CN105182328B - A kind of GPR buried target detection method based on two-dimensional empirical mode decomposition - Google Patents
A kind of GPR buried target detection method based on two-dimensional empirical mode decomposition Download PDFInfo
- Publication number
- CN105182328B CN105182328B CN201510570738.6A CN201510570738A CN105182328B CN 105182328 B CN105182328 B CN 105182328B CN 201510570738 A CN201510570738 A CN 201510570738A CN 105182328 B CN105182328 B CN 105182328B
- Authority
- CN
- China
- Prior art keywords
- empirical mode
- dimensional empirical
- target
- echo data
- penetrating radar
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 47
- 238000000354 decomposition reaction Methods 0.000 title claims abstract description 27
- 238000000034 method Methods 0.000 claims abstract description 26
- 230000003247 decreasing effect Effects 0.000 claims abstract description 8
- 230000000149 penetrating effect Effects 0.000 claims description 49
- 238000013178 mathematical model Methods 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 6
- 239000000523 sample Substances 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 2
- 238000002592 echocardiography Methods 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000003709 image segmentation Methods 0.000 description 2
- 229910052755 nonmetal Inorganic materials 0.000 description 2
- 230000001629 suppression Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/885—Radar or analogous systems specially adapted for specific applications for ground probing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Geophysics And Detection Of Objects (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The present invention relates to a kind of GPR buried target detection method based on two-dimensional empirical mode decomposition, specifically include：1) two-dimensional empirical mode decomposition is carried out to the detection echo data of GPR, obtains two-dimensional empirical modal function component IMF and 1 residual error that K frequency is successively decreased successively；2) it regard the average of preceding M (M≤K) two-dimensional empirical modal function components as the characteristic value for detecting echo data；3) extreme point of the detection echo data characteristic value is obtained, the estimate of buried target vertex position is used as；4) spread speed of the estimation electromagnetic wave in underground；5) using GPR hyperbola mathematical modeling, hyperbolic fit is carried out, the positioning of buried target position is completed in the spread speed of underground according to the estimate and electromagnetic wave of the buried target vertex position.The method of the present invention lifts clutter recognition effect while more complete reservation target information, improves the precision of target positioning.
Description
Technical Field
The invention relates to the field of ground penetrating radar detection, in particular to a ground penetrating radar underground target detection method based on two-dimensional empirical mode decomposition.
Background
The ground penetrating radar is an effective shallow underground target detection technology which is rapidly developed in recent decades, is a non-destructive detection means, has the advantages of high detection speed, high resolution, convenience and flexibility in operation, low detection cost and the like, and is widely applied to detection and positioning of underground targets such as cavities, pipelines, mines and the like.
The two-dimensional echo data detected by the ground penetrating radar is called B-Scan data which is a data basis for subsequent radar signal processing, target identification and interpretation, and the ground penetrating radar target positioning technology is also based on the B-Scan data. The clutter in the B-Scan data of the ground penetrating radar is the most significant for realizing accurate positioning of the target. The clutter of the ground penetrating radar can be regarded as various echoes except the target echo, and generally comprises an antenna direct wave, a surface echo, an echo generated by a underground inhomogeneous medium, an echo generated by a false target and the like. The clutter of the ground penetrating radar makes accurate detection of underground targets difficult, especially for shallow buried targets, target echoes are weaker components compared with earth surface echoes, time delay between the target echoes and the earth surface echoes is small, and the target echoes are easily submerged by the clutter of strong earth surface echoes. Therefore, clutter suppression of the ground penetrating radar is the primary task for achieving accurate positioning of the ground penetrating radar target.
The common positioning method is mainly based on hyperbolic curve extraction of a B-scan image, and the target depth is calculated according to the velocity of the extracted hyperbolic curve. Mainly comprises the following steps: based on the extraction of the hyperbola by the neural network, more data are needed for training, and online detection is not easy to realize; by adopting a fuzzy clustering mode identification method, for shallow detection possibly existing in both a metal pipeline and a non-metal pipeline, a false alarm is easily generated, and a non-metal pipeline target is easily missed. When the method based on image segmentation and Hough transform is applied to a shallow detection pipeline, stronger clutter and target echoes cannot be effectively distinguished; when the method based on image segmentation and template matching is applied to a shallow detection pipeline, the sizes of pipe diameters are possibly changeable, so that the corresponding templates are more, and the algorithm operation time is longer; the curve detection based on morphology is to perform detection and judgment according to the gray value of an image, a target area can be judged, but a plurality of curves are obtained, and the curves need to be processed when the next calculation is performed.
Disclosure of Invention
The invention provides a ground penetrating radar underground target detection method based on two-dimensional empirical mode decomposition, and aims to solve the problems that a target positioning method in the prior art is complex and low in positioning accuracy.
