Buried object discrimination device and method

Abstract

To provide a buried object discrimination device and method capable of discriminating a buried object with high reliability.SOLUTION: A buried object discrimination device is configured to: input underground survey data given from outside; estimate a dielectric constant of an underground medium based upon the input underground survey data; execute opening composite processing on the underground survey data based upon the estimated dielectric constant; execute discrimination processing to discriminate a buried object based upon opening composite survey data obtained by performing the opening composite processing on the underground survey data and the underground survey data; and output information, associated with the buried object, obtained through the discrimination processing, as buried object information.SELECTED DRAWING: Figure 1A

Description

[Technical field]

[0001] The present invention relates to a buried object discrimination device and method, and is suitable for application to a buried object discrimination device that analyzes underground exploration data acquired by an underground radar device to discriminate underground buried objects (hereinafter simply referred to as buried objects). [Background technology]

[0002] Conventionally, when erecting electric poles or removing electric poles, surveys of buried objects in the construction area are conducted. In this case, surveys by test excavation are expensive and there is a possibility that buried objects may be damaged during excavation. Therefore, underground radar devices are used to survey buried objects as a low-cost and non-destructive survey method.

[0003] Electromagnetic waves emitted from an underground radar device usually propagate underground at a certain radiation angle. Therefore, the reflected waves received by the underground radar device include not only those from buried objects located directly below the underground radar device, but also those from buried objects located in the surrounding area. Therefore, the data obtained for multiple points on the ground surface during the exploration of buried objects contains distorted images of the reflected images from the buried objects.

[0004] In manual buried object surveys, underground exploration data acquired by a ground-penetrating radar device is converted into images, and the characteristic images that represent signals originating from the buried objects are then interpreted by the human eye to survey the buried objects.

[0005] Non-Patent Document 2 discloses a technique for estimating buried depth and electromagnetic wave speed in a medium from underground exploration data. In this technique, a value is estimated so that the theoretical arrival time fits to a clear reflection image in the underground exploration data while changing the speed of the electromagnetic wave in the medium and the buried object depth. Furthermore, Non-Patent Document 3 discloses a technique for correcting errors due to the angle of the side line crossing a buried pipe.

[0006] Non-Patent Document 1 discloses a synthetic aperture processing technology that uses data acquired at multiple points on the ground's surface. The synthetic aperture processing technology is a technology that synthesizes reflected signals from the same buried object at the reflection point based on parameters such as the relative positions of the transmitting antenna and receiving antenna of the underground radar device, the sampling interval during exploration, and the relative dielectric constant of the ground. This makes it possible to correct the characteristic image distortion mentioned above and generate synthetic aperture exploration data with an improved signal-to-noise ratio. Distortion correction is useful for improving the accuracy of determining the position and size of buried objects.

[0007] Non-Patent Document 4 discloses a technique for applying the above-mentioned synthetic aperture processing technique to obtain the dielectric constant underground. The image corrected by synthetic aperture processing converges to the reflection point, but if the parameters used in the calculation, such as the dielectric constant, contain errors, the image will remain distorted. The results of synthetic aperture processing are evaluated using a numerical index according to the degree of convergence, and the dielectric constant at which the evaluation result is maximized is searched for, thereby appropriately obtaining the average dielectric constant around the image.

[0008] Patent Document 1 discloses a method for estimating the depth of a plurality of buried objects in non-uniform soil. In non-uniform soil, the dielectric constant varies depending on the location due to the difference in soil composition. In this technology, migration processing, which is a type of aperture synthesis processing, is performed on underground exploration data while changing the dielectric constant within a certain range. The coordinate value and dielectric constant at which the migration result is maximized are regarded as the average dielectric constant at the coordinates and extracted. In addition, the position of the buried object is detected by a buried object detector that has been trained in advance. The buried object detector applies a machine learning method used for image recognition and trains. The migration result is referred to at the peripheral coordinates of the detected buried object to determine the corresponding dielectric constant. The buried object depth is then estimated from the buried object coordinates and dielectric constant.

[0009] In addition, Patent Document 2 discloses a technique for automatically identifying buried objects by using a buried object learning model based on a subsurface exploration image obtained by a ground penetrating radar device. The buried object learning model is an AI (Artificial Intelligence) model constituted by a neural network that has learned subsurface exploration data to be detected. This technique is particularly characterized by generating a subsurface exploration image from subsurface exploration data given from the outside and aperture synthesis exploration data subjected to aperture synthesis processing, and identifying buried objects based on the generated subsurface exploration image.

Prior Art Documents

Patent Documents

[0010]

Patent Document 1

Patent Document 2

Non-Patent Documents

[0011]

Non-Patent Document 1

Non-Patent Document 2

Non-Patent Document 3

[0012] According to the invention disclosed in Patent Document 2, highly accurate buried object identification can be achieved by inputting synthetic aperture processing data in addition to underground exploration data, generating an integrated image, and then inputting the image to an identification device. This is because high-quality aperture processing data based on appropriate parameters is expected to correct the distortion of the reflected image of the underground exploration data and improve the signal-to-noise ratio. However, since the generation of synthetic aperture processing data is performed outside the system and is not connected to the buried object identification unit, there is a possibility that external synthetic aperture processing data that does not meet the input specifications of the buried object identification unit may be generated, which causes a problem that the data cannot be input to the buried object identification unit together with the underground exploration data.

[0013] In addition, as described above, the synthetic aperture process requires device-specific parameters such as the positional relationship between the transmitting antenna and the receiving antenna of the underground radar device, and the dielectric constant of the soil. Therefore, the synthetic aperture process performed outside the system is necessarily performed independently for each underground radar device and each exploration area. Therefore, when the synthetic aperture process is performed in an external system, it is not easy to use the synthetic aperture data in the same system.

[0014] In this regard, if the format of the data input to the identifier that identifies buried objects can be guaranteed within the device, aperture synthesis processing data can be reliably input to the identifier, the identification performance of buried objects can be improved, and buried objects can be discriminated with high reliability.

[0015] In the invention disclosed in Patent Document 1, underground exploration data is subjected to aperture synthesis processing in advance using multiple relative dielectric constants, and the depth of the buried object is estimated by referring to the result of the processing at the position of the buried object detected by a separately prepared buried object detector.

[0016] However, after the buried object detector finishes detecting the buried object positions, the relative dielectric constant candidates at each buried object position are identified. Therefore, there is a problem that it is not possible to input synthetic aperture exploration data that has been subjected to aperture synthesis processing using an appropriate relative dielectric constant to the buried object detector. In addition, it is necessary to perform the synthetic aperture processing multiple times for the number of relative dielectric constants specified in advance, and there is a problem in balancing the calculation cost with the estimation resolution of the relative dielectric constant (and the depth of the buried object converted from it).

[0017] The present invention has been made in consideration of the above points, and proposes a buried object discrimination device and method for discriminating buried objects with high reliability. [Means for solving the problem]

[0018] In order to solve such problems, in the present invention, a buried object discrimination device that discriminates buried objects underground based on underground exploration data obtained by transmitting and receiving electromagnetic waves into the ground is provided with a dielectric constant estimation unit that estimates the dielectric constant of the underground medium based on the underground exploration data provided from outside and outputs an estimated dielectric constant, an aperture synthesis processing unit that uses the estimated dielectric constant to perform aperture synthesis processing on the underground exploration data and outputs aperture synthesis exploration data, and a buried object discrimination unit that performs identification processing to identify the buried object based on the aperture synthesis exploration data and the underground exploration data, and outputs information about the buried object as buried object information.

[0019] In addition, in the present invention, a buried object discrimination method is executed by a buried object discrimination device that discriminates buried objects underground based on underground exploration data obtained by transmitting and receiving electromagnetic waves underground, and includes a first step of inputting the underground exploration data provided from an external source, a second step of estimating the relative dielectric constant of the underground medium based on the input underground exploration data, a third step of performing aperture synthesis processing on the underground exploration data based on the estimated relative dielectric constant, a fourth step of performing an identification process to identify the buried object based on the aperture synthesis exploration data obtained by performing the aperture synthesis processing on the underground exploration data and the underground exploration data, and a fifth step of outputting information regarding the buried object obtained by the identification process as buried object information.

[0020] According to the buried object discrimination device and method of the present invention, a processing section that estimates the dielectric constant of the underground medium based on underground exploration data and a processing section that performs aperture synthesis processing on the same underground exploration data using the estimated dielectric constant of the underground medium are combined with a buried object identification processing section, so that the synthetic aperture exploration data can be reliably input to the buried object identification processing section, making it possible to increase the recognition rate of buried objects.Furthermore, it is possible to improve the detection rate of the buried object identification section that uses the results and reduce the rate of erroneous recognition.

[0021] Furthermore, in the present invention, the underground exploration data includes, as antenna structure information, information on the antenna structure of the underground radar device that generated the underground exploration data, and at least one of the dielectric constant estimation unit and the aperture synthesis processing unit estimates the dielectric constant based on a radar reflection formula corresponding to the antenna structure based on the antenna structure information included in the underground exploration data, among radar reflection formulas previously defined for each antenna structure, or performs aperture synthesis processing on the underground exploration data, and inputs it to the buried object identification unit. Here, the radar reflection formula is defined as a model that expresses the time it takes for an electromagnetic wave emitted from the underground radar device to be reflected by a buried object and received by a receiving antenna.

[0022] According to the buried object discrimination device of the present invention, the accuracy of the dielectric constant estimation by the dielectric constant estimation unit and the aperture synthesis processing by the aperture synthesis processing unit can be kept constant even for underground radar devices having different antenna structures, and the estimated or generated dielectric constant and synthetic aperture exploration data can be kept as homogeneous as possible for the buried object discrimination device.

[0023] Furthermore, in the present invention, the buried object discrimination device is provided with a depth conversion section. The buried object information output from the buried object discrimination section includes the position of the buried object on the time axis of the underground exploration data. The depth conversion section converts the position on the time axis into a depth representing the distance of the buried object from the ground surface based on the estimated relative dielectric constant estimated by the relative dielectric constant estimation section.

[0024] In addition, after the buried object identification process, the dielectric constant estimation unit re-estimates the dielectric constant based on the buried object information, and the depth conversion unit converts the depth of the buried object into a depth based on the re-estimated dielectric constant.

[0025] According to the buried object discrimination device of the present invention, the relative dielectric constant determined in advance for use in aperture synthesis processing can be reused within the device, and depth can be added to the buried object information output from the buried object discrimination device, allowing the user to intuitively confirm the depth position of the buried object.

