Wide adaptation domain observation system based on multi-offset ground penetrating radar and data processing method

Abstract

The problems that a traditional ground penetrating radar is insufficient in detection precision, fuzzy in imaging, poor in operation flexibility, poor in adaptability and the like in a complex underground environment are solved. The invention discloses a wide-adaptation-domain observation system based on a multi-offset ground penetrating radar and a data processing method, the arrangement mode of an antenna array is adjusted in real time through hardware, the detection performance is optimized, and high-precision imaging in a complex scene is achieved by combining speed analysis-offset processing collaborative optimization. The method has the advantages of high adaptability, flexibility in operation, high-resolution imaging and the like, is suitable for complex scenes such as urban underground pipeline positioning, geological disaster early warning and tunnel advanced detection, and provides reliable technical support for underground space safety detection.

Description

Technical Field

[0001] The present invention relates to the technical field of ground penetrating radar detection, and in particular to a wide adaptation domain observation system and data processing method based on a multi-offset ground penetrating radar. By dynamically adjusting the arrangement of the antenna array and combining the data processing method of multi-offset data, the high-resolution imaging ability of underground targets under complex geological conditions is significantly improved. Background Art

[0002] As a geophysical detection technology based on the propagation mechanism of high-frequency electromagnetic waves, ground penetrating radar can realize the efficient and non-destructive detection of underground targets by transmitting pulse signals and receiving the reflected waves and scattered waves of underground media. It plays an important role in the fields of urban underground space detection, geological disaster prevention and control, and tunnel advance detection. However, the technical bottlenecks in the hardware architecture design and data processing method of traditional ground penetrating radar systems are difficult to meet the refined detection requirements under complex geological conditions.

[0003] At the hardware design level, existing ground penetrating radar systems generally adopt fixed antenna arrays, resulting in their detection performance being limited by the preset parameter system. When the depth and size of the detection target vary greatly, the fixed antenna spacing is difficult to balance the requirements of high resolution in the shallow part and strong penetration in the deep part. In the case of inhomogeneous media or the presence of interference objects, it is easy to cause signal distortion, noise increase or target missing detection. For example, in complex application scenarios such as urban underground space detection, densely distributed metal pipelines, concrete structures and geological faults form multiple reflection interfaces, and the radar system with fixed parameters cannot adjust the transmitted waveform and receiving array, resulting in the mixing of target responses and clutter components in the echo signal. In addition, the traditional system lacks a real-time parameter feedback mechanism and cannot dynamically adjust the transmitted waveform parameters and receiving array configuration according to the spatial variation characteristics of geoelectric parameters, which is prone to waveform oscillation distortion and false anomaly responses.

[0004] At the data processing level, conventional velocity analysis relies on common midpoint gather stacking technology to estimate the equivalent root mean square velocity. However, this method does not fully consider the wave field propagation direction information and ray path anisotropy characteristics contained in multi-offset data, resulting in insufficient accuracy of the velocity model. Moreover, the accuracy of the velocity parameter directly determines the reliability of target spatial positioning. The migration algorithm has residual diffraction noise in the migration correction of complex structures (such as inclined interfaces and small-scale anomalies), and the imaging quality deteriorates significantly in the medium mutation area. The above defects make it difficult for traditional methods to meet the engineering requirements in terms of target positioning accuracy and imaging credibility in complex scenarios.

[0005] In view of the above technical bottlenecks, it is urgent to construct a ground penetrating radar technology system with a wide adaptation range in which the hardware system and data processing algorithm work together. At the hardware architecture level, an antenna array system is designed that can combine multi-offset observation data to improve imaging robustness, thereby enhancing the flexibility and adaptability of detection. This hardware system can optimize the antenna arrangement in real time according to factors such as the electromagnetic characteristics of the underground medium, target depth, and size, thus significantly improving the detection accuracy and efficiency and being able to effectively handle detection tasks in complex environments. At the data processing level, based on the wave field propagation direction and ray path characteristics of multi-offset data, the equivalent velocity model of the medium is inverted, and the dielectric constant distribution is extracted simultaneously, improving the data signal-to-noise ratio and result credibility. The migration optimization algorithm for inverting the dielectric constant based on the velocity spectrum realizes the migration of diffracted waves and effectively improves the positioning accuracy through time-depth conversion. The data processing method and the dynamically adjusted hardware system work together to significantly improve the authenticity and accuracy of imaging, promote the application of ground penetrating radar technology in more complex scenarios, and provide reliable technical support for fields such as geological exploration, engineering inspection, and underground target positioning. Summary of the Invention

[0006] The purpose of the present invention is to provide a wide adaptation range observation system and data processing method based on a multi-offset ground penetrating radar. By adjusting the arrangement mode of the antenna array in real time, the detection performance is optimized to adapt to different detection scenarios and target requirements. The imaging accuracy is improved through the supporting data processing method.