In order to solve the technical problems, the technical scheme of the invention is as follows:
1) performing two-dimensional empirical mode decomposition on B-Scan detection echo data of the ground penetrating radar to obtain K two-dimensional empirical mode function components IMF with sequentially decreasing frequency and 1 residual error;
2) taking the mean value of the first M (M is less than or equal to K) two-dimensional empirical mode function components as the characteristic value of the detection echo data;
3) acquiring an extreme point of the characteristic value of the detection echo data as an estimated value of the vertex position of the underground target;
4) estimating the propagation speed of the electromagnetic wave in the underground;
5) and according to the estimated value of the top position of the underground target and the propagation speed of the electromagnetic wave in the underground, performing hyperbolic fitting by using a hyperbolic mathematical model of the ground penetrating radar to complete positioning of the underground target position.
The specific process of performing two-dimensional empirical mode decomposition on the detection echo data of the ground penetrating radar in the step 1) is as follows:
a) firstly, determining detection echo data I of ground penetrating radarresAll extreme points of (1) are specifically determined by adopting an eight-neighborhood methodresAll maxima and minima of the image;
b) detection echo data I of ground penetrating radarresAll the extreme points of (2) are interpolated by using the radial basis function, and the interpolation is finishedRespectively using E as the maximum value point and the minimum value pointIAnd ESRepresenting, obtaining detection echo data I after curve fittingresUpper and lower envelopes of;
the specific form of the radial basis function RBF is:
wherein: s is the Radial Basis Function (RBF), pmBeing a polynomial of low degree, e.g. linear or quadratic or m of d variablesthPolynomial, | | · | |, represents the euclidean norm. Lambda [ alpha ]iIs the RBF coefficient and Φ is the real-valued function, often referred to as the center of the radial basis function RBF.
c) Averaging upper and lower envelopes
EM＝(EI+ES)/2； (2)
d) From raw probe echo data IresMinus EMObtaining new detection echo data
e) Judging according to IMF judgment conditionsWhether it is an IMF or not, if it is an IMF, let the first two-dimensional empirical mode function component (IMF)Is composed ofResidual errorOtherwise, useIn place of IresRepeating steps a) to d) until a decision is madeFor an IMF, let the first two-dimensional empirical mode function component (IMF)Is composed ofResidual errorAnd repeating the steps until K two-dimensional empirical mode function components IMF with sequentially decreasing frequency and 1 residual error are obtained.
The IMF determination condition is to set an SD threshold,
wherein,andto pass through the iththAs a result of the successive two attenuations of the individual modes,denotes the iththThe m row and n column values of the j-th attenuation of each mode decomposition, M, N, represent the row and column numbers of the two-dimensional ground penetrating radar image. In practice, a threshold value T is preset, and when SD is smaller than the threshold value, the iteration is stopped, namely, the judgment is madeIs an IMF.
In the step 3), the target echo is known to have hyperbolic characteristic according to the ground penetrating radar principle, and the ordinate of the vertex of the hyperbolic represents the shortest echo time delay, namely the ground penetrating radar is closest to the target at the measuring point. Therefore, the characteristic value of the selected detection echo data is scanned column by column, the minimum value of the ordinate is selected, and the ordinate of the vertex of the hyperbola is determined. The abscissa of the hyperbola represents the corresponding horizontal position of the object. And in the step 4), estimating the propagation speed of the electromagnetic wave in the underground by adopting a frequency beam offset method and combining a minimum entropy technology.
The hyperbolic mathematical model of the ground penetrating radar in the step 5) is as follows:
where x denotes the antenna position, x0Horizontal coordinates representing the position of the apex of the target, v represents the propagation velocity of the electromagnetic wave in the ground, t0Indicates the position of the antenna as x0T represents the target reflection echo time delay with the antenna position x.
The method for detecting the underground target of the ground penetrating radar based on the two-dimensional empirical mode decomposition comprises the steps of firstly carrying out the two-dimensional empirical mode decomposition on detection echo data of the ground penetrating radar to obtain a plurality of single-component signals, then extracting characteristic values of the detection echo data according to the single-component signals, estimating the position of the top point of the target, and then carrying out hyperbolic curve fitting by combining the estimated wave velocity and the ground penetrating radar principle to complete target positioning. The method can improve clutter suppression effect while completely retaining target information, and improve target positioning precision.