[0026] Furthermore, in the present invention, the aperture synthesis processing unit re-executes the aperture synthesis processing based on an aperture synthesis processing re-execution flag input from the outside, utilizing the dielectric constant re-estimated by the dielectric constant estimation unit, the buried object identification unit re-executes the buried object identification processing based on the aperture synthesis exploration data obtained by re-executing the aperture synthesis processing by the aperture synthesis processing unit, and the depth conversion unit converts the depth of the buried object into the depth of the buried object based on the buried object information obtained by re-executing the buried object identification processing and the dielectric constant re-estimated by the dielectric constant estimation unit.

[0027] According to the buried object discrimination device of the present invention, it is possible to regenerate the synthetic aperture exploration data to be input to the buried object identification unit based on the high-level buried object identification results in the buried object identification unit. This improves the convergence and S / N of the synthetic aperture exploration data to be input to the buried object identification unit, thereby improving the buried object identification accuracy in the buried object identification unit.

[0028] Furthermore, in the present invention, a selection unit is provided having a function of determining whether or not to re-execute the aperture synthesis processing in the aperture processing unit, the buried object identification processing in the buried object identification unit, and the depth conversion processing in the depth conversion unit.

[0029] Since the identification results of buried objects using the synthetic aperture exploration data updated by regeneration as input may be updated, this identification result may be returned to the dielectric constant estimation unit, and the dielectric constant may be re-estimated in the dielectric constant estimation unit and the aperture synthesis processing in the synthetic aperture processing unit may be performed multiple times.

[0030] By doing so, the convergence and S / N of the synthetic aperture exploration data input to the buried object identification unit are improved, and the identification accuracy of the buried object identification unit is improved. In this process, the selection unit that determines whether or not the synthetic aperture process, the buried object identification process, or the depth conversion process needs to be performed again can automatically improve the reliability of buried object identification in the buried object discrimination device of the present invention, allowing it to be performed with even greater reliability. Effect of the Invention

[0031] According to the present invention, it is possible to realize a buried object discrimination device and method that can discriminate buried objects with high reliability. [Brief description of the drawings]

[0032] [Figure 1A] 1 is a block diagram showing a configuration of a buried object discrimination device according to claim 1. FIG. [Figure 1B] 1 is a block diagram showing a configuration of a buried object management system according to a first embodiment. [Diagram 2] FIG. 1A is a diagram for explaining underground exploration data, and FIG. 1B is a diagram for explaining aperture synthesis exploration data. [Diagram 3] FIG. 1 is a diagram for explaining three-dimensional underground exploration data. [Figure 4] The figures are provided for explaining the buried object identification process using a CNN model. (A) shows the relationship between the CNN model and input data, (B) shows the combination of underground exploration data and synthetic aperture exploration data, and (C) shows a method of using underground exploration data and synthetic aperture data for identification. [Diagram 5] 15 is a flowchart of a buried object discrimination method according to claim 14. [Figure 6] (A) is an example of buried object information for two-dimensional underground exploration data, and (B) is an example of buried object information for three-dimensional underground exploration data. [Figure 7] (A) is an example of buried object information with depth for two-dimensional underground exploration data, and (B) is an example of buried object information with depth for three-dimensional underground exploration data. [Figure 8] FIG. 14 is a block diagram of a buried object management system according to claim 13. [Figure 9] FIG. 11 is a diagram showing an example of a screen configuration of an underground exploration result screen according to the second embodiment. [Figure 10] FIG. 11 is a block diagram showing the configuration of a buried object management system according to a third embodiment. [Figure 11] 3 is a block diagram of a buried object discrimination device according to claim 2. [Figure 12]FIG. 13 is a diagram showing an example of a screen configuration of an underground exploration result screen according to the third embodiment. [Figure 13] 13 is a flowchart showing a procedure of buried object discrimination processing according to the fourth embodiment. [Figure 14] 4 is a block diagram showing a configuration of a buried object discrimination device according to claim 3. FIG. [Figure 15] FIG. 13 is a block diagram showing the configuration of a buried object management system according to a fourth embodiment. [Figure 16] FIG. 13(A) is a block diagram showing the configuration of a buried object discrimination device according to a fourth claim, and FIG. 13(B) is a block diagram showing the configuration of a selection unit according to the fourth claim. [Figure 17] FIG. 13 is a block diagram showing the configuration of a buried object management system according to a fifth embodiment. [Figure 18] 23 is a table showing an example of how the re-execution flag of the selection unit according to the fourth claim in the sixth embodiment is determined. [Figure 19] 6 is a block diagram showing a configuration of a selection unit according to claim 5. FIG. [Figure 20] FIG. 13(A) is a block diagram showing the configuration of a buried object discrimination device recited in claim 6, and FIG. 13(B) is a block diagram showing the configuration of a buried object learning model generation unit recited in claim 6. [Figure 21] FIG. 13 is a block diagram showing the configuration of a buried object management system according to a seventh embodiment. [Figure 22] 8 is a block diagram showing a configuration of a buried object learning model generating unit according to claim 7. FIG. [Diagram 23] 10 is a block diagram showing a configuration of a buried object discrimination device according to claim 8. FIG. [Figure 24] FIG. 13 is a block diagram showing the configuration of a buried object management system according to an eighth embodiment. [Diagram 25] 10 is a block diagram showing a configuration of a buried object discrimination device according to claim 9. FIG. [Figure 26] FIG. 13 is a block diagram showing the configuration of a buried object management system according to a ninth embodiment. [Figure 27] 11 is a block diagram showing a configuration of a buried object discrimination device according to claim 10. FIG. [Figure 28] FIG. 23 is a block diagram showing the configuration of a buried object management system in a tenth embodiment. [Figure 29] 1A to 1B are diagrams illustrating differences in radar reflection types due to differences in antenna structures. [Diagram 30] 12 is a block diagram showing a configuration of a buried object discrimination device according to claim 11. FIG. [Diagram 31] FIG. 23 is a block diagram showing the configuration of a buried object management system in an eleventh embodiment. [Figure 32A] 23 is a flowchart showing a procedure for a buried object determination process performed by a buried object determination device in an eleventh embodiment. [Figure 32B] 23 is a flowchart showing a procedure for a buried object determination process performed by a buried object determination device in an eleventh embodiment. [Diagram 33] 13 is a block diagram showing a configuration of a buried object learning model generating unit according to claim 12. FIG. [Diagram 34] FIG. 23 is a block diagram showing the configuration of a buried object management system according to a twelfth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0033] An embodiment of the present invention will now be described in detail with reference to the drawings.

[0034] (1) First embodiment (1-1) Configuration of the buried object management system according to this embodiment 1B, the buried object management system according to this embodiment is generally designated by reference numeral 1. This buried object management system 1 is equipped with a buried object discrimination device 2 and an information display device 3.

[0035] The buried object discrimination device 2 is composed of a general-purpose computer device equipped with information processing resources such as a CPU (Central Processing Unit) and memory. The buried object discrimination device 2 inputs underground exploration data D1 acquired by an underground radar device (not shown), discriminates the type, shape, position, size, etc. of the buried object based on the underground exploration data D1, and outputs the discrimination result to the information display device 3 as buried object information D2.

[0036] The information display device 3 is configured with a display device equipped with, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, etc. The information display device 3 generates a predetermined exploration result screen on which the buried object discrimination result is displayed based on the buried object information D2 provided from the buried object discrimination device 2, and displays the generated exploration result screen.

[0037] (1-2) Configuration of the buried object discrimination device according to this embodiment As shown in FIG. 1A, a buried object discrimination device 2 of this embodiment includes a relative dielectric constant estimation section 11, an aperture synthesis processing section 12, and a buried object discrimination section 13.

[0038] The dielectric constant estimation unit 11, the opening synthesis processing unit 12, and the buried object identification unit 13 are realized by the above-mentioned CPU provided in the buried object discrimination device 2 executing a program stored in the above-mentioned memory provided in the buried object discrimination device 2.

[0039] The underground exploration data D1 is data acquired by transmitting and receiving electromagnetic waves into the ground by the underground radar device, and includes intensity information and phase information of the received signal for the time interval between the transmission and reception of the electromagnetic waves.

[0040] Fig. 2(A) shows an example of such underground exploration data D1. In Fig. 2(A), the vertical axis represents the time (t) from when the underground radar device emits electromagnetic waves into the ground until the underground radar device receives the waves reflected from the ground, and the horizontal axis represents the distance (x) in the exploration advance direction (advance direction of the underground radar device). Brightness also represents signal strength. Signal strength may be a positive or negative value, or even an imaginary number.

[0041] In Figure 2(A), the underground exploration data D1 is shown as a two-dimensional image with vertical and horizontal axes, but for example, the underground exploration data D1 obtained by an array-type underground radar device equipped with multiple transmitting antennas and receiving antennas becomes three-dimensional data that includes multiple two-dimensional data shown in Figure 2(A).

[0042] As shown in FIG. 3, for example, three-dimensional data has a time (t) axis, an exploration direction (x) axis, and a vertical axis (Y) axis relative to the exploration direction.

[0043] The dielectric constant estimation unit 11 in Figures 1A and 1B is a functional unit that has the function of estimating the dielectric constant of an underground medium based on underground exploration data D1 input from the outside, and outputting the estimated dielectric constant E1 to the aperture synthesis processing unit 12.

[0044] The relative dielectric constant can be estimated by applying a fitting method disclosed in Non-Patent Document 2, for example, in which clear points (points with high signal strength) in an image based on underground exploration data D1 are extracted as reflection points in a buried object of the electromagnetic waves emitted from an underground radar device, and parameters are changed based on the coordinates of the extracted clear points (reflection points) and the underground exploration data D1 so that the theoretical arrival time fits the underground exploration data D1.

[0045] As a fitting method for changing parameters so as to fit the theoretical arrival time to the underground exploration data D1, for example, the fitting method disclosed in Non-Patent Document 3 can be applied.

[0046] If no clear reflection point is found in the underground exploration data D1, the dielectric constant estimation unit 11 may output a predetermined dielectric constant. In this case, as the "predetermined dielectric constant", a range of dielectric constants that can be realistically obtained by the soil and moisture that constitute most of the underground is usually given to the dielectric constant estimation unit 11 in advance. Since the dielectric constant varies depending on the location underground, multiple dielectric constants may be estimated in the underground exploration data D1, and in that case, the dielectric constant estimation unit 11 may output multiple estimated dielectric constants E1.

[0047] The aperture synthesis processing unit 12 is a functional unit having a function of performing a predetermined aperture synthesis processing on the input underground exploration data D1 using the estimated relative dielectric constant E1 of the underground medium provided by the relative dielectric constant estimation unit 11. The aperture synthesis processing unit 12 outputs the aperture synthesis exploration data D3 obtained by the aperture synthesis processing as shown in Fig. 2(B) to the buried object identification unit 13. When there are a plurality of estimated relative dielectric constants E1 provided by the relative dielectric constant estimation unit 11, statistical values ​​such as the average value, median value, maximum value, or minimum value of the estimated relative dielectric constants E1 may be calculated before use.