[0007] The technical solution of the present invention is as follows: A wide adaptation range observation system and data processing method based on a multi-offset ground penetrating radar. The hardware system includes a ground penetrating radar host, a calibration board, a slide rail, a transmitting antenna, four receiving antennas, five drivers, and connecting wires. The data processing method includes velocity analysis and migration processing, significantly improving the authenticity and accuracy of imaging.

[0008] Further, the ground penetrating radar host includes a control unit, a signal processing unit, and a display unit.

[0009] Further, the control unit is used to adjust the receiving parameters and antenna arrangement of the transmitting antenna and the receiving antenna, and control the movement of the driver to adjust the distance between the antennas.

[0010] Further, the signal processing unit is used to preprocess the received radar signals, including background noise removal, gain, filtering, etc. Through preprocessing, the electromagnetic characteristics of the underground medium can be truly reflected, and a high-resolution underground medium distribution image is generated, laying a foundation for subsequent data processing.

[0011] Further, the display unit supports touch screen operation, and the detection results can be viewed in real time through the interface, and the antenna arrangement can be adjusted.

[0012] Furthermore, the length of the slide rail is 2 m, and the accuracy of the scale board is ±1 mm, which is used for antenna positioning and calibration.

[0013] Furthermore, the transmitting antenna and the receiving antenna are connected by a connecting wire, and are horizontally moved on the slide rail through the drive on the antenna, with a moving accuracy of ±0.5 mm. The drive is controlled by the control unit, and can adjust the distance between the antennas according to the detection requirements, with a dynamic adjustment range of 10 - 50 cm. The antenna spacing can be dynamically adjusted according to the characteristics of the underground medium to improve the detection accuracy and signal penetration depth.

[0014] Furthermore, the antenna arrangement mode supports two antenna arrangement modes of one transmitting and one receiving and one transmitting and multiple receiving, which are selected by the control unit according to the detection requirements to select a suitable arrangement method.

[0015] Furthermore, the velocity analysis and migration processing transmit the data to the computer through the interface of the host, and are further analyzed and interpreted by software, which is more suitable for multi-offset ground penetrating radar data.

[0016] Furthermore, the velocity analysis combines the wave field propagation direction information of multi-offset data to invert the equivalent velocity model of the medium, and at the same time extracts the dielectric constant distribution. Using the velocity-dielectric constant relationship, the mapping relationship between the electromagnetic wave propagation time and depth is corrected, and the positioning deviation introduced by the homogeneous medium assumption is eliminated.

[0017] Furthermore, the migration processing is based on the migration algorithm of dielectric constant inversion, realizes the accurate migration of diffracted waves, corrects the spatial positions of inclined interfaces and small-scale anomalies, suppresses residual noise, and improves the imaging authenticity.

[0018] A wide-adaptability observation system and data processing method based on multi-offset ground penetrating radar provided by the present invention can adapt to the detection requirements under different depths and complex geological conditions by dynamically adjusting the antenna arrangement, improve the detection accuracy and signal penetration depth. According to the image result of the display unit, the antenna arrangement is optimized through the control unit to improve the detection efficiency. Subsequently, more accurate underground target information is obtained through the supporting velocity analysis and migration processing. Description of the Drawings

[0019] Figure 1 Schematic diagram of the hardware structure of the ground penetrating radar supporting dynamic adjustment of antenna arrangement

[0020] Figure 2 Schematic diagram of the host unit of the ground penetrating radar

[0021] Figure 3 Schematic diagram of antenna arrangement and corresponding observation system

[0022] Figure 4 Comparison diagram of single-shot single-receive and one transmitting and multiple receiving

[0023] Figure 5 It is the stratigraphic division map of the actual measurement work area

[0024] Figure 6 It is the ground penetrating radar velocity spectrum map with different minimum offset distances

[0025] Figure 7 It is the pipeline profile map and the pipeline offset result map

[0026] Explanation of the attached figure numbers

[0027] 1 is the main unit

[0028] 2 is the connecting wire

[0029] 3 is the transmitting antenna

[0030] 4 is the receiving antenna

[0031] 5 is the drive

[0032] 6 is the slide rail

[0033] 7 is the scale board Specific implementation manners

[0034] 1. Instrument connection and initialization settings:

[0035] Connect the ground penetrating radar main unit to the transmitting antenna and the receiving antenna through the connecting wire, as Figure 1 shown, to ensure the stability and real-time performance of signal transmission.

