Split multi-frequency reconfigurable three-dimensional radar detection system and detection method

Abstract

This invention provides a split-type multi-frequency reconfigurable 3D radar detection system and method. Multiple independently frequency-selectable antenna array modules are flexibly reconfigured through a standardized combination interface. Combined with a distributed main control module, inter-module collaborative control and data fusion are achieved, constructing a modular detection architecture with configurable frequencies, variable form, and adjustable deployment. This architecture supports switching between various operating modes, such as single-module handheld fine detection and multi-module vehicle-mounted rapid survey. A multi-axis robotic arm precisely adjusts the relative positions and detection angles of the modules, ensuring spatiotemporal synchronization and consistency of multi-frequency data. Combined with high-precision positioning and 3D reconstruction algorithms, high-precision 3D images of underground targets are generated. This invention overcomes the limitations of traditional radar frequency fixation and structural rigidity, balancing detection depth and resolution, and significantly improving equipment portability, scalability, and environmental adaptability.

Description

Technical Field

[0001] This invention relates to the field of radar detection technology, and in particular to a split-type multi-frequency reconfigurable three-dimensional radar detection system and detection method. Background Technology

[0002] 3D Ground Penetrating Radar (3D GPR), a non-destructive testing technology that uses high-frequency electromagnetic waves to detect the distribution of underground media, has been widely used in fields such as road defect detection, underground pipeline detection, archaeological exploration, and engineering quality assessment. Its basic principle is to radiate high-frequency electromagnetic waves underground through a transmitting antenna, and receive the reflected echoes from different interfaces of underground media through a receiving antenna. Based on information such as the time delay, amplitude, and phase of the echoes, the spatial location and physical properties of underground targets are inverted.

[0003] With the increasing demands for refined, efficient, and multi-dimensional information acquisition in engineering exploration, the limitations of traditional 3D ground-penetrating radar systems in terms of architecture design and detection capabilities are becoming increasingly apparent. Specifically, existing technologies suffer from the following shortcomings: 1) Single frequency configuration, making it difficult to balance detection depth and resolution. Most existing 3D radar systems operate on a single fixed frequency. Due to the limitations of electromagnetic wave propagation characteristics, low-frequency signals have strong penetration capabilities but low resolution, making it difficult to identify shallow micro-defects or fine structures; high-frequency signals have high resolution but limited penetration depth, making it impossible to reliably detect deep targets. The single-frequency scheme prevents users from flexibly adjusting the operating frequency band according to actual needs when facing detection tasks of different depths and accuracies, resulting in a single device being unable to meet the application needs of multiple scenarios such as deep general surveys and shallow detailed surveys. 2) Fixed system architecture, insufficient scalability and reconfigurability. The frequency channels, antenna configurations, and hardware architecture of traditional radar systems are usually fixed at the factory, lacking modular and standardized design thinking. When users face different detection targets or depth requirements, they cannot extend the frequency, replace modules, or upgrade the functions of existing equipment. They can only meet diverse task needs by purchasing multiple dedicated devices with different frequency bands. This one-device-one-frequency model not only results in low equipment utilization but also significantly increases the user's procurement costs and maintenance burden. 3) There is a contradiction between portability and high performance, and poor environmental adaptability. To provide multi-frequency detection capabilities, some existing solutions adopt an integrated design, encapsulating antennas, transceiver modules, and control units of multiple frequencies in the same housing. This structure results in bulky and heavy equipment, making it difficult to install flexibly on vehicle platforms and unsuitable for complex terrain or narrow spaces where vehicles cannot access, such as sidewalks, utility tunnels, and archaeological sites. The field applicability and single-person operability of the equipment are thus severely restricted. 4) Limited three-dimensional detection capabilities and incomplete spatial information acquisition. Most current radar systems still use single-channel or simple linear array designs, and the collected data can only generate two-dimensional profile images, which are difficult to truly reflect the three-dimensional spatial morphology of underground anomalies. Although three-dimensional calculations can be approximated by densely deploying survey lines and then stitching them together, this method suffers from problems such as low data acquisition efficiency, large spatial registration errors, and complex processing procedures, making it difficult to meet the modern engineering requirements for accurate quantification of three-dimensional information such as the spatial location, orientation, scale, and volume of underground targets.

[0004] In summary, existing 3D ground-penetrating radar systems have significant shortcomings in terms of frequency configuration flexibility, system architecture reconfigurability, equipment portability, and 3D detection capabilities. They are unable to meet the urgent needs of complex and ever-changing engineering detection scenarios for high-performance, high-efficiency, and highly adaptable detection equipment, and a new radar structure and detection scheme are urgently needed. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a split-type multi-frequency reconfigurable three-dimensional radar detection system and detection method to solve the problems of existing three-dimensional ground penetrating radar systems being unable to flexibly adapt to diverse detection scenario requirements due to single frequency configuration, fixed system architecture, and limitations in portability and detection capabilities.

[0006] One aspect of the present invention provides a split-type multi-frequency reconfigurable three-dimensional radar detection system, the system comprising: Multiple antenna array modules are deployed in a distributed manner, and each antenna array module selects to operate at multiple preset operating frequencies; The combined interface module includes a mechanical connection structure and an electrical connection interface. The mechanical connection structure is used for detachably installing the antenna array module and deploying it in one of a variety of preset relative positions. The electrical connection interface provides the antenna array module with power, control signal, and data signal transmission channels. A positioning module that performs positioning based on one or more positioning signals; The distributed master control module is connected to the antenna array module through the electrical connection interface. According to the task requirements, it selects one or more of the antenna array modules to perform detection, and controls the antenna array modules to work independently or collaboratively according to the preset operating frequency and preset relative position matched to the task requirements. It collects the radar detection data returned by the antenna array modules and the positioning data returned by the positioning module to reconstruct a three-dimensional detection image. The communication interface module is used to communicate with the distributed main control module to acquire and transmit the three-dimensional detection image to the outside world. The power management module is used to supply power to the antenna array module, the combined interface module, the positioning module, the distributed main control module, and the communication interface module.

[0007] In some embodiments, the antenna array module employs MIMO array antenna elements, comprising multiple independent transmit and receive channels. Each transmit channel includes a digitally controlled attenuator, a power amplifier, a switchable cavity bandpass filter, a standing wave detection circuit, and a transmit antenna, with a transmit frequency range covering 50MHz to 2.5GHz. Each receive channel includes a limiter, a low-noise amplifier, an intermediate frequency filter, an ADC sampling circuit, and a receive antenna. The antenna array module also integrates an FPGA signal processing unit and an ARM control unit. The FPGA signal processing unit is used to perform transmission timing control and to perform ADC data acquisition, bandpass filtering, gain compensation, noise suppression, channel calibration, and buffering on the raw echo data. The ARM control unit is used to perform status monitoring and communication interaction with the distributed main control module. The operating frequencies of the antenna array module include: a 200MHz frequency for detecting depths of 3 to 10 meters, a 400MHz frequency for detecting depths of 1.5 to 5 meters, a 900MHz frequency for detecting depths of 0.5 to 2 meters, and a 1200MHz frequency for detecting depths of 0.1 to 1 meter.