[0048] As an example of such an aperture synthesis process, it is possible to apply the technology described on pages 262 to 267 of Non-Patent Document 1. In addition, the predetermined migration process disclosed in Patent Document 1 is also a type of aperture synthesis process and can be applied.

[0049] Since electromagnetic waves emitted into the ground spread at a certain radiation angle, the receiving antenna also receives reflected waves from buried objects that are not located directly below. For this reason, the underground exploration data D1 is usually distorted. Since this distortion can be corrected by the synthetic aperture processing, it is useful for determining the horizontal position and depth position of buried objects, and by inputting the synthetic aperture exploration data D3 to the buried object identification unit 13, it is possible to obtain the effect of improving the identification accuracy of buried objects in the buried object identification unit 13.

[0050] Furthermore, when the aperture synthesis processing unit 12 is given the estimated relative dielectric constant E1 for each location estimated by the relative dielectric constant estimation unit 11, it may perform partial aperture synthesis processing for a predetermined data range including each location and output integrated data. At this time, if each data range overlaps, it may be possible to calculate a representative value such as an average value for the overlapping range and integrate them.

[0051] The buried object identification unit 13 is a functional unit having a function of extracting a reflected image originating from a buried object based on the input underground exploration data D1 and the synthetic aperture exploration data D3 provided from the aperture synthesis processing unit 12, and deriving buried object information D2 including information on the type, shape, position, size, etc. of the buried object. The buried object information D2 derived by the buried object identification unit 13 is output from the buried object discrimination device.

[0052] The buried object identification unit 13 may derive buried object information using a buried object learning model, which is a learning model for buried objects by AI, or may derive buried object information using a rule base or multidimensional clustering. Furthermore, the buried object identification unit 13 may derive buried object information D2 identified by multiple buried object learning models.

[0053] As an AI-based buried object learning model, for example, a Convolutional Neural Network (CNN) model can be used. Figure 4 shows an example of the configuration of a buried object identification unit using a CNN model.

[0054] The CNN model is shown in FIG. 4(A) and may include a convolutional layer and a pooling layer. In the convolutional layer, input data is convolved with a specified filter, and the resulting values ​​(feature map data) are output to the pooling layer. Activation using an activation function may be performed before the feature map data is output from the convolutional layer to the pooling layer. As the activation function, for example, a sigmoid function, a softmax function, or a ReLU (Rectified Linear Unit) may be applied.

[0055] The pooling layer is provided after the convolution layer, and reduces the amount of data by using a specified filter to output the feature map data input from the convolution layer. The maximum value or average value can be used, for example, to reduce the amount of data. In the CNN model, the fully connected layer is used in the output layer, and combines and outputs the feature map data. The Flatten function can be used to combine the feature map data.

[0056] In order to input the underground exploration data D1 and the synthetic aperture exploration data D3 to the CNN model, the underground exploration data D1 and the synthetic aperture exploration data D3 can be synthesized in advance by a synthesis processing unit to generate synthetic data D4, as shown in Fig. 4(B) . In this case, as a method of synthesizing the underground exploration data D1 and the synthetic aperture exploration data D3, for example, a method of taking the average value, linear sum, maximum value, minimum value, etc. of the data values ​​at each coordinate can be applied.

[0057] 4(C), the buried object identification unit 13 derives buried object information D21, D22 based on the underground exploration data D1 and the synthetic aperture exploration data D3 using each identification machine (CNN models A, B) prepared corresponding to the underground exploration data D1 and the synthetic aperture exploration data D3, respectively, and outputs the buried object information D21, D22 derived based on the underground exploration data D1 and the synthetic aperture exploration data D3, respectively, to a result integration unit. The result integration unit may select either or both of the buried object information D21, D22, or common information of the buried object information D21, D22, and output it as buried object information D2.

[0058] By preparing classifiers corresponding to the underground exploration data D1 and the synthetic aperture exploration data D3, respectively, it is possible to perform classification suited to the feature quantities possessed by the underground exploration data D1 and the synthetic aperture exploration data D3, and obtain buried object information D2 according to these features. Then, by mutually complementing each other's buried object information D2 based on the buried object information D2, it is possible to improve the recall rate and the matching rate of the output of the buried object identification unit 13.

[0059] The buried object information D2 derived by the buried object identification unit 13 is output to the information display device 3, and a specified exploration result screen is displayed on the information display device 3, showing information such as the type, shape, position, and size of the buried object contained in the buried object information D2.

[0060] An example of buried object information D2 displayed on the information display device 3 will be described with reference to Fig. 6. Fig. 6(A) is an example of buried object information for two-dimensional underground exploration data. In the buried object information D2, the position is represented by the position in the exploration proceeding direction and the time it takes for the underground radar device to receive the reflected wave underground. In the case of a point object, it may be represented by a single point, and in the case of a line object, it may be represented by a line segment connecting the start point and the end point. Fig. 6(B) is an example of buried object information for three-dimensional underground exploration data. In this case, the buried object information D2 also has a component in the vertical direction of the exploration proceeding direction.

[0061] FIG. 5 shows a buried object discrimination method in the buried object discrimination device 2 having such a configuration.

[0062] First, underground exploration data D1 is input (S1).

[0063] Next, the dielectric constant estimation unit 11 estimates an estimated dielectric constant E1 of the underground medium based on the input underground exploration data D1, and outputs the estimated dielectric constant E1 to the aperture synthesis processing unit 12 (S2). The aperture synthesis processing unit 12 also performs aperture synthesis processing on the input underground exploration data D1 using the estimated dielectric constant E1 provided by the dielectric constant estimation unit 11, and outputs the above-mentioned aperture synthesis exploration data D3 thus obtained to the buried object identification unit 13 (S3).

[0064] The buried object identification unit 13 identifies buried objects based on the input underground exploration data D1 and the aperture synthesis exploration data D3 provided from the aperture synthesis processing unit 12, and generates buried object information D2 including information such as the type, shape, position and / or size of the identified buried object (S4).

[0065] The buried object identifying section 13 then outputs the generated buried object information D2 (S5). In this manner, a buried object discrimination result is output based on the buried object information D2, and this series of operations in the buried object discrimination method is completed.

[0066] (1-3) Advantages of this embodiment If the relative dielectric constant used in the aperture synthesis process is not the correct value, as disclosed in the above-mentioned Patent Document 1, the image that should be collected is over-processed, causing distortion of the image. The image distortion causes the area where the buried object is likely to exist to appear to be wider, which causes the position accuracy of the identified buried object to be impaired. In addition, the buried object identification unit may erroneously detect the excessive distortion as a false image, which may cause overdetection. For this reason, if the buried object identification unit 13 uses the underground exploration data D1 that has been subjected to the synthetic aperture process without using the correct relative dielectric constant to identify the buried object, this will cause a loss of reliability of the buried object discrimination device.

[0067] In this regard, the buried object discrimination device 2 of this embodiment integrally includes a dielectric constant estimation unit 11 that estimates the dielectric constant of the underground medium based on the underground exploration data D1, and an aperture synthesis processing unit 12 that performs aperture synthesis processing on the same underground exploration data D1 using the estimated dielectric constant E1 estimated by the dielectric constant estimation unit 11, so that it is possible to ensure the reproducibility of the aperture synthesis processed underground exploration data D1 (aperture synthesis exploration data D3) input to the buried object discrimination unit 13. As a result, the buried object discrimination device 2 can improve the buried object discrimination performance in the buried object discrimination unit 13, and thus make it possible to discriminate buried objects with high reliability.

[0068] (2) Second embodiment 8, in which the same reference numerals are assigned to parts corresponding to those in Fig. 1A and B, shows a buried object management system 20 according to a second embodiment. This buried object management system 20 is configured similarly to the buried object management system 1 according to the first embodiment, except that a buried object visualization system 21 is connected to a buried object discrimination device 2 instead of the information display device 3.

[0069] The buried object visualization system 21 comprises a buried object information storage device 22, a map information storage device 23, and an information display device 24. The buried object information storage device 22 is composed of a large-capacity non-volatile storage device such as an external hard disk device. The buried object information storage device 22 sequentially stores and accumulates the buried object information D2 output from the buried object discrimination device 2.

[0070] The map information storage device 23 is also configured with a large capacity non-volatile storage device such as an external hard disk device, etc. The map information storage device 23 stores in advance at least map information of the search area.

[0071] The information display device 24 is composed of an information processing device equipped with a liquid crystal display, an organic EL display, etc. Based on information such as the type, shape, location and / or size of the buried object contained in the buried object information group D2A stored in the buried object information accumulation device 22 and the map information DM of the exploration area stored in the map information storage device 23, the information display device 24 generates and displays an underground exploration result screen 30 as shown in Fig. 9, which integrates these pieces of information.

[0072] The underground exploration result screen 30 is configured with a map display area 30A and a buried object information display area 30B. A map 30AA with an image 30AB of a buried object superimposed thereon is displayed in the map display area 30A, and a list 30BA showing the type, material and / or size of the buried object is displayed in the buried object information display area 30B.

[0073] According to the buried object management system 20 of this embodiment having the above-mentioned configuration, in addition to the effects obtained by the first embodiment, it is possible to obtain the effect that a buried object information group D2A based on underground exploration data D1 acquired at various locations and dates and times can be managed by a single buried object visualization system 21, and various information about buried objects based on the buried object information group D2A can be presented to the user in a visually easy-to-understand manner.

[0074] (3) Third embodiment Fig. 10, in which parts corresponding to those in Fig. 1B are given the same reference numerals, shows a buried object management system 40 according to a third embodiment. This buried object management system 40 differs greatly from the buried object management system 1 of the second embodiment in that a buried object discrimination device 41 according to claim 2 shown in Fig. 11 is provided with a depth conversion unit 42. The depth conversion unit 42 is a functional unit that is realized by the above-mentioned CPU included in the buried object discrimination device 41 executing a corresponding program stored in the above-mentioned memory included in the buried object discrimination device 41.

[0075] The depth conversion unit 42 is notified of the estimated dielectric constant E1 estimated by the dielectric constant estimation unit 11 by the dielectric constant estimation unit 11. The depth conversion unit 42 then refers to the estimated dielectric constant E1 based on information on the position of the buried object on the time axis included in the buried object information D2 provided by the buried object identification unit 13 (information on the time from when the underground radar device emits electromagnetic waves into the ground until the electromagnetic waves are reflected by the buried object and return to the underground radar device), calculates the distance of the buried object from the ground surface (hereinafter, this is called the depth or depth position), and outputs buried object information with depth D2' including the calculated depth information. The buried object information with depth D2' is output to the information display device 3, and a predetermined exploration result screen on which information such as the type, shape, position, and size of the buried object included in the buried object information with depth D2' is displayed on the information display device 3.

