of freedom for solving the nonlinear overdetermined equations, ensuring that the inversion algorithm can still converge even in the presence of mechanical errors.

[0029] Example 2: Self-calibration and imaging process of overdetermined phase equation based on host reference This embodiment details the specific execution process of the signal processing method, as follows: Step S1 (Horizontal State Detection): Control the system to be in a horizontally extended state, and use the basic MIMO transceiver antenna array and the extended antenna unit to form a horizontally widened virtual array to collect first state echo data.

[0030] Specifically, the control system is in a horizontally extended state. The main array and extended antenna elements work together to synthesize a MIMO virtual array with significantly expanded horizontal width. The radar transmits a broadband LFM signal, receives the echo, performs range compression and azimuth focusing, and collects and stores the first-state echo data. This data is mainly used to provide high-azimuth resolution two-dimensional radar images, providing a high-quality data source for subsequent selection of space beacons.

[0031] Step S2 (Vertical State Detection): Drive the electromechanical reconfiguration extension arm mechanism to rotate to the vertically deployed state, and simultaneously drive the secondary rotation mechanism to adjust the polarization direction of the extended antenna element, and collect the second state echo data.

[0032] Specifically, the drive electromechanical reconfiguration extension arm mechanism rotates to the vertically deployed state. Simultaneously, the secondary rotation mechanism is triggered to perform polarization alignment compensation. The system then re-transmits the detection signal, acquiring second-state echo data. This data incorporates a vertical interferometric baseline, carrying the target's elevation and altitude information.

[0033] Step S3 (Full-state mechanical error self-calibration): Using the fixed array coordinates of the basic MIMO transceiver antenna array of the radar host module as the absolute spatial reference, the echo phase of the high coherence point in the target scene is jointly extracted, a nonlinear phase mapping model including the three-dimensional mechanical displacement error of the extended arm is constructed, the residual phase error compensation value in each state is obtained by numerical iterative inversion, and the echo data of the first state and the echo data of the second state are phase offset compensation, and the calibrated first state data and the calibrated second state data are output.

[0034] This step is the crucial link between the raw data and the high-precision 3D solution. The specific execution is as follows: S31: Select N permanent scattering points PS with high signal-to-noise ratio and uniform spatial distribution within the field of view of the target scene as virtual spatial beacons; S32: For each PS point, the energy of the PS point in the reference image generated by the host base array is traced back to the original MIMO channel domain, and the original complex observation phase of the PS point in all equivalent transmit and receive channels in the first state echo data and the second state echo data is extracted respectively. S33: Construct a first phase mapping model corresponding to the horizontal extension state and a second phase mapping model corresponding to the vertical unfolding state respectively; the first phase mapping model and the second phase mapping model express the theoretical phase center coordinates of each equivalent channel as the superposition of ideal design coordinates and unknown three-dimensional mechanical displacement deviation vector. Using the original complex observation phases of the N PS points, construct nonlinear overdetermined equation sets about the three-dimensional mechanical displacement deviation vector of the first state and the three-dimensional mechanical displacement deviation vector of the second state respectively. S34: Solve the overdetermined equations respectively to obtain the three-dimensional mechanical displacement deviation vector of the first state and the three-dimensional mechanical displacement deviation vector of the second state, and calculate the theoretical phase deviation of each channel affected by the extension arm in the corresponding state to generate the first state compensation phase and the second state compensation phase. S35: Apply the first state compensation phase to the complex image domain of the first state echo data, apply the second state compensation phase to the complex image domain of the second state echo data, complete the physical topology digital reset of the virtual array, and output the calibrated first state data and the calibrated second state data.

[0035] Traditional error compensation methods based on permanent scatterers (PS) typically involve calibration in the complex image domain (SLC) or interferometric phase domain after imaging focusing, using polynomial fitting or establishing a spatially varying baseline model. Mathematically, these methods deal with the aliasing phase of coherently superimposed multi-channel echoes, failing to decompose the error and assign it to individual antenna channels. Therefore, they cannot correct for individual mechanical deformations of specific antennas (such as physical position deviations of extended channels introduced by extended arm rotation). For the reconfigurable configuration of interferometric radar based on extended arms in this application, a method for directly calibrating channel position errors is proposed: First, highly coherent PS points are selected in the focused two-dimensional complex image, and their three-dimensional spatial coordinates are determined. Then, using these coordinates, the energy of these PS points in the complex image is traced back to the unfocused original MIMO channel domain before imaging through coherent inverse projection (despreading), extracting the original observation phase corresponding to each physical channel. Since the radar main array is rigidly fixed and has no additional positional error, the algorithm uses the main channel as the absolute spatial position reference. It constructs a nonlinear overdetermined system of equations for the multi-channel observation phases of each PS point, relating them to the unknown three-dimensional displacement error of the extended arm channel. This system is then solved directly through numerical iteration to compensate for the actual positional deviation of each physical channel. This design, which transforms adaptive image fitting into solving for physical channel positional errors, significantly relaxes the rigid constraints on the processing and resetting accuracy of the reconfigurable cantilever mechanism. Compared to the traditional design approach that pursues high-precision mechanical resetting, it significantly reduces hardware manufacturing costs while ensuring measurement accuracy, resulting in a clear transformative effect and competitive advantage.