[0008] In some embodiments, the mechanical connection structure is a multi-axis robotic arm, which is fixedly connected to the antenna array module via quick-release components. The multi-axis robotic arm adjusts the relative position and detection angle of the antenna array module in response to the control signals of the distributed master control module.

[0009] In some embodiments, in a collaborative work scenario, the multi-axis robotic arm, in response to the control signal of the distributed master control module, deploys the antenna array modules selected based on a task requirement to the same horizontal detection surface, with the elevation difference between each antenna array module being within 1 / 4 of the wavelength of the medium corresponding to the highest operating frequency; and the central axis of each antenna array module coincides with the direction of the survey line. In an independent working scenario, the multi-axis robotic arm, in response to the control signals of the distributed main control module, independently deploys the antenna array modules selected based on multiple task requirements according to their corresponding detection positions and angles.

[0010] In some embodiments, the positioning module includes a BeiDou positioning module, an RTK positioning module, and an IMU inertial measurement unit; The power management module deploys an independent power supply within each of the antenna array modules for power supply, and / or provides centralized power supply through a power sharing bus.

[0011] In some embodiments, the distributed master control module includes: The global synchronization control unit has a built-in Beidou-docked thermostatic crystal oscillator to generate a reference clock and distribute it to the antenna array module through a synchronization clock bus to achieve time synchronization. The data processing and storage unit, equipped with a GPU parallel acceleration unit, is used to fuse the raw echo data collected by each of the antenna array modules and reconstruct the three-dimensional detection image. The interactive visualization unit allows users to input control commands and preview the three-dimensional detection image based on a touch-screen human-computer interaction interface.

[0012] In some embodiments, the communication interface module connects to a cloud server via a preset link, and is used to forward the raw echo data and the three-dimensional detection image to the cloud server for remote access, or to forward task requirements based on the cloud server to achieve remote control.

[0013] On the other hand, the present invention also provides a detection method based on a split-type multi-frequency reconfigurable three-dimensional radar. The method is executed based on the distributed main control module in the above-mentioned split-type multi-frequency reconfigurable three-dimensional radar detection system, and the method includes the following steps: In response to the requirements of the detection mission, a detection configuration scheme is selected and distributed to the combined interface module and the antenna array module, and configuration completion feedback is received. In a collaborative working scenario, the detection configuration scheme includes multiple selected antenna array modules and their relative positions, transmission parameters, and reception parameters. In an independent working scenario, the detection configuration scheme includes multiple selected antenna array modules and their independent deployment positions, detection angles, transmission parameters, and reception parameters. Perform multi-channel data acquisition, synchronously acquire the raw echo data of the antenna array module currently participating in the detection, the positioning data of the positioning module, and record the timestamp and the attitude information of the antenna array module; After preprocessing and filtering the multi-channel data, the original echo data of multiple frequencies collected by each antenna array module are fused in a collaborative working scenario, and three-dimensional imaging reconstruction is performed to obtain a collaborative three-dimensional detection image; or in an independent working scenario, the original echo data collected by each antenna array module are separately subjected to three-dimensional imaging reconstruction to obtain an independent three-dimensional detection image. The collaborative 3D detection image or the independent 3D detection image is used to identify, classify, and label targets, and then the results are visualized.

[0014] In some embodiments, the transmission parameters include the operating frequency, transmission power, pulse width, pulse repetition frequency, and transmission timing of the antenna array module; the reception parameters include reception gain, sampling rate, sampling duration, number of superpositions, and filtering parameters. The operating frequencies include: a 200MHz frequency for detecting depths of 3 to 10 meters, a 400MHz frequency for detecting depths of 1.5 to 5 meters, a 900MHz frequency for detecting depths of 0.5 to 2 meters, and a 1200MHz frequency for detecting depths of 0.1 to 1 meter.

[0015] In some embodiments, before selecting a detection configuration scheme in response to detection mission requirements, the method further includes: The system performs a level-one self-check of the local functions of the distributed master control module, a level-two self-check of the connection status between modules in the system, and a level-three self-check of the functions of each module in the system. The system summarizes the self-test results, classifies faulty devices according to their severity, issues alarms for minor faults, automatically isolates serious faults, updates the available hardware topology of the system, and sends a self-test report and fault prompts to the user terminal.

[0016] The modular, multi-frequency reconfigurable 3D radar detection system and method of this invention flexibly disassembles and reassembles multiple independently frequency-selectable antenna array modules through standardized combination interfaces. A distributed main control module enables collaborative control and data fusion between modules, thereby constructing a modular detection architecture with configurable frequencies, variable form, and adjustable deployment. This architecture not only supports switching between various operating modes, from single-module handheld fine detection to multi-module vehicle-mounted rapid surveys, but also allows for precise adjustment of the relative positions and detection angles between modules via a multi-axis robotic arm, ensuring strict synchronization and consistency of multi-frequency data in the spatiotemporal dimensions. Furthermore, combined with high-precision positioning and 3D reconstruction algorithms, it generates high-precision 3D images of underground targets. The method, through its modular, modular design, overcomes the limitations of fixed frequencies and rigid structures in traditional radar systems, achieving a balance between detection depth and resolution across multiple scenarios. It significantly improves the portability, scalability, and environmental adaptability of the equipment. Simultaneously, its multi-channel synchronous acquisition and 3D imaging capabilities enhance the accuracy and completeness of underground space information acquisition, effectively solving the problems of poor adaptability, low utilization, and operational limitations of existing equipment in complex detection tasks.

[0017] Additional advantages, objects, and features of the invention will be set forth in part in the description which follows, and will also become apparent in part to those skilled in the art upon studying the description, or may be learned by practice of the invention. The objects and other advantages of the invention can be realized and obtained by means of the structures specifically pointed out in the description and drawings.

[0018] Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable with the present invention will become clearer from the following detailed description. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, are not intended to limit the scope of the invention. In the drawings: Figure 1 This is a schematic diagram of the structure of a split-type multi-frequency reconfigurable three-dimensional radar detection system according to an embodiment of the present invention.

[0020] Figure 2 This is a flowchart illustrating a detection method based on a split-type multi-frequency reconfigurable three-dimensional radar according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0022] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.

[0023] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0024] It should also be noted that, unless otherwise specified, the term "connection" in this article can refer not only to a direct connection, but also to an indirect connection involving an intermediary.