[0076] In this case, if there are multiple estimated relative dielectric constants E1, the depth conversion unit 42 uses a part of the estimated relative dielectric constant E1 estimated at a position closest to the position of the buried object included in the buried object information D2 of the buried object identified by the buried object identification unit 13.

[0077] Furthermore, as shown in FIG. 3, when a reaction (clear point) originating from a buried object appears in multiple two-dimensional cross sections in the underground exploration data D1 for one buried object, the dielectric constant estimation unit 43 may estimate a different dielectric constant for each cross section of the same buried object (estimate multiple dielectric constants for the same buried object).

[0078] In such a case, the depth conversion unit 42 may extract a range of the underground exploration data D1 in which it can be determined that the same buried object has been identified based on the buried object information D2 of the buried object identified by the buried object identification unit 13, and may extract multiple dielectric constants to be used for depth conversion from the estimated dielectric constant E1 within that range, and may adopt, for example, an average value of the extracted dielectric constants as the dielectric constant to be used for converting the buried object to a depth.

[0079] In addition, when the size of the buried object included in the buried object information D2 is equal to or larger than a specified size, the range of the underground exploration data D1 may be specified for each part of the buried object, and a representative value of the estimated dielectric constant E1 within the specified range may be calculated based on the dielectric constant estimated by the dielectric constant estimation unit 43 within the specified range, and the representative value may be used by the depth conversion unit 42.

[0080] Next, a method for converting the depth of a buried object in the depth conversion unit 42 will be described. As shown in Fig. 2(A), the underground exploration data D1 has at least an axis of the exploration progress direction (x direction in Fig. 2(A)) and an axis of the time direction (t direction in Fig. 2(A)). The time t here is the elapsed time from when the underground radar device emits electromagnetic waves into the ground to when the underground radar device receives the electromagnetic waves reflected underground.

[0081] For this reason, the buried object identification unit 13 usually identifies the position of a buried object in the xt plane. Among these, the position in the time axis direction is sufficient to know the relative positional relationship of the depths of multiple identified buried objects, but does not represent the absolute position of the depth within the area where the survey was performed.

[0082] To obtain the absolute position of a buried object in the depth direction, it is necessary to obtain the speed v at which the electromagnetic waves emitted from the underground radar device travel underground and convert it based on the position t of the buried object on the time axis.

[0083] Here, the conversion from time t to depth z is, for example,

number

[0084] Furthermore, the speed v at which electromagnetic waves travel underground is calculated by multiplying the speed of light in a vacuum c by the relative dielectric constant ε γ Using the following formula

number

[0085] Therefore, the depth conversion unit 42 converts the position of the buried object on the time axis included in the buried object information D2 into a depth using these formulas (1) and (2) and the estimated relative dielectric constant E1 estimated by the relative dielectric constant estimation unit 11, and outputs buried object information with depth D2' including the converted depth information. Then, the information display device 3 displays the buried object information with depth D2'.

[0086] An example of buried object information with depth D2' displayed on the information display device 3 will be described with reference to Fig. 7. Fig. 7(A) is an example of buried object information for two-dimensional underground exploration data. In the depth-included buried object information D2', the position is represented by the position relative to the exploration progress direction and the depth. In the case of a point object, it may be represented by a single point, and in the case of a line object, it may be represented by a line segment connecting the start point and the end point. Fig. 7(B) is an example of buried object information with depth D2' for three-dimensional underground exploration data. In this case, the depth-included buried object information D2' also has a component in the vertical direction to the exploration progress direction.

[0087] According to the buried object management system 40 of this embodiment having the above-mentioned configuration, the absolute depthwise position of the buried object within the search area is displayed on the information display device 3, so that in addition to the effect obtained by the first embodiment, it is possible to obtain the effect that the user can intuitively confirm the depth position of the buried object.

[0088] Furthermore, instead of the information display device 3 connected to the buried object discrimination device 41 shown in Figure 11, a buried object visualization system 21 shown in Figure 8 is connected, and buried object information with depth D2' is stored in the buried object information storage device 22. Based on the stored buried object information group D2A and the map information DM of the exploration area stored in the map information storage device 23, an underground exploration result screen 44, for example as shown in Figure 12, is generated and displayed.

[0089] The underground exploration result screen 44 is configured with a map display area 44A and a buried object information display area 44B. The map display area 44A displays three-dimensionally drawn images 44AA, 44AB of the exploration surface and buried objects, and values ​​indicating the vertical distances of these buried objects from the exploration surface. The buried object information display area 44B displays a list 44BA showing the type, material, and / or size of the buried objects.

[0090] According to the buried object management system having the above-mentioned configuration, the absolute position of the buried object in the depth direction within the exploration area, as well as the depth-related buried object information D2' generated based on multiple underground exploration data D1, are superimposed on the same map information DM and managed, thereby enabling the user to intuitively confirm the buried position between buried objects.

[0091] (4) Fourth embodiment Fig. 15, in which the same reference numerals are assigned to parts corresponding to those in Fig. 10, shows a buried object management system 60 according to the fourth embodiment. This buried object management system 60 differs from the buried object management system 40 of the third embodiment in that, in a buried object discrimination device 61 according to claim 3 shown in Fig. 14, the buried object identification unit 13 outputs the buried object information D2 to the relative dielectric constant estimation unit 53 in addition to the depth conversion unit 42, and the relative dielectric constant estimation unit 53 re-estimates the relative dielectric constant of the underground medium as necessary based on the buried object information D2 and the underground exploration data D1, and that the aperture synthesis processing unit 54 can re-execute the aperture synthesis processing based on the estimated relative dielectric constant E1 obtained by the re-estimation and an aperture synthesis processing re-execution flag FM input from outside the buried object discrimination device 61.

[0092] 13 shows the flow of a buried object discrimination process performed by the buried object discrimination device 61 of this embodiment for discriminating a buried object. This buried object discrimination process is started when the buried object discrimination device 61 is provided with underground exploration data D1.

[0093] The dielectric constant estimation unit 53 estimates the dielectric constant of the underground medium based on the input underground exploration data D1, and outputs the estimated dielectric constant E1 to the aperture synthesis processing unit 54 (S11). The aperture synthesis processing unit 54 also performs aperture synthesis processing on the input underground exploration data D1 using the estimated dielectric constant E1 provided by the dielectric constant estimation unit 53, and outputs the above-mentioned synthetic aperture exploration data D3 thus obtained to the buried object identification unit 13 (S12).

[0094] The buried object identification unit 13 identifies buried objects based on the input underground exploration data D1 and the aperture synthesis exploration data D3 provided from the aperture synthesis processing unit 54, generates buried object information D2 including information such as the type, shape, position and / or size of the identified buried object, and outputs it to the depth conversion unit 42 (S13).

[0095] The depth conversion unit 42 compares the position where the estimated relative dielectric constant E1 is estimated with the position of the buried object included in the buried object information D2 based on the position of the buried object included in the buried object information D2 provided by the buried object identification unit 52, and calculates the distance between the position of the relative dielectric constant E1 estimated by the relative dielectric constant estimation unit 53 and the position of the buried object included in the buried object information D2 (S14). Then, it is determined whether or not this distance is within an allowable range (S15).

[0096] Obtaining a positive result in this determination means that there is a high possibility that the estimated relative dielectric constant E1 estimated by the relative dielectric constant estimation unit 53 is accurate. Thus, at this time, the buried object identification unit 52 does not output the buried object information D2 generated at that time to the relative dielectric constant estimation unit 53.

[0097] As a result, in the depth conversion unit 42, the position of the buried object on the time axis is converted into a depth based on the buried object information D2 from the buried object identification unit 52 and the estimated relative dielectric constant E1 provided by the relative dielectric constant estimation unit 53 (S18).

[0098] Furthermore, the depth conversion unit 42 generates depth-added buried object information D2' including the converted depth position, and outputs the generated buried object information D2' (S19). With the above, the buried object discrimination process ends.

[0099] In contrast, a negative result in the determination in step S15 means that there is a possibility that the estimated relative dielectric constant E1 estimated by the relative dielectric constant estimation unit 53 is not accurate. Thus, at this time, the buried object identification unit 52 outputs the buried object information D2 generated at that time to the relative dielectric constant estimation unit 53.

[0100] The relative dielectric constant estimating unit 53 re-estimates the relative dielectric constant of the underground medium based on the buried object information D2 provided by the buried object identifying unit and the underground exploration data D1 (S16).

[0101] Specifically, the dielectric constant estimation unit 53 re-estimates the dielectric constant by performing a fitting process in which the parameters are changed so as to fit the logical arrival time to the underground exploration data D1, using the position of the buried object identified by the buried object identification unit 52 as a substitute for the position of the above-mentioned clear point.

[0102] Then, the aperture synthesis processing unit 54 judges whether the aperture synthesis processing re-execution flag FM indicates 1, which prompts re-execution (S17). Obtaining a negative result in the judgment of step S17 means that the user has determined that re-execution of aperture synthesis processing is not necessary, so steps S18 and S19 are executed and the processing ends. Obtaining a positive result in the judgment of step S17 means that re-execution of aperture synthesis processing is required. In this case, the aperture synthesis processing re-execution flag FM is changed to 0 (S20), and then feedback is given to step S12 to re-execute the aperture synthesis processing. The subsequent processing is as described above.

[0103] As a result, in the depth conversion unit 42, the position of the buried object on the time axis is converted into a depth based on the buried object information D2 from the buried object identification unit 52 and the re-estimated value of the dielectric constant provided by the dielectric constant estimation unit 53 (S18).

[0104] Furthermore, the depth conversion unit 42 generates buried object information D2' including the converted depth, and outputs the generated buried object information D2' (S19). With this, the buried object discrimination process ends.

[0105] Even if the estimated relative dielectric constant E1 corresponding to the buried object information has already been estimated, the relative dielectric constant estimation unit 53 may re-estimate the estimated relative dielectric constant E1 by setting to output a negative result in step S15. In this case, if the buried object information D2 of the buried object identified by the buried object identification unit 13 includes the depth position, horizontal position, type, shape, and size of the buried object, in step S16, the relative dielectric constant estimation unit 53 estimates the relative dielectric constant based on a logical arrival time that is assumed based on parameters such as the depth position, horizontal position, type, shape, and size of the buried object and that may be more valid than the logical arrival time assumed in the first estimation.