Drawings
FIG. 1 is a flowchart of a method for locating an underground target of a ground penetrating radar in the embodiment;
FIG. 2 is a flowchart of a two-dimensional empirical mode decomposition algorithm in accordance with the present embodiment;
FIG. 3 is a B-Scan echo image actually measured by the ground penetrating radar in the embodiment;
FIG. 4 is a diagram illustrating an image after a first IMF is extracted by two-dimensional empirical mode decomposition according to the present embodiment;
FIG. 5 is a diagram illustrating a relationship between a radar antenna and a target B-Scan echo in the present embodiment;
FIG. 6 is a graph showing the effect of the curve fitting on the original B-Scan image in this embodiment.
Detailed Description
The technical scheme of the invention is explained in detail in the following with the accompanying drawings.
As shown in fig. 1, the method for detecting a ground penetrating radar underground target based on two-dimensional empirical mode decomposition of the embodiment includes the following steps:
1) performing two-dimensional empirical mode decomposition on detection echo data of the ground penetrating radar to obtain K two-dimensional empirical mode function components IMF with sequentially decreasing frequency and 1 residual error;
2) taking the mean value of the first M (M is less than or equal to K) two-dimensional empirical mode function components as the characteristic value of the detection echo data;
3) acquiring an extreme point of the characteristic value of the detection echo data as an estimated value of the vertex position of the underground target;
4) estimating the propagation speed of the electromagnetic wave in the underground;
5) and according to the estimated value of the top position of the underground target and the propagation speed of the electromagnetic wave in the underground, performing hyperbolic fitting by using a hyperbolic mathematical model of the ground penetrating radar to complete positioning of the underground target position.
The above steps are described in detail below:
in step 1), performing two-dimensional empirical mode decomposition on the B-Scan echo data of the ground penetrating radar, where the empirical mode decomposition process may be a decomposition process in the prior art, as shown in fig. 2, the following two-dimensional empirical mode decomposition process is preferably adopted in this embodiment:
step1 firstly determining detection echo data I of ground penetrating radarresAll extreme points of (1) are specifically determined by adopting an eight-neighborhood methodresAll maxima and minima of the image;
detection echo data I of Step2 for ground penetrating radarresAll the extreme points are interpolated by using the radial basis function, and the interpolated maximum point and minimum point are respectively interpolated by using EIAnd ESRepresenting, obtaining detection echo data I after curve fittingresUpper and lower envelopes of;
the specific form of the radial basis function RBF is:
wherein: s is the Radial Basis Function (RBF), pmBeing a polynomial of low degree, e.g. linear or quadratic or m of d variablesthPolynomial, | | · | |, represents the euclidean norm. Lambda [ alpha ]iIs the RBF coefficient and Φ is the real-valued function, often referred to as the center of the radial basis function RBF.
Step3 calculating average value E of upper and lower envelopesM＝(EI+ES)/2；
Step4 from the raw probe echo data IresMinus EMObtaining new detection echo data
Step5 is judged according to IMF judgment conditionWhether it is an IMF or not, if it is an IMF, let the first two-dimensional empirical mode function component (IMF)Is composed ofResidual errorOtherwise, useIn place of IresRepeating steps a) to d) until a decision is madeFor an IMF, let the first two-dimensional empirical mode function component (IMF)Is composed ofResidual errorAnd repeating the steps until K two-dimensional empirical mode function components IMF with sequentially decreasing frequency and 1 residual error are obtained.
The IMF determination condition is to set an SD threshold,
wherein,andis a drug infusionThe iththThe results of two successive attenuations of the individual modes, M, N representing the number of rows and columns of the two-dimensional image,denotes the iththThe data of the m row and n column of the j attenuation of the mode decomposition. In practice, a threshold value T is preset, and when SD is smaller than the threshold value, the iteration is stopped, namely, the judgment is madeIs an IMF.
And finally obtaining K two-dimensional empirical mode function components IMF with frequencies decreasing from high to low and 1 residual error according to the method.
In the embodiment of step 2), the mean value of the frequency components of the first M (M ≦ K) two-dimensional empirical mode functions is preferably used as the feature value of the detected echo data, as shown in fig. 4, and the feature value can suppress clutter while retaining the target position.
In the step 3), the target echo is known to have hyperbolic characteristic according to the ground penetrating radar principle, and the ordinate of the vertex of the hyperbolic represents the shortest echo time delay, namely the ground penetrating radar is closest to the target at the measuring point. Therefore, the characteristic value of the detected echo data selected by scanning line by line is selected, the minimum value is selected, the ordinate of the vertex of the hyperbola is determined, and the abscissa of the hyperbola represents the corresponding horizontal position of the target.
As for the step 4), as shown in fig. 5, a hyperbolic mathematical model of the ground penetrating radar is obtained according to the principle of the ground penetrating radar:
where x denotes the antenna position, x0Horizontal coordinates representing the position of the apex of the target, v represents the propagation velocity of the electromagnetic wave in the ground, t0Indicates the position of the antenna as x0T represents the target reflection with the antenna position xAnd echo time delay. Therefore, the vertex coordinates (x) are obtained0,t0) And the wave velocity v, wherein three parameters to be estimated are respectively used for solving the vertex coordinates (x)0,t0) And a wave velocity v.