[0025] Existing 3D ground-penetrating radar (GPR) systems generally operate at a single fixed frequency. Limited by the propagation characteristics of electromagnetic waves, low-frequency signals, while possessing strong penetration capabilities, suffer from insufficient resolution, while high-frequency signals, despite their high resolution, have limited penetration depth. This makes it difficult for a single device to simultaneously meet the diverse detection needs of both deep general surveys and shallow detailed surveys. Furthermore, traditional system architectures are fixed at the factory, lacking modular and standardized design. Users cannot flexibly expand or reorganize frequency channels according to actual tasks, and must instead purchase multiple dedicated devices with different frequency bands to address different scenarios, resulting in low equipment utilization and high operating costs. To provide multi-frequency detection capabilities, some integrated solutions forcibly integrate multiple frequency modules into a single housing, resulting in bulky and heavy equipment that is difficult to carry in complex terrain or confined spaces, severely limiting its field applicability. In addition, existing systems mostly adopt single-channel or simple linear array designs, and the collected data can only generate two-dimensional profile images, which cannot truly restore the three-dimensional spatial morphology of underground anomalies. Even with post-processing, they still face problems such as low data acquisition efficiency and large spatial registration errors, making it difficult to meet the modern engineering requirements for accurate quantification of three-dimensional information such as the spatial location, orientation, and volume of underground targets.

[0026] In view of this, one aspect of the present invention provides a split-type multi-frequency reconfigurable three-dimensional radar detection system, such as... Figure 1 As shown, the system includes: an antenna array module, a combined interface module, a positioning module, a distributed main control module, a communication interface module, and a power management module.

[0027] Multiple antenna array modules are deployed in a distributed manner, with each module operating at one of several preset operating frequencies. In some embodiments, the antenna array module employs a MIMO array of antenna elements, comprising multiple independent transmit and receive channels. Each transmit channel includes a digitally controlled attenuator, a power amplifier, a switchable cavity bandpass filter, a standing wave detection circuit, and a transmit antenna, with a transmit frequency range covering 50MHz to 2.5GHz. Each receive channel includes a limiter, a low-noise amplifier, an intermediate frequency filter, an ADC sampling circuit, and a receive antenna.

[0028] Specifically, this antenna array module uses a multi-input multi-output (MIMO) array antenna unit as its core hardware foundation. Through multiple integrated independent transmit and receive channels, it achieves parallel detection of the underground medium. During transmission, the module selects one of several preset operating frequencies as the current operating frequency band based on the task requirements issued by the distributed master control system. Then, the transmit power is precisely controlled by a digitally controlled attenuator within the transmit channel. The RF signal is amplified by a power amplifier, and then the transmit frequency band is finely selected and its purity optimized by a switchable cavity bandpass filter to filter out out-of-band interference, ensuring the accuracy and stability of the output signal frequency. A standing wave detection circuit monitors the matching status between the transmitting antenna and the transmission path in real time to prevent overload of reflected power due to impedance mismatch, protecting the transmission link. The processed electromagnetic wave signal is finally radiated outward through the transmitting antenna and enters the underground medium.

[0029] In the receiving phase, the receiving antenna captures the weak echo signal reflected from the underground medium. This signal is first overload protected by a limiter to prevent strong signals from damaging subsequent circuits. Then, it is amplified by a low-noise amplifier to achieve high gain and low noise, thus improving system sensitivity. The amplified signal then enters an intermediate frequency filter to further filter out out-of-band noise, and finally, a high-precision ADC sampling circuit converts the analog signal into a digital signal. Throughout the transmission and reception process, multiple transmit and receive channels can work collaboratively according to the spatiotemporal coding strategy of the MIMO array. Through time-division or frequency-division transmission timing and parallel reception by multiple channels, a multi-angle, multi-offset detection data set is formed. This module thus achieves a complete closed-loop operation, from frequency selection, transmit power control, and ensuring the purity of the transmitted signal, to high-sensitivity reception and high-fidelity digital conversion of weak echo signals, providing high-quality, multi-dimensional raw data support for subsequent data fusion and 3D imaging.

[0030] The antenna array module operates at the following frequencies: 200MHz for detecting depths of 3 to 10 meters, 400MHz for detecting depths of 1.5 to 5 meters, 900MHz for detecting depths of 0.5 to 2 meters, and 1200MHz for detecting depths of 0.1 to 1 meter.

[0031] There is an inherent contradiction between the penetration depth and resolution of electromagnetic waves in underground media: the lower the frequency, the longer the wavelength, and the stronger the penetration ability, but the lower the resolution; the higher the frequency, the shorter the wavelength, and the higher the resolution, but the penetration depth is limited. This invention constructs a complete detection spectrum chain from low frequency to high frequency by integrating four typical frequency bands into the same system. Among them, the 200MHz band has a longer wavelength and stronger penetration capability, making it suitable for surveying deep targets in the 3 to 10 meter depth range. It can effectively detect large-scale anomalies such as deep cavities, groundwater levels, or deeply buried pipelines. The 400MHz band serves as a transition between mid and low frequencies, balancing a certain penetration depth and resolution. It is suitable for fine detection in medium-deep areas of 1.5 to 5 meters. The 900MHz band belongs to the mid-to-high frequency range, with significantly improved resolution. It is suitable for high-resolution imaging of shallow structures of 0.5 to 2 meters, and can clearly identify interlayer interfaces of road structures, shallow defects, and medium-depth buried pipelines. The 1200MHz band has the shortest wavelength and the highest resolution. It is suitable for ultra-high precision detection in shallow surface areas of 0.1 to 1 meter, and can accurately depict fine structures such as surface cracks, road surface voids, shallow buried pipelines, and small targets.

[0032] This invention utilizes multiple operating frequencies, either collaboratively or individually, to acquire complete underground information from shallow to deep layers according to task requirements. It achieves a balance between detection depth and resolution for multiple targets, overcoming the inherent limitation of single frequencies in meeting diverse detection needs. The frequencies complement each other: deep low-frequency data provides deep background information for shallow high-frequency data, while shallow high-frequency data supplements the deep low-frequency data with fine structural features. After multi-frequency data fusion, a full-profile 3D image from the surface to depth can be generated, achieving integrated presentation of the entire detection area. Users can flexibly select single or multiple frequency combinations based on the target depth and accuracy requirements of specific detection tasks. This allows for both high-precision shallow detection and large-scale deep surveys, truly achieving the design goal of multi-purpose, on-demand configuration. This frequency combination covers typical detection depth ranges for major application scenarios such as municipal road detection, underground pipeline detection, bridge and tunnel detection, archaeological exploration, and engineering quality assessment, demonstrating good industry versatility and scenario adaptability.