[0106] Here, in the above-mentioned step S11, if the relative dielectric constant estimation unit 53 performs a fitting method in which the clear points described in Non-Patent Document 2 are assumed to be reflection points of electromagnetic waves at buried objects, there is a risk of missing unclear reflection images actually measured at non-metallic buried objects, etc.

[0107] Regarding this point, in the buried object discrimination device 61 of the present embodiment, when the position of the estimated dielectric constant E1 estimated by the dielectric constant estimation unit 53 and the position of the buried object identified by the buried object identification unit 13 are far apart, the estimated dielectric constant E1 is re-estimated in the dielectric constant estimation unit 53 using the position information of the buried object identified by the buried object identification unit 13, and the position of the buried object on the time axis is converted to a depth based on the estimated dielectric constant E1 obtained by this re-estimation. Therefore, even for reflection images that are missed when the clear points are assumed to be reflection points of the buried object, depth conversion can be performed using the re-estimated estimated dielectric constant E1, and the accuracy of the converted depth of the buried object can be improved.

[0108] Furthermore, if the relative dielectric constant used in the aperture synthesis process is not a correct value, the image that should be collected by the aperture synthesis process is over-processed, causing distortion of the image. Therefore, if the underground exploration data D1 (aperture synthesis exploration data D3) that has been subjected to the aperture synthesis process using an incorrect relative dielectric constant is used to perform identification in the buried object identification unit 13, this can lead to overdetection and other problems.

[0109] In this regard, in the buried object discrimination device 61 of this embodiment, the aperture synthesis process is performed again using the dielectric constant re-estimated by the dielectric constant estimation unit 53, so that the aperture synthesis process can be performed on the underground exploration data D1 using an appropriate dielectric constant.

[0110] Therefore, according to this embodiment, the accuracy of identifying buried objects in buried object identifying section 13 can be further improved, and thus it is possible to obtain the effect that buried objects can be identified with even higher reliability.

[0111] (5) Fifth embodiment Fig. 17, in which parts corresponding to those in Fig. 15 are given the same reference numerals, shows the configuration of a buried object management system 70 according to a fifth embodiment. The buried object management system 70 in Fig. 17 is significantly different from the buried object management system 61 according to the fourth embodiment in that a selection unit 75 is provided as in the buried object discrimination device 71 recited in claim 4 shown in Fig. 16(A) compared to the buried object discrimination device 61.

[0112] 17 is a functional unit realized by the above-mentioned CPU included in the buried object discrimination device 71 executing the corresponding program stored in the above-mentioned memory included in the buried object discrimination device 71. This selection unit 75 has a function of outputting a depth conversion re-execution flag F3, an aperture synthesis processing re-execution flag FM, and a buried object discrimination re-execution flag F2 that control whether or not to re-execute aperture synthesis processing in the aperture synthesis processing unit 54, whether or not to re-execute buried object discrimination in the buried object discrimination unit 64, and whether or not to re-execute depth conversion in the depth conversion unit 62, based on the estimated relative dielectric constant E1 estimated in the relative dielectric constant estimation unit 53, the underground exploration data D1, and the synthetic aperture exploration data D3.

[0113] Specifically, the selection unit 75 will be described with reference to a block diagram shown in Fig. 16(B). The estimated relative dielectric constant E1 input to the selection unit 75 is input to a theoretical underground exploration data generation unit 76 and a depth conversion re-execution flag generation unit 79. The theoretical underground exploration data generation unit 76 assumes that a buried object exists at the position where the estimated relative dielectric constant E1 is estimated, generates a theoretical reflection image based on the estimated relative dielectric constant E1, and outputs it as theoretical underground exploration data D1T to an exploration data agreement calculation unit 77. The theoretical underground exploration data D1T may be generated by performing a numerical calculation simulation using the finite element method, the finite difference time domain method, or the like.

[0114] The exploration data agreement rate calculation unit 77 calculates the exploration data agreement rate V1, which indicates the agreement rate of the exploration data, based on the underground exploration data D1 and the theoretical underground exploration data D1T. When the underground exploration data D1 and the theoretical underground exploration data D1T are configured with arrays of the same size, the agreement rate can be calculated, for example, as the average value of the absolute value of their differences. A high exploration data agreement rate indicates that the estimated relative dielectric constant E1 estimated by the relative dielectric constant estimation unit 53 can well explain the underground exploration data D1, and can therefore be used to evaluate the validity of the estimated relative dielectric constant E1. The calculated exploration data agreement rate V1 is output to the depth conversion re-execution flag generation unit 79 and the aperture synthesis processing re-execution flag generation unit 710.

[0115] The exploration data convergence rate calculation unit 78 calculates the convergence rate as the exploration data convergence rate V2 based on the aperture synthesis exploration data D3. The method of calculating the convergence rate can be, for example, the method disclosed in Non-Patent Document 4. Since the aperture synthesis process is a process for correcting the distortion of the reflected image, the exploration data convergence rate V2 indicating the convergence rate can be used to evaluate the validity of the aperture synthesis process performed by the aperture synthesis processing unit 54. The exploration data convergence rate V2 is output to the buried object identification re-execution flag generation unit 711.

[0116] The depth conversion re-execution flag generation unit 79 holds the estimated relative dielectric constant E1, the exploration data agreement rate V1, or both, and generates a depth conversion re-execution flag F3 based on changes in the held estimated relative dielectric constant E1, the exploration data agreement rate V1, or both.

[0117] The aperture synthesis processing re-execution flag generation unit 710 holds the search data matching rate V1, and generates an aperture synthesis processing re-execution flag FM based on a change in the held search data matching rate V1.

[0118] The buried object identification retry flag generating unit 711 holds the search data convergence rate V2, and generates a buried object identification retry flag F2 based on a change in the held search data convergence rate V2.

[0119] Some of the generation patterns of the depth conversion re-execution flag F3, the aperture synthesis processing re-execution flag FM, and the buried object identification re-execution flag F2 will be described with reference to a specific example shown in FIG.

[0120] As shown in FIG. 18, when there is a difference between the first and second results of the estimated relative dielectric constant E1 that is equal to or greater than a specified threshold, the flag state is set to "1" indicating that the depth conversion process should be re-executed since it is considered that a significant difference will occur in the conversion result in the depth conversion unit 62 (No. 1). Conversely, when the difference is equal to or less than the specified threshold, it is considered that no significant difference will occur in the depth even if the depth conversion process is performed again, so the flag state is set to "0" indicating that the depth conversion process should not be re-executed (No. 2). Also, when the difference between the first and second values ​​of the exploration data agreement rate V1 is positive, it is considered that a more appropriate estimated dielectric constant E1 has been obtained, so the flag state is set to "1" indicating that the depth conversion process should be re-executed (No. 3). Conversely, when the difference between the first and second values ​​of the exploration data agreement rate V1 is negative, it is considered that a less appropriate estimated dielectric constant E1 has been obtained, so the flag state is set to "0" indicating that the depth conversion process should not be re-executed (No. 4).

[0121] The aperture synthesis rerun flag FM is also set to "1" (No. 5) to indicate that the aperture synthesis should be rerun, since it is considered that a more appropriate estimated dielectric constant E1 has been obtained when the difference between the first and second numerical values ​​of the survey data match rate V1 is positive. Conversely, it is set to "0" (No. 6) to indicate that the aperture synthesis should not be rerun, since it is considered that a less appropriate estimated dielectric constant E1 has been obtained when the difference between the first and second numerical values ​​of the survey data match rate V1 is negative.

[0122] The buried object identification re-execution flag F2 is also set to "1" (No. 7), indicating that buried object identification processing should be re-executed, since it is considered that more appropriate aperture synthetic exploration data D3 has been obtained when the difference between the first and second numerical values ​​of the exploration data convergence rate V2 is positive. Conversely, it is set to "0" (No. 8), indicating that buried object identification processing should not be re-executed, since it is considered that less appropriate aperture synthetic exploration data D3 has been obtained when the difference between the first and second numerical values ​​of the exploration data convergence rate V2 is negative.

[0123] In addition, the selection unit 75 may determine the validity of the estimated dielectric constant E1, the exploration data match rate V1, and the exploration data convergence rate V2 before and after the re-execution based on whether or not a predetermined threshold has been reached or whether or not the rate of change has exceeded a predetermined threshold, in addition to by comparing the magnitude before and after the re-execution as described above.

[0124] The buried object management system 70 of this embodiment having the above configuration can regenerate the synthetic aperture exploration data D3 to be input to the buried object identification unit 64 based on the high-level buried object identification results in the buried object identification unit 64. This improves the quality of the synthetic aperture exploration data D3 to be input to the buried object identification unit 64, and can improve the buried object identification accuracy in the buried object identification unit 64.

[0125] Since the buried object identification result (buried object information D2) using the updated synthetic aperture exploration data D3 as input may be updated, this identification result may be returned to the dielectric constant estimation unit 53, and the re-estimation of the dielectric constant in the dielectric constant estimation unit 53, the aperture synthesis processing in the synthetic aperture processing unit 54, and the above-mentioned selection action in the selection unit 75 may be performed multiple times. By doing so, the quality of the synthetic aperture exploration data D3 input to the buried object identification unit 64 is improved, and the identification accuracy of the buried object identification unit 64 can be improved.

[0126] In this case, for example, among the data shown in FIG. 18, each time the dielectric constant is re-estimated by the dielectric constant estimating unit 53, the new dielectric constant may be overwritten as the initial estimated value of the dielectric constant and held, or data for a plurality of times may be held.

[0127] By doing so, every time the dielectric constant is re-estimated by the dielectric constant estimation unit 53, the re-estimated dielectric constant and the synthetic aperture exploration data D3 generated by the aperture synthesis processing unit 54 based on the re-estimated dielectric constant become of higher quality, so that the identification accuracy of buried objects in the buried object identification unit 64 can be further improved. Therefore, according to the buried object management system 70 of this embodiment, buried objects can be identified with even higher reliability.

[0128] (6) Sixth embodiment Fig. 19, in which parts corresponding to those in Fig. 16(B) are given the same reference numerals, shows the configuration of a selection unit 75' of a buried object management system according to the sixth embodiment. The selection unit 75' of Fig. 19 is significantly different from the selection unit 75 according to the fifth embodiment in that it can output an exploration data match rate V1 and an exploration data convergence rate V2.

[0129] The exploration data match rate V1 and the exploration data convergence rate V2 output from the selection unit 75' are values ​​for evaluating the validity of the dielectric constant estimation process by the dielectric constant estimation unit 53 and the aperture synthesis process by the aperture synthesis processing unit 54, respectively, and in the sixth embodiment, these exploration data match rate V1 and the exploration data convergence rate V2 are output outside the buried object discrimination device.