[0036] Step S4 (3D Imaging Solution): Input the calibrated first state data into the 2D imaging processing module to generate a high azimuth resolution radar image, and input the calibrated first state data and the calibrated second state data together into the multi-baseline interferometry processing module to perform dewinding operation on the compensated multi-baseline interferometry phase, and combine it with the spatial geometric projection matrix to generate a 3D digital elevation model of the target.

[0037] Specifically, the calibrated first-state data output from step S3 is input into a conventional SAR / ISAR imaging link to generate a high-azimuth resolution two-dimensional radar image. Simultaneously, the calibrated first-state data and the calibrated second-state data are jointly input into the multi-baseline interferometry processing module. In the vertical state, the short baselines (small antenna spacing) on ​​the extended arm are used to extract sparse interferometric fringes, determine the absolute elevation range of the target, and ensure de-ambiguity; the long baselines from the main unit to the end of the arm are used to extract dense interferometric fringes, providing elevation sensitivity. Integer ambiguities are resolved using a multi-baseline fusion algorithm, and the elevation angle is inverted using the spatial geometric projection matrix. The output is a high-precision three-dimensional digital elevation model (3D DEM).

[0038] The dewinding operation is performed on the compensated multi-baseline interferometric phase, specifically including: By using a short baseline composed of adjacent extended antenna elements on the same rigid extended arm, sparse interference fringes are extracted to determine the absolute elevation range of the target and obtain the short baseline result. Using the long baseline formed by the radar main module base array and the antenna at the end of the extended arm, dense interference fringes are extracted to obtain the long baseline phase ambiguity; By using a multi-baseline phase fusion mechanism, the short baseline results are used to constrain the long baseline phase ambiguity to obtain an integer phase ambiguity solution. The target pitch angle is then inverted using the spatial geometric projection matrix to generate the three-dimensional digital elevation model.

[0039] Step S5 (Radial Deformation Calculation): Based on the micro-phase changes of the three-dimensional digital elevation model and corresponding resolution units obtained at different observation times, calculate the radial deformation field of the target in the radar line of sight under three-dimensional spatial coordinates, and superimpose and map the radial deformation field onto the three-dimensional digital elevation model to output the final deformation monitoring result.

[0040] Based on the 3D DEM generated in step 4, the system establishes the spatial three-dimensional geometric coordinates of the scene units. In subsequent monitoring cycles, combined with conventional atmospheric calibration, the system calculates the microscopic changes of the resolution units along the radar line-of-sight (LOS). Finally, the system superimposes and maps these sub-millimeter-level radial deformation information onto the corresponding three-dimensional geometric positions on the 3D DEM, enabling structural health monitoring of targets such as dams and slopes.

[0041] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0042] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system, characterized in that, The reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system includes: The radar main unit module has a basic MIMO transceiver antenna array rigidly arranged on its radiating surface for transmitting and receiving detection signals and serving as the absolute spatial reference of the system. An electromechanical reconfigurable extension arm mechanism, one end of which is hinged to the radar host module via a main rotary joint, is configured to be able to reconfigure the physical space between a horizontally extended state and a vertically deployed state. The length of the extension arm is set based on the working wavelength and angular ambiguity constraints of the radar system. The secondary rotating mechanism is located at the end of the electromechanical reconfigurable extension arm mechanism; An extended antenna unit is mounted on the secondary rotating mechanism; the secondary rotating mechanism is configured to synchronously adjust the spatial polarization direction of the extended antenna unit during the horizontal to vertical reconfiguration process of the electromechanical reconfiguration extension arm mechanism, so as to maintain polarization alignment with the basic MIMO transceiver antenna array.

2. The reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system according to claim 1, characterized in that, At least two sets of extended antenna elements are mounted radially spaced on the extended arm mechanism. When the extended arm mechanism is in a vertically extended state, the at least two sets of extended antenna elements together with the basic MIMO transceiver antenna array of the radar host module form a multi-scale interferometric baseline combination, wherein the shorter baseline is configured to provide an unambiguous pitch angle measurement range, and the longer baseline is configured to provide a high-precision pitch elevation resolution.

3. The reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system according to claim 1, characterized in that, The main rotary joint and the secondary rotary mechanism adopt a manual indexing rotary device with mechanical limit buckles, or a servo motor drive device with an integrated high-precision angle encoder.