[0033] In other embodiments, the antenna array module also integrates an FPGA signal processing unit and an ARM control unit. The FPGA signal processing unit is used to perform transmission timing control and to perform ADC data acquisition, bandpass filtering, gain compensation, noise suppression, channel calibration and buffering on the raw echo data. The ARM control unit is used to perform status monitoring and communication interaction with the distributed main control module.

[0034] The combined interface module includes a mechanical connection structure and an electrical connection interface. The mechanical connection structure allows for the detachable installation of the antenna array module and its deployment in a variety of preset relative positions. The electrical connection interface provides power, control signal, and data signal transmission channels for the antenna array module. This design allows antenna array modules of different frequencies to be quickly assembled, disassembled, and repositioned according to mission requirements, forming a flexible system configuration ranging from independent single-module operation to multi-module collaborative detection.

[0035] In some embodiments, the mechanical connection structure is a multi-axis robotic arm, which is fixedly connected to the antenna array module via quick-release components. The multi-axis robotic arm adjusts the relative position and detection angle of the antenna array module in response to control signals from the distributed main control module. Responding to control signals issued by the distributed main control module, the multi-axis robotic arm can automatically adjust the spatial relative position and detection angle of the antenna array module, realizing an intelligent upgrade of the connection structure from passively fixed to actively adjustable. Based on this, differentiated control strategies are executed according to different operating scenarios.

[0036] In some embodiments, in a collaborative work scenario, the multi-axis robotic arm, in response to control signals from a distributed master control module, deploys antenna array modules selected based on a task requirement onto the same horizontal detection surface. The elevation difference between each antenna array module is within 1 / 4 of the wavelength of the medium corresponding to the highest operating frequency; and the central axis of each antenna array module coincides with the direction of travel of the measurement line. In an independent work scenario, in response to control signals from a distributed master control module, the multi-axis robotic arm independently deploys antenna array modules selected based on multiple task requirements according to their corresponding detection positions and angles.

[0037] In collaborative work scenarios, the multi-axis robotic arm deploys multiple antenna array modules selected based on the same task requirements onto the same horizontal detection surface, strictly controlling the elevation difference between modules to not exceed one-quarter of the wavelength of the medium corresponding to the highest operating frequency, while ensuring that the central axis of each module coincides with the direction of the survey line. This precise positional constraint effectively guarantees that the multi-frequency modules have a consistent phase reference plane and spatial reference system during synchronous detection, avoiding data misalignment and imaging distortion caused by elevation differences or axis deflection, laying a spatiotemporal consistency foundation for subsequent multi-frequency data fusion and high-precision 3D reconstruction. In independent work scenarios, the multi-axis robotic arm independently deploys the selected antenna array modules according to their respective detection positions and angles based on multiple different task requirements, enabling the same system to simultaneously perform multiple detection tasks of different depths and accuracies, greatly improving the parallel efficiency and equipment utilization of on-site operations.

[0038] A positioning module performs positioning based on one or more positioning signals. In some embodiments, the positioning module includes a BeiDou positioning module, an RTK positioning module, and an IMU inertial measurement unit.

[0039] The distributed master control module connects to the antenna array module via an electrical connection interface. It selects one or more antenna array modules to perform detection according to task requirements, and controls the antenna array modules to work independently or collaboratively according to the preset operating frequency and preset relative position matched to the task requirements. It collects radar detection data returned by the antenna array module and positioning data returned by the positioning module to reconstruct a three-dimensional detection image.

[0040] In some embodiments, the distributed master control module includes: a global synchronization control unit, which has a built-in BeiDou-trained temperature-controlled crystal oscillator to generate a reference clock and distribute it to the antenna array modules via a synchronization clock bus to achieve time synchronization; a data processing and storage unit, equipped with a GPU parallel acceleration unit, used to fuse the raw echo data collected by each antenna array module and reconstruct the three-dimensional detection image; and an interactive visualization unit, which allows input of control commands and preview display of the three-dimensional detection image based on a touch-screen human-machine interface.

[0041] Specifically, the global synchronization control unit uses a BeiDou-trained cryogenic crystal oscillator as the reference clock source to generate a high-precision, low-jitter synchronization clock signal. This signal is then distributed to all participating antenna array modules via a synchronization clock bus, ensuring strict consistency in transmission timing and sampling time across all modules. This lays the foundation for the subsequent spatiotemporal fusion of multi-frequency data. The interactive visualization unit receives user-defined detection task requirements via a touch-screen human-machine interface. Users can set parameters such as target detection depth, expected resolution, and operating mode through the graphical interface. The distributed main control module automatically matches the optimal frequency combination and module deployment scheme accordingly and sends configuration commands to the combination interface module and antenna array module via the electrical connection interface. The detection operation begins after each module completes self-checks and configuration confirmation. The actions performed include the following: 1) During the data acquisition phase, the distributed master control module initiates the synchronous acquisition process according to the selected working mode. In collaborative working scenarios, multiple antenna array modules simultaneously or in a time-sharing manner transmit electromagnetic waves according to the transmission sequence set by the distributed master control module. Each receiving channel acquires the reflected echoes from the underground medium in parallel. Simultaneously, the positioning module records the spatial coordinates and antenna attitude information of each data point in real time, including high-precision latitude and longitude coordinates and elevation data provided by BeiDou or RTK, as well as attitude parameters such as heading angle, pitch angle, and roll angle provided by the IMU inertial measurement unit. All raw echo data, positioning data, and timestamp information are packaged and transmitted back to the data processing and storage unit of the distributed master control module through the electrical connection interface.

[0042] 2) In the preprocessing stage, the data processing unit performs a series of preprocessing operations on the raw echo data. First, bandpass filtering is performed on the data of each channel to filter out out-of-band noise and interference signals according to the operating frequency range of the channel; then, gain compensation is performed, including time gain compensation and automatic gain control, to correct the amplitude attenuation caused by geometric diffusion and medium absorption during electromagnetic wave propagation; then, noise suppression algorithms are used to reduce the interference of environmental noise and system noise; finally, channel calibration is performed, using built-in calibration parameters to compensate for the amplitude and phase differences between channels, ensuring the consistency and comparability of multi-channel data.

[0043] 3) In the multi-frequency data fusion stage, the distributed master control module performs spatiotemporal registration and information fusion on the preprocessed data from different frequencies. Spatiotemporal registration, based on the position and attitude information recorded by the positioning module, maps all data to a unified world coordinate system, forming a data volume with precise spatial attributes. Information fusion leverages the complementary advantages of different frequencies' detection characteristics: low-frequency data provides deep background information and macroscopic structural features, while high-frequency data supplements shallow fine structure and detail information. Through fusion algorithms such as wavelet transform or sparse representation based on dictionary learning, the multi-frequency information is integrated into a comprehensive data volume with broadband response characteristics, retaining both deep penetration capability and shallow high-resolution characteristics.