[0036] The main unit initializes the system through the control unit, and sets basic information such as the working frequency of the antenna, the antenna arrangement mode, the distance between antennas, and the sampling points.

[0037] Antenna arrangement mode: The antenna arrangement mode of one transmitting and one receiving or one transmitting and multiple receiving can be selected.

[0038] Antenna spacing setting: The control unit adjusts the positions of the transmitting antenna and the receiving antenna on the slide rail through the drive to accurately control the antenna spacing. The scale board makes it more intuitive to display.

[0039] Sampling point setting: According to the detection requirements, set the density and distribution of sampling points to ensure the integrity and resolution of detection data.

[0040] 2. Start measurement:

[0041] After completing the parameter settings, start the measurement through the control unit.

[0042] The transmitting antenna emits electromagnetic wave signals to the ground, and the receiving antenna receives the reflected wave signals and transmits the signals to the signal processing unit.

[0043] The signal processing unit preprocesses the received reflected wave signals, including filtering, denoising, and gain adjustment, to improve the signal quality.

[0044] After the measurement is completed, the final underground medium distribution image can be viewed through the display unit, and the detection results can be analyzed.

[0045] 3. Real-time display and adjustment:

[0046] The display unit displays the detection results in real time, including the profile image of the underground medium and the signal waveform.

[0047] According to the profile characteristics of the display unit, the parameters can be flexibly adjusted to meet the on-site working needs: (1) Adjust the antenna spacing: If the detection target is small or higher resolution is required, the antenna spacing can be reduced; if deeper underground media need to be detected, the antenna spacing can be increased, as Figure 3 shown; (2) Switch the antenna arrangement mode: According to the detection requirements, different antenna arrangement modes can be switched. For example, in complex geological conditions, the one-shot four-receive mode can be adopted to improve the detection efficiency, as Figure 4 shown; (3) Optimize the sampling points: According to the real-time profile image, the sampling point density can be increased or decreased to balance the detection accuracy and the measurement speed.

[0048] 4. Data saving:

[0049] After the measurement is completed, the final underground medium distribution image can be viewed through the display unit, and the detection results can be analyzed.

[0050] The detection data can be saved to the built-in memory of the host or an external storage device for subsequent processing and report generation.

[0051] The data can also be transmitted to a computer through the interface of the host and further analyzed and interpreted using professional software.

[0052] 5. Data processing:

[0053] The measured data is preprocessed by removing the direct wave, background denoising, gain, etc., to make the deep signals clearer and improve the signal quality.

[0054] Common midpoint gather extraction processing is performed on the original wavefield record; then, the velocity spectrum analysis method is used to perform velocity scanning on the CMP gather, construct the stacking velocity spectrum, and extract the optimal stacking velocity parameters; on this basis, layer velocity recursive calculation is performed through the Dix formula, and finally a velocity-depth model of the layered medium is established to realize the quantitative inversion of the formation interface thickness and physical property parameters.

[0055] Using the inverted dielectric parameters as input conditions, the Kirchhoff integral migration algorithm is used to perform wave equation reverse time migration calculation on radar data, thereby reconstructing the spatial wave impedance interface of the underground pipeline and generating a depth-domain positioning profile with clear physical meaning. Through the migration imaging mechanism constrained by medium parameters, this method effectively solves the positioning distortion problem caused by velocity assumption deviation in the traditional time-depth conversion method.

[0056] 5. Application examples:

[0057] Controlling the minimum offset to be 0.4m, 0.6m, 0.8m, 1.0m, using a maximum coverage of 6 times, and a 400MHz antenna, four groups of field measurement experiments are designed. The stratification of the formation in the field measurement area is as Figure 5 shown.