[0130] By doing so, the information display device 3 connected to the buried object discrimination device can display the search data match rate V1 and the search data convergence rate V2, and thus the user can check the validity of the buried object discrimination results of the buried object discrimination device. Therefore, according to the buried object management system of this embodiment, buried objects can be discriminated with even higher reliability.

[0131] (7) Seventh embodiment Fig. 21, in which the same reference numerals are assigned to parts corresponding to those in Fig. 1B, shows a buried object management system 90 according to the seventh embodiment. This buried object management system 90 differs from the first embodiment in that a buried object discrimination device 91 in Fig. 20(A) has a buried object learning model generation unit 97 shown in Fig. 20(B), and the buried object learning model generation unit 97 generates a buried object learning model LM using the acquired underground exploration data D1, the aperture synthetic exploration data D3 generated within the device itself, and buried object presence information A1 including information that at least a buried object is present or not present in the exploration area in which the underground exploration data D1 was acquired, and the buried object management system 90 identifies buried objects using the generated buried object learning model LM.

[0132] Actually, in the case of this embodiment, the learning data generation unit 95 generates learning data DL based on the underground exploration data D1, the synthetic aperture exploration data D3 generated based on the underground exploration data D1, and the buried object presence information A1, and stores the learning data DL in the learning data storage unit 94. Here, in Fig. 20(B) the learning data storage unit 94 is shown to be included in the buried object learning model generation unit 97, but it may be disposed inside or outside the buried object discrimination device 91 of the buried object learning model generation unit 97.

[0133] The buried object learning model generation unit 97 uses the learning data group DLA stored in the memory as described above to learn the type, shape, position, size, and the like of the buried object in the underground exploration data D1 and / or the synthetic aperture exploration data D3 with the learner 96, thereby generating a buried object learning model LM. This buried object learning model LM is, for example, an AI (Artificial Intelligence) model constituted by a neural network.

[0134] Then, when the buried object identification unit 93 is given underground exploration data D1 acquired through exploration work in a new exploration area, etc., and / or aperture synthesis exploration data D3 from the aperture synthesis processing unit 12, it identifies the type, shape, position, size, etc. of the buried object based on the buried object learning model LM, and outputs buried object information D2 based on the identification results to the information display device 3.

[0135] The buried object learning model generation unit 97 then uses the continuously accumulated learning data group DLA to re-learn the type, shape, position, size, etc. of buried objects in the underground exploration data D1 and / or the synthetic aperture exploration data D3 in the learning device 96, and updates the buried object learning model LM as necessary.

[0136] According to the buried object management system 90 of this embodiment having the above-mentioned configuration, the synthetic aperture exploration data D3 corresponding to the underground exploration data D1 is generated within the buried object discrimination device 91, so that the underground exploration data D1 and / or the synthetic aperture exploration data D3 can be automatically associated with buried object information A1 such as the type, shape, position and size of the buried object within the buried object discrimination device 91.

[0137] Therefore, compared to the conventional case in which the synthetic aperture exploration data D3 is generated outside the buried object discrimination device 91, it is possible to reduce the cost and effort required to match the underground exploration data D1 and / or the synthetic aperture exploration data D3 with buried object information A1 such as the type, shape, position and size of the buried object.

[0138] Furthermore, in the present buried object management system 90, the buried object learning model LM is updated appropriately as described above, so that the buried object identification performance of the buried object identifying unit 93 can be continuously improved.

[0139] As a result, according to the buried object management system 90 of this embodiment, in addition to the effect obtained by the first embodiment, the effect of being able to construct a buried object discrimination device with high buried object discrimination performance at low cost can be obtained.

[0140] Furthermore, in this embodiment, as shown in FIG. 22, a buried object learning model generation unit 97' as described in claim 7 is provided instead of the buried object learning model generation unit 97. By constantly storing the underground exploration data D1 and the aperture synthesis data D3 in the exploration data storage unit 166 and inputting buried object presence information A1 within the exploration area, the learning data generation unit 95 generates learning data DL using the stored exploration data group DPL.

[0141] As a result, according to the buried object management system 90 of this embodiment, even if buried object presence information for the exploration area is acquired at a time different from the acquisition of underground exploration data, the learning data DL can be automatically associated and appropriate learning data DL can be accumulated within the buried object management system 90. And, by appropriately updating the buried object learning model LM, it is possible to obtain the effect that the buried object management system 90 can be operated while continuing to improve the buried object identification performance of the buried object identification unit 93.

[0142] (8) Eighth embodiment 24, in which parts corresponding to those in Fig. 1A and B are given the same reference numerals, shows a buried object management system 100 according to an eighth embodiment. As shown in Fig. 23 which shows a buried object discrimination device 101 of claim 8, this buried object management system 100 is significantly different from the buried object management system 1 of the first embodiment in that a data compression unit 102 that compresses input underground exploration data D1 is additionally provided to the buried object discrimination device 2 of claim 1 shown in Fig. 1A.

[0143] In practice, the data compression unit 102 compresses the input underground exploration data D1 by extracting data of sparse points, for example, on the x-axis or t-axis, or on both the x-axis and t-axis in Fig. 2(A). However, various other compression methods can be applied as a method for compressing the underground exploration data D1 by the data compression unit 102, such as reducing the number of bits of data at each point.

[0144] Then, the data compression unit 102 outputs the compressed underground exploration data D1 as compressed underground exploration data D10 to the relative dielectric constant estimation unit 11, the aperture synthesis processing unit 12, and the buried object identification unit 13. As a result, each of the subsequent processes in the relative dielectric constant estimation unit 11, the aperture synthesis processing unit 12, and the buried object identification unit 13 is executed based on the compressed underground exploration data D10.

[0145] According to the buried object management system 100 of this embodiment having the above-mentioned configuration, in addition to the effects obtained by the first embodiment, it is possible to obtain the effect of reducing the calculation costs of each process in the relative dielectric constant estimation section 11, the opening synthesis processing section 12 and the buried object identification section 13 of the buried object discrimination device 101.

[0146] Furthermore, according to this buried object management system 100, it is possible to reduce the memory capacity required for various calculation processes in the buried object discrimination device 101, which has the effect of enabling buried objects to be discriminated at lower cost and in a shorter time.

[0147] (9) Ninth embodiment 26, in which parts corresponding to those in Fig. 1A and B are given the same reference numerals, shows a buried object management system 110 according to a ninth embodiment. As shown in Fig. 25 which shows a buried object discrimination device 111 of claim 9, this buried object management system 110 differs greatly from the buried object management system 1 of the first embodiment in that a resizing processing unit 112 which resizes the underground exploration data D1 and the synthetic aperture exploration data D3 is additionally provided in the buried object discrimination device 111.

[0148] In practice, the resizing processing unit 112 is provided with the input underground exploration data D1 and the synthetic aperture exploration data D3 output from the aperture synthesis processing unit 12. The resizing processing unit 112 then executes resizing processing on the underground exploration data D1 and the synthetic aperture exploration data D3, and outputs the resized underground exploration data D1 and the resized synthetic aperture exploration data D3' to the buried object identification unit 13.

[0149] In this case, the "resizing process" refers to a process of increasing or decreasing the number of data points arranged along the x-axis or t-axis direction in Fig. 2(A). In the resizing process unit, the data size after resizing is preset, such as 500 x 1000 for two-dimensional data as shown in Fig. 2(A).

[0150] The resizing unit 112 then resizes the input underground exploration data D1 and the synthetic aperture exploration data D3 to the specified data size. Note that the resized data sizes of the underground exploration data D1 and the synthetic aperture exploration data D3 may be set to the same size or different sizes.

[0151] As a method for changing the number of data points in such resizing processing, an interpolation method such as nearest neighbor interpolation, linear interpolation, Lagrange interpolation, centroid interpolation, or quadratic spline interpolation can be used.

[0152] According to the buried object management system 110 of this embodiment having the above-mentioned configuration, the size of the data flowing to subsequent processing can be kept constant within the buried object discrimination device 111 by such resizing processing, so that even if the size of the underground exploration data D1 acquired and generated by, for example, an underground radar device of a different manufacturer or model changes, it is possible to reuse some or all of it.

[0153] Therefore, according to this buried object management system 110, even if the buried object identification unit 13 has a configuration for identifying buried objects using the buried object learning model LM as in the seventh embodiment, it is possible to eliminate the need to modify the network size of the buried object learning model LM (Figure 19), thereby achieving the effect of enabling the construction of a more versatile system.

[0154] (10) Tenth embodiment Fig. 28, in which the same reference numerals are assigned to parts corresponding to those in Fig. 21, shows a buried object management system 120 according to the tenth embodiment. This buried object management system 120 is configured similarly to the buried object management system 110 of the ninth embodiment, except that a data division unit 122 for dividing underground exploration data D1 is additionally provided in a buried object discrimination device 121 recited in claim 10 shown in Fig. 27.

[0155] In practice, the data division unit 122 is provided with the underground exploration data D1 input to the buried object discrimination device 121. The data division unit 122 then performs a division process to divide this underground exploration data D1 into a plurality of pieces, and outputs the divided underground exploration data (hereinafter, referred to as divided underground exploration data) D11 to the relative dielectric constant estimation unit 11, the aperture synthesis processing unit 12, and the resizing processing unit 112 in sequence.

[0156] In this case, the underground exploration data D1 is divided, for example, in the exploration proceeding direction (x-axis direction in FIG. 2(A)) into a plurality of divided underground exploration data D11 equivalent to a predetermined distance in real space. For example, if the movement distance of the underground radar device in the exploration proceeding direction is 100 m, the data division unit 122 divides the underground exploration data D1 into 10 divided underground exploration data D11, each of which has a movement distance of 10 m in the exploration proceeding direction.

[0157] According to the buried object management system 120 of this embodiment having the above-mentioned configuration, it is possible to reduce the calculation costs of the relative dielectric constant estimation section 11, the aperture synthesis processing section 12 and the buried object identification section 13 in the buried object discrimination device 121 without incurring a decrease in the amount of information due to data compression as in the ninth embodiment, for example.

[0158] Furthermore, according to the buried object management system 120, the memory capacity of the buried object discrimination device 121 can be reduced, and the buried object discrimination process can be carried out at lower cost in a shorter time.

[0159] (11) Eleventh embodiment There are several types of underground radar devices with different structures of transmitting and receiving antennas. Figures 29(A-1) and (B-1) show typical structural examples of such transmitting and receiving antennas. Figure 29(A-1) shows an antenna structure configured as a transmitting and receiving antenna 130 in which a transmitting antenna Tx and a receiving antenna Rx are integrated, and Figure 29(B-1) shows an antenna structure of a transmitting and receiving antenna 131 in which a transmitting antenna Tx and a receiving antenna Rx are provided separately.