[0044] 4) In the 3D imaging reconstruction stage, the GPU parallel acceleration unit on the distributed main control module executes 3D reconstruction algorithms such as migration imaging or tomography. Migration imaging, based on electromagnetic wave propagation theory, reverses the echo data collected from each receiving point to its true spatial reflection point location, eliminating diffraction interference and focusing the underground anomaly to the correct spatial coordinates. Tomography, on the other hand, inverts and solves for the electromagnetic parameter distribution of the underground medium, constructing a 3D attribute volume reflecting differences in dielectric constant or conductivity. In collaborative scenarios, since each antenna array module has been precisely deployed to the same horizontal detection surface using a multi-axis robotic arm with an elevation difference controlled within a quarter wavelength, the data collected by multiple modules has a highly consistent phase reference surface, which can be directly merged into large-aperture array data, significantly improving lateral resolution and imaging signal-to-noise ratio. After reconstruction, a data volume containing the 3D spatial distribution of the underground target is generated.

[0045] 5) In the visualization output stage, the interactive visualization unit renders and displays the 3D data volume. Volume rendering technology generates a 3D image, intuitively presenting the spatial morphology and distribution characteristics of the underground anomaly; isosurface extraction technology delineates the boundary interface between the target body and the surrounding medium; and a slicing tool generates 2D cross-sectional views in any direction for users to perform detailed analysis. Simultaneously, the distributed main control module automatically calculates the anomaly's location coordinates, depth, spatial orientation, dip angle, volume, and other quantitative parameters based on the 3D data volume, and overlays these parameters onto the 3D image in labeled form, forming a 3D detection result containing quantitative information. Finally, this 3D detection image is transmitted externally through the communication interface module for viewing by remote terminals or shared in the cloud.

[0046] The communication interface module is used to communicate with the distributed main control module to acquire and transmit 3D detection images. In some embodiments, the communication interface module connects to a cloud server via a preset link to forward raw echo data and 3D detection images to the cloud server for remote access, or to achieve remote control based on task requirements forwarded by the cloud server.

[0047] The power management module supplies power to the antenna array module, combined interface module, positioning module, distributed main control module, and communication interface module. The power management module provides power to each antenna array module via an independent power supply and / or centralized power supply via a shared power bus.

[0048] On the other hand, the present invention also provides a detection method based on a split-type multi-frequency reconfigurable three-dimensional radar. This method is executed based on the distributed main control module in the aforementioned split-type multi-frequency reconfigurable three-dimensional radar detection system, such as... Figure 2 As shown, the method includes the following steps S101~S104: Step S101: In response to the detection mission requirements, select a detection configuration scheme, send the detection configuration scheme to the combined interface module and the antenna array module, and receive configuration completion feedback; wherein, in the collaborative working scenario, the detection configuration scheme includes the selected multiple antenna array modules and their relative positions, transmission parameters and reception parameters; in the independent working scenario, the detection configuration scheme includes the selected multiple antenna array modules and their independent deployment positions, detection angles, transmission parameters and reception parameters.

[0049] Step S102: Perform multi-channel data acquisition, synchronously acquire the raw echo data of the antenna array module currently participating in the detection, the positioning data of the positioning module, and record the timestamp and the attitude information of the antenna array module.

[0050] Step S103: After preprocessing and filtering the multi-channel data, the original echo data of multiple frequencies collected by each antenna array module are fused in the collaborative working scenario, and three-dimensional imaging reconstruction is performed to obtain a collaborative three-dimensional detection image; or the original echo data collected by each antenna array module are separately reconstructed in the independent working scenario to obtain an independent three-dimensional detection image.

[0051] Step S104: Perform target recognition, classification, and annotation on the collaborative 3D detection image or the independent 3D detection image, and output the visualization.

[0052] Specifically, in step S101, a detection configuration scheme is selected in response to the detection task requirements. The distributed main control module receives the detection task requirements input by the user through the interactive visualization unit, including parameters such as target detection depth, expected resolution, and operating area characteristics. Then, it automatically matches the optimal detection configuration scheme according to a preset rule base. In a collaborative work scenario, the configuration scheme specifies the use of multiple antenna array modules, which are deployed to the same horizontal detection surface by a multi-axis robotic arm. The relative positions between each module are precisely controlled, and transmission and reception parameters are configured for each module. In some embodiments, the transmission parameters include the operating frequency, transmission power, pulse width, pulse repetition frequency, and transmission timing of the antenna array module; the reception parameters include reception gain, sampling rate, sampling duration, superposition times, and filtering parameters; the operating frequencies include: 200MHz for detection at depths of 3-10 meters, 400MHz for detection at depths of 1.5-5 meters, 900MHz for detection at depths of 0.5-2 meters, and 1200MHz for detection at depths of 0.1-1 meters. To ensure all modules operate collaboratively under a unified spatial reference and acquisition timing, the configuration scheme specifies the independent deployment locations and detection angles of multiple antenna array modules in independent working scenarios. Each module configures its corresponding transmit and receive parameters according to its independent task requirements, achieving parallel and distributed detection operations. After the configuration scheme is distributed to the combination interface module and the antenna array module, the system waits for each module to complete self-checks and configuration confirmations and provide status feedback.

[0053] Step S102 executes multi-channel data acquisition. The distributed main control module distributes a synchronization clock signal through the global synchronization control unit, triggering all antenna array modules currently participating in the detection to simultaneously or in a time-division manner transmit electromagnetic waves according to a preset transmission sequence. Each receiving channel acquires reflected echo data from the underground medium in parallel. Simultaneously, the positioning module records the spatial coordinates and antenna attitude information of each data point in real time, including high-precision latitude, longitude, and elevation data provided by BeiDou or RTK, and attitude parameters such as heading, pitch, and roll angles provided by the IMU inertial measurement unit. All raw echo data, positioning data, timestamp information, and attitude information are packaged and transmitted back to the main control module's data processing and storage unit via an electrical connection interface, forming a multi-channel raw dataset with precise spatiotemporal labels.

[0054] Step S103 is the core step in data processing and 3D imaging reconstruction. First, the acquired multi-channel data undergoes preprocessing and filtering, including bandpass filtering to remove out-of-band noise in each operating frequency band, time gain compensation to correct electromagnetic wave propagation attenuation, noise suppression to improve the signal-to-noise ratio, and channel calibration to compensate for amplitude and phase differences between multiple channels. After preprocessing, the system performs differentiated imaging processing based on the working scenario.