[0058] Velocity analysis of the collected common midpoint data shows Figure 6 , and analysis Figure 6 shows that: when the minimum offset is 0.4m and 0.6m, the distance between the transmitting and receiving antennas is small, the time difference of electromagnetic wave propagation between layers is small, and the underground stratification is not obvious. When the minimum offset is 0.8m and 1.0m, the obvious underground medium stratification can be seen. As the offset increases, the stratification of the formation becomes clearer, which is more conducive to the identification of stratified media. However, when the offset is too large, more signals carried by the deep layer are received, and the deep energy is abnormal, which is not conducive to the picking of the velocity spectrum.

[0059] The ground penetrating radar data of the underground pipeline has been preprocessed, and the inversion values of the layer velocity and layer thickness of the stratified medium above the pipeline have been obtained through the velocity analysis method. The cumulative layer thickness gives the pipeline burial depth of about 0.847m, and the actual pipeline burial position is about 0.8m. Calculating the relative dielectric constant of the underground medium based on the layer velocity information is the key parameter for Kirchhoff migration. It is calculated that the relative dielectric constant of the background medium around the pipeline is about 16. Migration processing of the underground pipeline profile data gives Figure 7 . According to Figure 7 shown, there is a hyperbolic response feature at the abscissa of 1.5m in the profile, and it is judged that there is an underground pipeline there. Although the stratification of the medium above the pipeline is not obvious after data preprocessing, the general trend can still be seen. And because there are many stones in the shallow medium, there are many small hyperbolic features in the echo above the pipeline. The migration imaging result is related to the measured response feature. From 0 - 50cm, multiple focal points are formed by migration affected by shallow stones, and their trend is roughly the same as the detection profile. There is a single focal point at a burial depth of about 0.8m. Combining with the profile analysis, it should be a pipeline anomaly. The top and bottom interfaces of the pipeline are offset as a high value and a low value, and the pipeline burial depth is also close to the actual burial depth, meeting the requirements of pipeline positioning.

[0060] Matters not covered by this invention are well-known technologies.

[0061] The above embodiments are only used to illustrate the technical concept and features of the present invention, and the purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. However, the protection scope of the present invention cannot be limited thereby. Any equivalent changes or modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.

Claims

1. A wide adaptation domain observation system and data processing method based on multi-offset ground penetrating radar, characterized in that: The hardware system works in cooperation with the data processing algorithm to achieve high-precision imaging in complex scenarios by dynamically adjusting the arrangement of the antenna array and processing multi-offset data.

2. The hardware system according to claim 1 includes: The ground penetrating radar host, calibration board (accuracy ±1mm), slide rail (length 2m), a tunable transmitting antenna, four receiving antennas, five drivers (moving accuracy ±0.5mm), and connecting wires.

3. The ground penetrating radar host according to claim 2 includes a control unit, a signal processing unit, and a display unit. The transmitting antenna and the receiving antenna according to claim 2 are connected by connecting wires and are horizontally moved on the slide rail under the control of the driver. The calibration board is used for antenna positioning and calibration. The antenna spacing can be dynamically adjusted (10 - 50cm) to adapt to the electromagnetic characteristics of the underground medium and the depth of the detection target.

4. The control unit according to claim 3 is used to adjust the receiving parameters and the antenna arrangement of the transmitting antenna and the receiving antenna, and control the movement of the driver to adjust the distance between the antennas.

5. The signal processing unit according to claim 3 is used to preprocess the received radar signals, including background denoising, gain, filtering, etc. Through preprocessing, it can truly reflect the electromagnetic characteristics of the underground medium, generate a high-resolution image of the underground medium distribution, and lay a foundation for subsequent data processing.

6. The display unit according to claim 3 supports touch screen operation, and can view the detection results in real time through the interface and adjust the antenna arrangement.

7. The data processing algorithm according to claim 1 is more suitable for the velocity analysis and migration processing of multi-offset ground penetrating radar data.

8. The velocity analysis according to claim 7 combines the wave field propagation direction information of multi-offset data to invert the equivalent velocity model of the medium, and at the same time extracts the dielectric constant distribution. Using the velocity-dielectric constant relationship, it corrects the mapping relationship between the electromagnetic wave propagation time and the depth, and eliminates the positioning deviation introduced by the homogeneous medium assumption.

9. The migration processing according to claim 7 is based on the migration algorithm of dielectric constant inversion, realizes the accurate migration of diffracted waves, corrects the spatial positions of inclined interfaces and small-scale anomalies, suppresses residual noise, and improves the authenticity of imaging.

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