[0160] In the case of the antenna structure of Fig. 29(A-1), as shown in Fig. 29(A-2), most of the electromagnetic waves emitted from the transmitting / receiving antenna 130 into the ground are reflected by a buried object 132 buried directly below, and the reflected waves are received by the transmitting / receiving antenna 130. In the case of the antenna structure of Fig. 29(B-1), as shown in Fig. 29(B-2), of the waves emitted from the transmitting antenna Tx of the transmitting / receiving antenna 131 into the ground and reflected by the buried object 132 directly below, only the reflected waves of a portion of the electromagnetic waves that are incident on the buried object 132 at a certain angle of incidence are received by the receiving antenna Rx of the transmitting / receiving antenna 131.

[0161] As is clear from a comparison of Figures 29(A-2) and 29(B-2), the path that the electromagnetic waves emitted from the transmitting and receiving antennas 130, 131 take to be reflected by the buried object 132 and received by the transmitting and receiving antennas 130, 131 varies depending on the antenna structure of the underground radar device, and accordingly the time that it takes from when the transmitting and receiving antennas 130, 131 emit the electromagnetic waves to when the reflected waves of the electromagnetic waves from the buried object 132 are received by the transmitting and receiving antennas 130, 131 also varies. With regard to this reception time, if the horizontal axis represents the position of the underground radar device and the vertical axis represents the time required for reception, it can be expressed as the entire edges of 133, 134 in Figures 29(A-4) and (B-4).

[0162] For example, when the antenna structure of the underground radar device is as shown in FIG. 29(A-1), the x coordinate of the position directly above the buried object 132 in the transmitting / receiving antenna 130 of the underground radar device is expressed as x 0 The time it takes for the electromagnetic wave emitted from that position to be reflected by the buried object 132 and return to the transmitting / receiving antenna 130 is t 0 , the x coordinate of the transmitting / receiving antenna 130 is x i The time it takes for the electromagnetic wave emitted from the position to be reflected by the buried object 132 and return to the transmitting / receiving antenna 130 is t i If the speed at which the electromagnetic wave travels underground is v, then over time t i The radar reflection formula is as follows:

number

[0163] In addition, when the antenna structure of the underground radar device is as shown in FIG. 29(B-1), the x coordinate of the position directly above the buried object 132 of the transmitting antenna Tx of the transmitting / receiving antenna 131 is expressed as x 0 The time it takes for the electromagnetic wave emitted from that position to be reflected by the buried object 132 and reach the receiving antenna Rx is t 0 , the x coordinate of the transmitting antenna Tx is x i The time it takes for the electromagnetic wave emitted from the position to be reflected by the buried object 132 and reach the receiving antenna Rx is t i, the speed at which the electromagnetic wave travels underground is v, and the distance between the transmitting antenna Tx and the receiving antenna Rx in the transmitting / receiving antenna 131 is TR offset (See FIG. 29(B-1)) Then, at time t i The radar reflection formula is as follows:

number

[0164] In this case, for example, in the buried object discrimination device 2 of the first embodiment, the dielectric constant estimation unit 11 and the aperture synthesis processing unit 12 perform calculations to estimate the dielectric constant and correct distortion of the reflected image by modeling the time it takes for the electromagnetic waves emitted from the underground radar device to be reflected by a buried object and received by the receiving antenna as a radar reflection equation.

[0165] For this reason, if the same radar reflection formula is used to estimate the dielectric constant or perform aperture synthesis processing without distinguishing between the underground exploration data D1 from the underground radar device with the antenna structure of Figure 29 (A-1) and the underground exploration data D1 from the underground radar device with the antenna structure of Figure 29 (B-1), a large error may occur between the estimated dielectric constant and the actual dielectric constant, or distortion may occur in the aperture synthesis image.

[0166] Therefore, in this embodiment, the radar reflection type is switched depending on the antenna structure of the underground radar device, thereby preventing a large error between the estimated relative dielectric constant and the actual relative dielectric constant and distortion in the aperture synthesized image.

[0167] 31, in which the same reference numerals are assigned to parts corresponding to those in FIG. 1A and B with respect to the operation of the buried object discrimination device of this embodiment, shows the configuration of a buried object management system 140 according to this embodiment equipped with such functions. This buried object management system 140 is significantly different from the buried object management system 1 of the first embodiment in that the functions of the relative dielectric constant estimation section 142 and the aperture synthesis processing section 143 of the buried object discrimination device 141 are different.

[0168] 32A and 32B show the flow of a buried object discrimination process executed for discriminating a buried object in the buried object discriminating device of this embodiment.

[0169] As shown in Fig. 32A and Fig. 32B, in this buried object discrimination device 141, first, the dielectric constant estimation unit 142 reads the underground exploration data D1 (S501). Then, it is determined whether the underground exploration data D1 includes antenna structure information IA (S502). If the antenna structure information IA does not exist, the buried object discrimination process ends through the same processes as those of the buried object management system 1 of the first embodiment (S504, S505, S508 to S510 in Fig. 32B).

[0170] If the underground exploration data D1 includes antenna structure information IA, that is, if a positive result is obtained in step S502, it is determined whether to change the radar reflection formula R1 of the relative dielectric constant estimation unit 142 (S511). If a positive result is obtained in this step S511, the relative dielectric constant estimation unit 142 selects the radar reflection formula R1 based on the antenna structure information IA (S503). If a negative result is obtained in step S511, step S503 is skipped. Next, the relative dielectric constant estimation unit 142 estimates the relative dielectric constant (S504). The estimated relative dielectric constant E1 obtained by the relative dielectric constant estimation unit 142 is input to the aperture synthesis processing unit 143 and read together with the underground exploration data D1 (S505). Next, it is selected whether to change the radar reflection formula R2 of the aperture synthesis processing unit 143 (S506). If a positive result is obtained in this step S506, the aperture synthesis processing unit 143 selects the radar reflection formula R2 based on the antenna structure information IA (S507). If a negative result is obtained in step S506, step S507 is skipped. As for the subsequent processing, the same processing (S508 to S510) as in the buried object management system 1 of the first embodiment is carried out, and then this buried object discrimination processing ends.

[0171] In this buried object discrimination device 141, in order to enable the dielectric constant estimation unit 142 and the aperture synthesis processing unit 143 to change the radar reflection formulas R1 and R2, a list of antenna structures for each manufacturer and model of underground radar device (hereinafter referred to as the antenna structure list) and radar reflection formulas such as equations (3) and (4) for each antenna structure are stored and managed, for example, in the above-mentioned memory provided in the buried object discrimination device 141.

[0172] According to the buried object management system 140 of this embodiment having the above-mentioned configuration, the accuracy of the dielectric constant estimation by the dielectric constant estimation unit 142 and the aperture synthesis processing by the aperture synthesis processing unit 143 can be kept constant even for underground radar devices having different antenna structures, and the estimated or generated dielectric constant and synthetic aperture exploration data D3 can be kept as homogeneous as possible as the buried object discrimination device 141.

[0173] Therefore, according to the present buried object management system 140, in addition to the effect obtained by the first embodiment, it is possible to obtain the effect that the output of the buried object identifying section 13 can be guaranteed for general purposes.

[0174] (12) Twelfth embodiment As illustrated in Figures 29(A-3) and 29(B-3), the reflection paths of electromagnetic waves are different for underground radar devices with different antenna structures, so the reflection images from buried objects that appear in the underground exploration data D1 shown in Figure 1B may have unique shapes.

[0175] Therefore, it is believed that the accuracy of identifying buried objects can be improved by storing the given underground exploration data D1 separately for each antenna structure of the underground radar device used to acquire the underground exploration data D1, generating a buried object learning model that identifies buried objects based on the stored underground exploration data D1 for each antenna structure, and identifying buried objects using the generated buried object learning model.

[0176] Figure 34, in which the same reference numerals are assigned to parts corresponding to those in Figure 31, shows a buried object management system 170 of this embodiment configured based on this idea. One of the features of this buried object management system 170 is that it has a buried object learning model generation unit 172 shown in Figure 33, generates a buried object learning model LM (LM1, LM2, ...) for each antenna structure of the underground radar device, and identifies buried objects using a corresponding buried object learning model LM among the generated buried object learning models LM.

[0177] In practice, in this embodiment, the learning data DL generated by the learning data generation unit 95 of the buried object learning model generation unit 172 holds the antenna structure information IA included in the underground exploration data D1. The learning device 173 extracts a learning data group DLA having the same type of antenna structure information IA from the accumulated learning data group DLA, and trains the buried object learning model LM based on the extracted data. The buried object learning model generation unit holds a buried object learning model LM (LM1, LM2, ...) for each piece of antenna structure information IA.

[0178] On the other hand, the buried object identification unit 174 inputs the underground exploration data D1, reads the antenna structure information IA, acquires a suitable buried object learning model LM from the buried object learning model generation unit 172, and identifies buried objects using the acquired buried object learning model LM. The correspondence between the antenna structure information IA and the buried object learning model LM is stored in a correspondence table, for example, in a memory provided in this buried object discrimination device and referenced.

[0179] Then, the buried object identifying unit 174 outputs buried object information D2 of the buried object obtained by this identification process from the buried object discrimination device 171 to the information display device 3. As a result, the buried object discrimination result is displayed on the information display device 3 based on this buried object information D2.

[0180] According to the buried object management system 170 of this embodiment having the above-mentioned configuration, a buried object learning model LM (LM1, LM2) suitable for each antenna structure is generated within the system for input of underground exploration data D1 acquired by underground radar devices having different structures, and the identification accuracy of the buried object identification unit 174 can be improved while ensuring homogeneity of the output of the buried object identification unit 174.

[0181] (13) Other embodiments In the above-mentioned first to twelfth embodiments, the buried object discrimination device is described as being configured by one computer device, but the present invention is not limited to this, and the buried object discrimination device may be constructed by multiple computer devices that constitute a distributed computing system.

[0182] In addition, in the above-mentioned first to twelfth embodiments, the relative dielectric constant estimation units 11, 53, 142, the aperture synthesis processing units 12, 54, 63, 73, 143, the buried object identification units 13, 64, 174, the depth conversion units 42, 62, the selection units 75, 75', the buried object learning model generation units 97, 97', 172, the data compression unit 102, the data division unit 122, and the resizing processing unit 112 are configured as software, but the present invention is not limited to this, and some or all of these may be configured as hardware.