[0055] In collaborative operation scenarios, multiple antenna array modules are precisely deployed to the same horizontal detection surface via a multi-axis robotic arm. The elevation difference between modules is controlled within one-quarter of the wavelength of the medium corresponding to the highest operating frequency, and the central axis of each module coincides with the direction of the survey line. Therefore, the data collected by multiple modules possess a highly consistent phase reference surface and spatial benchmark. The system performs multi-frequency fusion processing on the raw echo data from multiple frequencies. The fusion process fully utilizes the detection advantages of each frequency: low-frequency data contributes deep penetration capability and macroscopic structural information, while high-frequency data provides shallow high-resolution details and fine features. Through fusion algorithms such as wavelet transform or dictionary-based sparse representation, the multi-frequency information is integrated into a comprehensive data volume with broadband response characteristics. The fused data is then used for 3D imaging reconstruction. An offset imaging algorithm is employed to reverse the echo data collected from each receiving point to its true spatial reflection point location, eliminating diffraction interference and focusing the underground anomaly on the correct spatial coordinates. Simultaneously, a tomographic imaging algorithm is used to invert the electromagnetic parameter distribution of the underground medium, constructing a 3D attribute volume reflecting differences in dielectric constant or conductivity. In collaborative work scenarios, due to the large aperture array effect formed by multiple modules, the reconstructed collaborative 3D exploration images have higher lateral resolution and signal-to-noise ratio, and can clearly present the complete underground structure from the shallow surface to the deep layers.

[0056] In independent operation scenarios, each antenna array module independently acquires data according to its deployment location and detection angle, without any spatiotemporal correlation requirements between them. The system preprocesses the raw echo data acquired by each module separately, and then independently performs 3D imaging reconstruction to generate multiple independent 3D detection images. Each image corresponds to the detection area and depth range covered by a frequency module, which is suitable for scenarios involving multi-task parallel operation or independent detection of different areas.

[0057] Step S104 executes target recognition, classification, annotation, and visualization output. The system performs target recognition and classification processing on the reconstructed 3D detection image. Based on a preset underground anomaly feature library, it automatically identifies typical targets such as cavities, pipelines, voids, and cracks, and classifies the targets according to echo characteristics. The identified targets are annotated in the 3D image, with annotations including quantitative parameters such as target type, location coordinates, burial depth, spatial orientation, dip angle, and volume. The interactive visualization unit generates 3D stereo images using volume rendering technology, supporting arbitrary angle rotation and slice browsing. It can also generate various visualization results such as isosurface maps and cross-sectional views. Finally, the 3D detection image containing annotation information is transmitted externally or stored locally through the communication interface module for comprehensive analysis by the user.

[0058] By selecting a scenario-adaptive configuration scheme, flexible switching between collaborative and independent detection is achieved, fully leveraging the modular and reconfigurable architecture advantages of the system. The combination of multi-channel synchronous acquisition and high-precision positioning data ensures accurate registration of data in the spatiotemporal dimensions, laying a data foundation for high-quality 3D imaging. Multi-frequency data fusion in collaborative scenarios effectively integrates the advantages of detection at different frequencies, achieving a unity of deep penetration and shallow high resolution. Parallel processing capabilities in independent scenarios significantly improve the efficiency of multi-task operations. The final output 3D detection images not only contain intuitive spatial morphological information but also provide precise quantitative parameters, offering comprehensive and reliable data support for engineering detection and disease diagnosis.

[0059] In some embodiments, before selecting a detection configuration scheme in response to detection mission requirements, the method further includes steps S201 and S202: Step S201: Perform a level 1 self-check of the local functions of the distributed master control module, a level 2 self-check of the connection status between modules in the system, and a level 3 self-check of the functions of each module in the system.

[0060] Step S202: Perform self-test result summary. If a fault exists, classify the faulty equipment and issue alarm prompts for minor faults. Automatically isolate serious faults, update the available hardware topology of the system, and simultaneously send a self-test report and fault prompts to the user terminal.

[0061] Steps S201 and S202 constitute a three-level self-test and fault handling process before system startup or configuration. Step S201 performs self-tests step by step according to the logic from core to periphery and from basic to complete: The first-level self-test focuses on the local functions of the distributed main control module itself, including the verification of the working status of key components such as control units, data processing units, synchronization clock modules, and interactive interfaces, to ensure the reliability of the system brain; the second-level self-test detects the connection status between various modules in the system, covering the mechanical connection confirmation and electrical connection continuity test of the combined interface module, and verifying whether the data transmission and power supply links of the electrical connection interface are unobstructed; the third-level self-test delves into the functions of independent units such as antenna array modules, positioning modules, and power management modules, including the working status of the transmitting and receiving channels, frequency switching capabilities, data acquisition integrity, positioning signal reception quality, and power supply capacity and charging / discharging performance. After completing the three-level self-test, step S202 summarizes and classifies the self-test results. For minor faults such as channel gain deviation or temporary loss of positioning signal lock, alarm prompts are generated without affecting the operation of the main functions. For serious faults such as transmitter module damage, electrical connection interruption, or main control unit abnormality, automatic isolation is performed, the module is removed from the system hardware topology, and the available resource list is updated. At the same time, a self-test report and fault prompts containing fault type, fault location, and handling suggestions are fed back to the user. Through the three-level progressive self-test mechanism, a comprehensive health status assessment is achieved from the system core to peripheral modules, and from hardware connection to functional integrity. This effectively avoids the risk of invalid detection or data quality degradation caused by equipment failure. The graded fault handling strategy ensures the continuous availability of the system's core functions while realizing the automatic isolation and topology reconstruction of faulty modules, improving the system's fault tolerance and robustness in field operations. The real-time feedback of self-test reports and fault prompts provides users with a clear understanding of equipment status and a basis for operation and maintenance decisions, significantly reducing the time cost of on-site troubleshooting and enhancing the reliability and maintainability of the system in complex field operation environments.

[0062] The present invention will now be described with reference to a specific embodiment: This embodiment provides a split-type reconfigurable quad-band three-dimensional radar detection system, including: a distributed main control system, a band 1 antenna array module, a band 2 antenna array module, a band 3 antenna array module, a band 4 antenna array module, and an interface module for connecting different band antenna array combinations. The system framework is as follows: Figure 1 As shown.

[0063] The frequency band 1-4 antenna array modules adopt the same modular structure design, and parameters such as frequency and channels can be customized according to detection requirements. The frequency band 1-4 antenna array modules can work independently or can be arbitrarily combined through combination interface modules to form single-frequency, dual-frequency, triple-frequency or quad-frequency three-dimensional ground penetrating radar equipment.

[0064] The antenna array modules adopt the same modular structure design, with dimensions of 1020mm (length) × 520mm (width) × 200mm (height) and a weight of no more than 15kg, making them easy for a single person to carry and operate. The outer shell is made of high-strength engineering plastic, providing waterproof, dustproof, and shockproof protection, with an IP65 protection rating.