4. A signal processing method based on a reconfigurable ground-based MIMO three-dimensional deformation interferometric radar system, characterized in that, The signal processing method includes: Step S1: Control the system to be in a horizontally extended state, and use the basic MIMO transceiver antenna array and the extended antenna unit to form a horizontally widened virtual array to collect first-state echo data; Step S2: Drive the electromechanical reconfiguration extension arm mechanism to rotate to the vertically deployed state, and simultaneously drive the secondary rotation mechanism to adjust the polarization direction of the extended antenna unit, and collect the second state echo data; Step S3: Using the fixed array coordinates of the basic MIMO transceiver antenna array of the radar host module as the absolute spatial reference, jointly extract the high coherence point echo phase in the target scene, construct a nonlinear phase mapping model including the three-dimensional mechanical displacement error of the extended arm, obtain the residual phase error compensation value in each state through numerical iterative inversion, and perform phase offset compensation on the echo data of the first state and the echo data of the second state, and output the calibrated first state data and the calibrated second state data. Step S4: Input the calibrated first state data into the two-dimensional imaging processing module to generate a high azimuth resolution radar image, and input the calibrated first state data and the calibrated second state data together into the multi-baseline interferometry processing module to perform dewinding operation on the compensated multi-baseline interferometry phase, and combine it with the spatial geometric projection matrix to generate a three-dimensional digital elevation model of the target. Step S5: Based on the micro-phase changes of the three-dimensional digital elevation model and corresponding resolution units obtained at different observation times, calculate the radial deformation field of the target in the radar line of sight under three-dimensional spatial coordinates, and superimpose and map the radial deformation field onto the three-dimensional digital elevation model to output the final deformation monitoring result.

5. The signal processing method according to claim 4, characterized in that, Step S3 specifically includes: S31: Select N permanent scattering points PS with high signal-to-noise ratio and uniform spatial distribution within the field of view of the target scene as virtual spatial beacons; S32: For each PS point, the energy of the PS point in the reference image generated by the host base array is traced back to the original MIMO channel domain, and the original complex observation phase of the PS point in all equivalent transmit and receive channels in the first state echo data and the second state echo data is extracted respectively. S33: Construct a first phase mapping model corresponding to the horizontal extension state and a second phase mapping model corresponding to the vertical unfolding state respectively; the first phase mapping model and the second phase mapping model express the theoretical phase center coordinates of each equivalent channel as the superposition of ideal design coordinates and unknown three-dimensional mechanical displacement deviation vector. Using the original complex observation phases of the N PS points, construct nonlinear overdetermined equation sets about the three-dimensional mechanical displacement deviation vector of the first state and the three-dimensional mechanical displacement deviation vector of the second state respectively. S34: Solve the overdetermined equations respectively to obtain the three-dimensional mechanical displacement deviation vector of the first state and the three-dimensional mechanical displacement deviation vector of the second state, and calculate the theoretical phase deviation of each channel affected by the extension arm in the corresponding state to generate the first state compensation phase and the second state compensation phase. S35: Apply the first state compensation phase to the complex image domain of the first state echo data, apply the second state compensation phase to the complex image domain of the second state echo data, complete the physical topology digital reset of the virtual array, and output the calibrated first state data and the calibrated second state data.

6. The signal processing method according to claim 5, characterized in that, The specific steps in step S34 of solving the overdetermined system of equations are as follows: Using the channels of the basic MIMO transceiver antenna array as zero-displacement references, the maximum likelihood estimation method, weighted least squares method, or Levenberg-Marquardt algorithm is used to perform global optimization in the multidimensional parameter space to solve for the mechanical displacement deviation vector that achieves the best consistency match between the phase center position of each channel of the reconstructed full array and the physical phase observation values ​​of N spatial beacon points.

7. The signal processing method according to claim 4, characterized in that, In step S4, the dewinding operation is performed on the compensated multi-baseline interferometric phase, specifically including: By using a short baseline composed of adjacent extended antenna elements on the same rigid extended arm, sparse interference fringes are extracted to determine the absolute elevation range of the target and obtain the short baseline result. Using the long baseline formed by the radar main module base array and the antenna at the end of the extended arm, dense interference fringes are extracted to obtain the long baseline phase ambiguity; By using a multi-baseline phase fusion mechanism, the short baseline results are used to constrain the long baseline phase ambiguity to obtain an integer phase ambiguity solution. The target pitch angle is then inverted using the spatial geometric projection matrix to generate the three-dimensional digital elevation model.

8. The signal processing method according to claim 4, characterized in that, An atmospheric phase calibration step is also included between steps S5 and S4: Using the calibrated first state data and the calibrated second state data, atmospheric disturbance phase components in the scene background region are extracted, an atmospheric phase spatiotemporal variation model is constructed, and spatial interpolation compensation is performed to eliminate the interference of atmospheric decoherence on the microscopic phase variation.

9. The signal processing method according to claim 4, characterized in that, In step S1, the equivalent aperture size of the horizontally widened virtual array is determined by the horizontal extension length of the extension arm. Its design meets the azimuth angular resolution requirements, and the number of physical antenna channels is equivalently expanded to the product of the number of transmit and receive channels through MIMO virtual array synthesis technology.

10. The signal processing method according to claim 4, characterized in that, The radar line-of-sight radial deformation field is calculated based on the calibrated microscopic phase difference and the radar operating wavelength through an interferometric phase-displacement conversion relationship.

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