[0183] Furthermore, in the above-mentioned first to twelfth embodiments, the buried object management systems 1, 20, 40, 60, 70, 90, 110, 120, 140, and 170 have been described as having only the characteristic configurations unique to the first to twelfth embodiments, respectively, but the present invention is not limited to this, and a buried object management system may be configured by combining some or all of the characteristic configurations unique to the first to twelfth embodiments. [Industrial Applicability]

[0184] The present invention can be widely applied to buried object discrimination devices of various configurations that discriminate buried objects based on underground exploration data obtained by transmitting and receiving electromagnetic waves into the ground. [Explanation of symbols]

[0185] 1,20,40,60,70,90,110,120,140,170 ...... buried object management system, 2,41,61,71,81,91,161,101,111,121,141,171 ...... buried object discrimination device, 11,53,142 ...... relative dielectric constant estimation unit, 12,54,63,73,143 ...... aperture synthesis processing unit, 13,64,174 ...... buried object identification unit, 30,44 ...... underground exploration result screen, 42,62 ...... depth conversion unit, 56,153 ...... memory, 102 ...... data compression unit, 112 ...... resizing processing unit, 1 22: Data division unit, 130: Transmitting and receiving antenna, 132: Buried object, D1: Underground exploration data, D1': Resized underground exploration data, D3': Resized aperture synthetic exploration data, D2, D21, D22: Buried object information, D2': Buried object information with depth, D3: Aperture synthetic exploration data, D10: Compressed underground exploration data, D11: Divided underground exploration data, Rx: Receiving antenna, Tx: Transmitting antenna, D4: Synthetic data, E1: Estimated relative dielectric constant, FM: Aperture synthetic processing re-execution flag, F2: Buried object Re-identification flag, F3... depth conversion re-execution flag, V2... exploration data convergence rate, V1... exploration data match rate, D2A... buried object information group, DM... map information, 22... buried object information storage device, 23... map information storage device, 24... information display device, 21... buried object visualization system, 75, 75'... selection unit, A1... buried object presence information, 94... learning data storage unit, 95... learning data generation unit, 166... ​​exploration data storage unit, DPL... exploration data group, DLA... learning data group, DL... learning data, I A...antenna structure information, LM, LM1, LM2...buried object learning model, 76...theoretical underground exploration data generation unit, 77...exploration data match rate calculation unit, 78...exploration data convergence rate calculation unit, 79...depth conversion re-execution flag generation unit, 710...aperture synthesis processing re-execution flag generation unit, 711...buried object identification re-execution flag, D1T...theoretical underground exploration data, 97, 97', 172...buried object learning model generation unit, 96, 173...learning device, 133, 134...full edge of buried object reflection signal, R1, R2...radar reflection formula.

Claims

1. A buried object discrimination device that discriminates buried objects based on underground exploration data obtained by transmitting and receiving electromagnetic waves to and from the ground, a relative permittivity estimation unit that estimates the relative permittivity of an underground medium based on the underground exploration data provided from outside and outputs the estimated relative permittivity; an aperture synthesis processing unit that performs a synthetic aperture process on the underground exploration data using the estimated relative dielectric constant and outputs synthetic aperture exploration data that maintains the format of input data within the buried object discrimination device; a buried object identifying unit that performs an identification process for identifying the buried object based on the synthetic aperture exploration data and the underground exploration data, and outputs information about the buried object as buried object information; A buried object discrimination device comprising:

2. 2. The buried object discrimination device according to claim 1, The apparatus further includes a depth conversion unit that converts the position of the buried object information on the time axis into a depth representing the distance of the buried object from the ground surface based on the buried object information output from the buried object identification unit and the estimated relative dielectric constant estimated by the relative dielectric constant estimation unit, and outputs buried object information with depth that also includes the converted depth. A buried object discrimination device characterized by:

3. 3. The buried object discrimination device according to claim 2, the relative dielectric constant estimating unit re-estimates the estimated relative dielectric constant based on the buried object information output by the buried object identifying unit, The aperture synthesis processing unit receiving a flag for re-executing aperture synthesis processing from outside the buried object discrimination device; Based on the aperture synthesis processing re-execution flag, determining whether to re-execute the aperture synthesis processing based on the estimated relative dielectric constant re-estimated by the relative dielectric constant estimating unit; When the buried object identification unit is to be re-implemented, re-executing the buried object identification process based on the synthetic aperture exploration data and the underground exploration data obtained by re-executing the synthetic aperture process by the synthetic aperture processing unit; The depth conversion unit converting the position of the buried object on the time axis into a depth of the buried object based on the buried object information obtained by re-executing the buried object identification process and the estimated relative dielectric constant re-estimated by the relative dielectric constant estimating unit; The buried object information with depth updated to the converted depth is output. A buried object discrimination device characterized by:

4. 4. The buried object discrimination device according to claim 3, The buried object discrimination device includes: a selection unit having a function of outputting an aperture synthesis processing re-execution flag, a buried object identification re-execution flag, and a depth conversion re-execution flag for controlling re-execution of the aperture synthesis processing unit, the buried object identification unit, and the depth conversion unit based on the underground exploration data, the estimated relative dielectric constant, and the aperture synthesis exploration data, The selection unit a theoretical underground exploration data generation unit that calculates theoretical underground exploration data based on the estimated relative dielectric constant; a coincidence rate calculation unit that compares the underground exploration data with the theoretical underground exploration data and calculates a coincidence rate therebetween; a convergence rate calculation unit that calculates a convergence rate of the synthetic aperture exploration data; a depth conversion retry flag generation unit that holds the estimated relative dielectric constant and the coincidence rate and generates the depth conversion retry flag; an aperture synthesis processing re-execution flag generation unit that holds the matching rate and generates the aperture synthesis processing re-execution flag; a buried object discrimination retry flag generation unit that holds the convergence rate and generates the buried object discrimination retry flag. A buried object discrimination device characterized by:

5. 5. The buried object discrimination device according to claim 4, The selection unit outputs at least one of the match rate and the convergence rate to an outside of the buried object discrimination device. A buried object discrimination device characterized by:

6. 2. The buried object discrimination device according to claim 1, the buried object discrimination device includes a buried object learning model generation unit, The buried object learning model generation unit buried object presence information including information indicating at least whether the buried object is present or not in the exploration area from which the underground exploration data was acquired, and a training data generation unit that generates training data based on the underground exploration data and the synthetic aperture exploration data; a learning device that learns an embedded object learning model based on the accumulated learning data group; The buried object identification unit identifies the buried object using the buried object learning model. A buried object discrimination device characterized by:

7. 2. The buried object discrimination device according to claim 1, the buried object discrimination device includes a buried object learning model generation unit, The buried object learning model generation unit The underground exploration data and the synthetic aperture exploration data are constantly stored in an exploration data storage unit; a learning data generation unit that receives buried object presence information including the known locations of the buried objects, generates learning data from the buried object presence information and a group of search data stored in the search data storage unit that is acquired based on the buried object presence information, and stores the learning data in the learning data storage unit; a learning device that learns an embedded object learning model based on the accumulated learning data group; The buried object identification unit identifies the buried object using the buried object learning model. A buried object discrimination device characterized by:

8. The buried object discrimination device according to claim 1, Further comprising a data compression unit that receives input of the underground exploration data, compresses the underground exploration data, and outputs the compressed data to the relative dielectric constant estimation unit, the aperture synthesis processing unit, and the buried object identification unit, The calculation costs of the relative permittivity estimation unit, the aperture synthesis processing unit, and the buried object identification unit can be reduced. A buried object discrimination device characterized by:

9. 2. The buried object discrimination device according to claim 1, Further comprising a resizing processing unit that receives input of the underground exploration data, resizes the underground exploration data and the aperture synthesis exploration data output from the aperture synthesis processing unit to a predetermined size, respectively, to generate resized underground exploration data and resized aperture synthesis exploration data, and outputs the resized underground exploration data and resized aperture synthesis exploration data to the buried object identification unit, The same buried object identifier can be used regardless of the size of the underground exploration data. A buried object discrimination device characterized by:

10. 10. The buried object discrimination device according to claim 9, Further comprising a data division unit that receives input of the underground exploration data, divides the underground exploration data to generate divided underground exploration data, and outputs the divided underground exploration data to the relative dielectric constant estimation unit, the aperture synthesis processing unit, and the buried object identification unit, The calculation costs for the divided underground exploration data of the relative dielectric constant estimation unit, the aperture synthesis processing unit, the resizing processing unit, and the buried object identification unit can be reduced without reducing the amount of information contained in the underground exploration data. A buried object discrimination device characterized by:

11. 2. The buried object discrimination device according to claim 1, At least one of the relative permittivity estimating unit and the aperture synthesis processing unit is determining whether the underground exploration data includes antenna structure information including the antenna structure of the underground radar device that generated the underground exploration data; If the antenna structure information is available, selecting the radar reflection formula corresponding to the antenna structure from among radar reflection formulas defined in advance for each of the antenna structures; Estimating the relative permittivity based on the radar reflection equation or performing the aperture synthesis process on the underground exploration data A buried object discrimination device characterized by:

12. The buried object discrimination device according to claim 11, the buried object discrimination device includes a buried object learning model generation unit, The buried object learning model generation unit constantly storing the underground exploration data and the synthetic aperture exploration data; a learning data generation unit that generates learning data based on buried object presence information including information indicating at least whether the buried object is present or not in the exploration area from which the underground exploration data was acquired, and on a group of accumulated exploration data; a learning device that extracts a group of learning data relating to the same type of antenna structure based on the antenna structure from the accumulated learning data, and learns an embedded object learning model for each of the antenna structures based on the group of learning data, The buried object identification unit identifies the buried object by using the buried object learning model related to the antenna structure of the input underground exploration data from among the accumulated buried object learning models. A buried object discrimination device characterized by:

13. The buried object discrimination device according to claim 1 ; a buried object visualization system that visualizes the buried object information, The buried object visualization system includes: a buried object information storage device that stores the buried object information output from the buried object identification unit of the buried object discrimination device; a map information storage device for storing map information; An information display device is provided that integrates and displays part or all of the buried object information stored in the buried object information storage device and the map information stored in the map information storage device based on the location of the buried object information. A buried object management system.

14. A buried object discrimination method executed by a buried object discrimination device that discriminates buried objects underground based on underground exploration data obtained by transmitting and receiving electromagnetic waves to and from the underground, comprising: a first step of inputting the underground exploration data provided from an external source; a second step of estimating the relative dielectric constant of the underground medium based on the input underground exploration data; a third step of performing a synthetic aperture process on the underground exploration data based on the estimated relative dielectric constant; a fourth step of performing an identification process for identifying the buried object based on the synthetic aperture exploration data, which is obtained by performing a synthetic aperture process on the underground exploration data and which maintains the format of input data within the buried object discrimination device, and the underground exploration data; a fifth step of outputting information about the buried object obtained by the identification process as buried object information; A buried object discrimination method comprising:

Images