[0065] The combined interface module is installed on the outside of the antenna array module and consists of two parts: a mechanical connection structure and an electrical connection interface. The mechanical connection adopts a quick-release snap-fit ​​design, which can complete the combination or separation of the two housings within 10 seconds; the electrical connection uses high-density waterproof connectors to achieve reliable transmission of power, control signals and data signals.

[0066] Each frequency band antenna array module is equipped with the following functional modules: a transmitting module, a receiving module, a control and signal sampling module, a power management module, and a communication interface module.

[0067] The transmitting module contains at least six transmitters and transmitting antennas, enabling six transmission channels. The transmission frequency can be customized at the factory according to user requirements, with a selectable frequency range covering 50MHz-2.5GHz.

[0068] The receiving module is configured with at least seven receivers and receiving antennas, which are staggered with the transmitting antennas to receive echo signals from two adjacent transmitting antennas. The receiving module employs a low-noise amplifier and a high dynamic range ADC to ensure effective capture of weak echo signals.

[0069] The control and signal sampling module integrates an FPGA signal processing unit and an ARM control unit, and is responsible for functions such as transmission timing control, data acquisition, preprocessing and data transmission. The module has a built-in large-capacity memory that can store no less than 8 hours of detection data. At the same time, it connects with the electrical interface in the combined interface module to realize the hardware interface connection between the antenna array module and the distributed main control system.

[0070] The power management module has a built-in rechargeable lithium battery pack with a capacity of no less than 9Ah, supporting continuous operation for more than 8 hours in a single casing. The module features intelligent charge and discharge management, power monitoring, and low battery alarm functions.

[0071] The communication interface module provides gigabit Ethernet network support via wired or wireless means to communicate with the distributed master control system and upload echo data.

[0072] When high-precision deep exploration is required, the band 1 antenna array module, band 2 antenna array module, band 3 antenna array module, and band 4 antenna array module can be physically connected through a combined interface module.

[0073] The combined four-frequency system operates as follows: Assuming band 1 is 200MHz, band 2 is 400MHz, band 3 is 900MHz, and band 4 is 1200MHz, the four frequencies work in tandem as follows: The 200MHz channel handles coarse detection at depths of 3-10 meters, providing an overview of target distribution over a wide depth range. The 400MHz channel handles medium-resolution detection at depths of 1.5-5 meters, providing preliminary and precise location of deep targets. The 900MHz channel handles high-resolution detection at shallow to intermediate depths of 0.5-2 meters, obtaining detailed information on intermediate targets. The 1200MHz channel handles high-resolution detection at shallow depths of 0.1-1 meters, accurately identifying surface structures and small targets. After data fusion processing, the data from the four channels generates a complete three-dimensional detection image from the surface to depth.

[0074] The three-dimensional data processing flow in this embodiment includes the following steps: S1: Multi-channel data acquisition, synchronous acquisition of raw echo data from each frequency channel, recording auxiliary information such as time, position, and attitude.

[0075] S2: Preprocessing and filtering, performing preprocessing on the raw data such as bandpass filtering, gain compensation, and noise suppression.

[0076] S3: Multi-frequency data fusion, which integrates detection data from different frequencies to combine the advantages of each frequency.

[0077] S4: 3D imaging reconstruction, using migration imaging algorithm or tomography algorithm to generate 3D data volume.

[0078] S5: Target recognition and annotation, which performs target recognition, classification and 3D annotation on 3D data volumes.

[0079] S6: Visualization output, generating various visualization results such as 3D images, cross-sectional views, and slice views.

[0080] This embodiment breaks through the limitations of traditional fixed-frequency radar configurations by employing four independently packaged frequency modules, including low-frequency, medium-frequency, high-frequency, and very-high-frequency modules, achieving plug-and-play functionality through standardized mechanical and electrical interfaces. Users can flexibly select, replace, or reconfigure frequency modules according to the detection mission, achieving multi-purpose functionality and on-demand reconfiguration. Breaking away from the traditional integrated model, each frequency module is designed as an independent, lightweight unit. It supports handheld operation with a single module, vehicle-mounted operation with multiple modules, or multi-person collaborative module carrying into complex terrain, fundamentally resolving the contradiction between high performance and portability. A multi-channel array antenna design, combined with high-precision BeiDou / GPS positioning data, enables simultaneous acquisition by multiple modules. Through 3D reconstruction algorithms, it accurately reconstructs the spatial morphology, orientation, tilt angle, and volume of underground anomalies, achieving a technological leap from 2D profiling to 3D stereoscopic detection. The system can automatically recommend the optimal frequency combination scheme based on preset detection depth and resolution requirements; or dynamically adjust the operating frequency and acquisition parameters based on real-time echo signal quality to ensure data quality under complex geological conditions.

[0081] In summary, the modular multi-frequency reconfigurable 3D radar detection system and method of this invention flexibly disassembles and reassembles multiple independently frequency-selectable antenna array modules through standardized combination interfaces. A distributed main control module enables collaborative control and data fusion between modules, thereby constructing a modular detection architecture with configurable frequencies, variable form, and adjustable deployment. This architecture not only supports switching between various operating modes, from single-module handheld fine detection to multi-module vehicle-mounted rapid surveys, but also allows for precise adjustment of the relative positions and detection angles between modules via a multi-axis robotic arm, ensuring strict synchronization and consistency of multi-frequency data in the spatiotemporal dimension. Furthermore, combined with high-precision positioning and 3D reconstruction algorithms, it generates high-precision 3D images of underground targets. The method, through modular and modular design, overcomes the limitations of fixed frequencies and rigid structures in traditional radar systems, achieving a balance between detection depth and resolution across multiple scenarios. It significantly improves the portability, scalability, and environmental adaptability of the equipment. Simultaneously, the multi-channel synchronous acquisition and 3D imaging capabilities enhance the accuracy and completeness of underground space information acquisition, effectively solving the problems of poor adaptability, low utilization, and operational limitations of existing equipment in complex detection tasks.

[0082] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. When implemented in hardware, it can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the desired tasks. The programs or code segments can be stored in a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave.

[0083] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0084] In this invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or in place of features of other embodiments.

[0085] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. For those skilled in the art, various modifications and variations can be made to the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A split-type multi-frequency reconfigurable three-dimensional radar detection system, characterized in that, The system includes: Multiple antenna array modules are deployed in a distributed manner, and each antenna array module selects to operate at multiple preset operating frequencies; The combined interface module includes a mechanical connection structure and an electrical connection interface. The mechanical connection structure is used for detachably installing the antenna array module and deploying it in one of a variety of preset relative positions. The electrical connection interface provides the antenna array module with power, control signal, and data signal transmission channels. A positioning module that performs positioning based on one or more positioning signals; The distributed master control module is connected to the antenna array module through the electrical connection interface. According to the task requirements, it selects one or more of the antenna array modules to perform detection, and controls the antenna array modules to work independently or collaboratively according to the preset operating frequency and preset relative position matched to the task requirements. It collects the radar detection data returned by the antenna array modules and the positioning data returned by the positioning module to reconstruct a three-dimensional detection image. The communication interface module is used to communicate with the distributed main control module to acquire and transmit the three-dimensional detection image to the outside world. The power management module is used to supply power to the antenna array module, the combined interface module, the positioning module, the distributed main control module, and the communication interface module.

2. The split-type multi-frequency reconfigurable three-dimensional radar detection system according to claim 1, characterized in that, The antenna array module adopts MIMO array antenna elements, including multiple independent transmit and receive channels. Each transmit channel includes a digitally controlled attenuator, a power amplifier, a switchable cavity bandpass filter, a standing wave detection circuit, and a transmit antenna, with a transmit frequency range covering 50MHz~2.5GHz. Each receive channel includes a limiter, a low-noise amplifier, an intermediate frequency filter, an ADC sampling circuit, and a receive antenna. The antenna array module also integrates an FPGA signal processing unit and an ARM control unit. The FPGA signal processing unit is used to perform transmission timing control and to perform ADC data acquisition, bandpass filtering, gain compensation, noise suppression, channel calibration and buffering on the raw echo data. The ARM control unit is used to perform status monitoring and communication with the distributed main control module; The operating frequencies of the antenna array module include: a 200MHz frequency for detecting depths of 3 to 10 meters, a 400MHz frequency for detecting depths of 1.5 to 5 meters, a 900MHz frequency for detecting depths of 0.5 to 2 meters, and a 1200MHz frequency for detecting depths of 0.1 to 1 meter.

3. The split-type multi-frequency reconfigurable three-dimensional radar detection system according to claim 1, characterized in that, The mechanical connection structure is a multi-axis robotic arm, which is fixedly connected to the antenna array module via quick-release components. The multi-axis robotic arm adjusts the relative position and detection angle of the antenna array module in response to the control signals of the distributed main control module.

4. The split-type multi-frequency reconfigurable three-dimensional radar detection system according to claim 3, characterized in that, In a collaborative work scenario, the multi-axis robotic arm, in response to the control signal of the distributed main control module, deploys the antenna array modules selected based on a task requirement to the same horizontal detection surface. The elevation difference between each antenna array module is within 1 / 4 of the wavelength of the medium corresponding to the highest operating frequency. Furthermore, the central axis of each antenna array module coincides with the direction of the survey line. In an independent working scenario, the multi-axis robotic arm, in response to the control signals of the distributed main control module, independently deploys the antenna array modules selected based on multiple task requirements according to their corresponding detection positions and angles.

5. The split-type multi-frequency reconfigurable three-dimensional radar detection system according to claim 1, characterized in that, The positioning module includes a BeiDou positioning module, an RTK positioning module, and an IMU inertial measurement unit; The power management module deploys an independent power supply within each of the antenna array modules for power supply, and / or provides centralized power supply through a power sharing bus.

6. The split-type multi-frequency reconfigurable three-dimensional radar detection system according to claim 1, characterized in that, The distributed master control module includes: The global synchronization control unit has a built-in Beidou-docked thermostatic crystal oscillator to generate a reference clock and distribute it to the antenna array module through a synchronization clock bus to achieve time synchronization. The data processing and storage unit, equipped with a GPU parallel acceleration unit, is used to fuse the raw echo data collected by each of the antenna array modules and reconstruct the three-dimensional detection image. The interactive visualization unit allows users to input control commands and preview the three-dimensional detection image based on a touch-screen human-computer interaction interface.

7. The split-type multi-frequency reconfigurable three-dimensional radar detection system according to claim 1, characterized in that, The communication interface module connects to the cloud server via a preset link and is used to forward the raw echo data and the three-dimensional detection image to the cloud server for remote access, or to forward task requirements based on the cloud server to achieve remote control.

8. A detection method based on a split-type multi-frequency reconfigurable three-dimensional radar, characterized in that, The method is executed based on the distributed master control module in the split-type multi-frequency reconfigurable three-dimensional radar detection system according to any one of claims 1 to 7, and the method includes the following steps: In response to the requirements of the detection mission, a detection configuration scheme is selected and distributed to the combined interface module and the antenna array module, and configuration completion feedback is received. In a collaborative working scenario, the detection configuration scheme includes multiple selected antenna array modules and their relative positions, transmission parameters, and reception parameters. In an independent working scenario, the detection configuration scheme includes multiple selected antenna array modules and their independent deployment positions, detection angles, transmission parameters, and reception parameters. Perform multi-channel data acquisition, synchronously acquire the raw echo data of the antenna array module currently participating in the detection, the positioning data of the positioning module, and record the timestamp and the attitude information of the antenna array module; After preprocessing and filtering the multi-channel data, the original echo data of multiple frequencies collected by each antenna array module are fused in a collaborative working scenario, and three-dimensional imaging reconstruction is performed to obtain a collaborative three-dimensional detection image; or in an independent working scenario, the original echo data collected by each antenna array module are separately subjected to three-dimensional imaging reconstruction to obtain an independent three-dimensional detection image. The collaborative 3D detection image or the independent 3D detection image is used to identify, classify, and label targets, and then the results are visualized.

9. The detection method based on a split-type multi-frequency reconfigurable three-dimensional radar as described in requirement 8 of the preceding wheel, characterized in that, The transmission parameters include the operating frequency, transmission power, pulse width, pulse repetition frequency, and transmission timing of the antenna array module; The receiving parameters include receiving gain, sampling rate, sampling duration, number of superpositions, and filtering parameters; The operating frequencies include: a 200MHz frequency for detecting depths of 3 to 10 meters, a 400MHz frequency for detecting depths of 1.5 to 5 meters, a 900MHz frequency for detecting depths of 0.5 to 2 meters, and a 1200MHz frequency for detecting depths of 0.1 to 1 meter.

10. The detection method based on a split-type multi-frequency reconfigurable three-dimensional radar as described in requirement 9 of the previous wheel, characterized in that, In response to the requirements of the detection mission, before selecting a detection configuration scheme, the method further includes: The system performs a level-one self-check of the local functions of the distributed master control module, a level-two self-check of the connection status between modules in the system, and a level-three self-check of the functions of each module in the system. The system summarizes the self-test results, classifies faulty devices according to their severity, issues alarms for minor faults, automatically isolates serious faults, updates the available hardware topology of the system, and sends a self-test report and fault prompts to the user terminal.

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