The target vertex coordinates (x) have been estimated in the above step 3)0,t0) The following details the estimation process of the wave velocity v:
a) selecting a minimum value V of wave speedminCalculating an offset result under a given speed value by using a frequency wave number offset method;
b) the entropy of the shifted image is calculated according to the following formula, denoted as E1；
c) Selecting a speed step Δ V, using Vmin+ΔV，Vmin+2ΔV，Vmin+3 Δ V, …, performing offset calculation on the detected echo data processed in step 2) until the velocity reaches the maximum predetermined value VmaxIf n speed parameters are shared, the image entropy after the offset is calculated, and the result is recorded as E2，E3…, up to En。
d) And finding the speed value corresponding to the entropy value minimum point, wherein the value is the most reasonable offset speed parameter v.
The present embodiment preferably estimates the wave velocity v in the above manner, and as other embodiments, there are many ways to estimate the wave velocity v in the prior art, and detailed description is omitted here.
And 5) substituting the target vertex position estimated in the step 3) and the speed v estimated in the step 4) into a hyperbolic mathematical model of the ground penetrating radar, fitting a hyperbola, and finishing the positioning of the ground penetrating radar target as shown in fig. 6.
The specific embodiments are given above, but the present invention is not limited to the described embodiments. The basic idea of the present invention lies in the above basic scheme, and it is obvious to those skilled in the art that no creative effort is needed to design various modified models, formulas and parameters according to the teaching of the present invention. Variations, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention, and still fall within the scope of the invention.
Claims (5)
1. A ground penetrating radar underground target detection method based on two-dimensional empirical mode decomposition is characterized by comprising the following steps:
1) performing two-dimensional empirical mode decomposition on B-Scan detection echo data of the ground penetrating radar to obtain K two-dimensional empirical mode function components IMF with sequentially decreasing frequency and 1 residual error;
2) taking the mean value of the first M (M is less than or equal to K) two-dimensional empirical mode function components as the characteristic value of the detection echo data;
3) acquiring an extreme point of the characteristic value of the detection echo data as an estimated value of the vertex position of the underground target;
4) estimating the propagation speed of the electromagnetic wave in the underground;
5) and according to the estimated value of the top position of the underground target and the propagation speed of the electromagnetic wave in the underground, performing hyperbolic fitting by using a hyperbolic mathematical model of the ground penetrating radar to complete positioning of the underground target position.
2. The method for detecting the underground target of the ground penetrating radar based on the two-dimensional empirical mode decomposition according to claim 1, wherein the specific process of performing the two-dimensional empirical mode decomposition on the detection echo data of the ground penetrating radar in the step 1) is as follows:
a) firstly, determining detection echo data I of ground penetrating radarresAll extreme points of (a);
b) detection echo data I of ground penetrating radarresAll the extreme points are interpolated by using the radial basis function, and the interpolated maximum point and minimum point are respectively interpolated by using EIAnd ESRepresenting, obtaining detection echo data I after curve fittingresUpper and lower envelopes of;
c) calculating the average value E of the upper and lower envelopesM＝(EI+ES)/2；
d) From raw probe echo data IresMinus EMObtaining new detection echo data
e) Determining condition judgment according to two-dimensional empirical mode function (IMF)Whether the two-dimensional empirical mode function component IMF is determined, if the two-dimensional empirical mode function component IMF is determined, the first two-dimensional empirical mode function component IMF is determinedIs composed ofResidual errorOtherwise, useIn place of IresRepeating steps a) to d) until a decision is madeFor a two-dimensional empirical mode function component IMF, let the first two-dimensional empirical mode function component IMFIs composed ofResidual errorAnd repeating the steps until K two-dimensional empirical mode function components IMF with sequentially decreasing frequency and 1 residual error are obtained.
3. The method for detecting the underground target of the ground penetrating radar based on the two-dimensional empirical mode decomposition according to claim 1, wherein the estimation value of the vertex position of the underground target in the step 3) is obtained by: and scanning the selected characteristic values of the detected echo data row by row, selecting the minimum value, determining the ordinate of the vertex of the hyperbola, and representing the horizontal position corresponding to the target by the abscissa of the hyperbola.
4. The method for detecting the underground target of the ground penetrating radar based on the two-dimensional empirical mode decomposition according to claim 1, wherein the propagation speed of the electromagnetic wave in the underground is estimated in the step 4) by adopting a frequency beam shifting method and combining a minimum entropy technology.
5. The method for detecting the underground target of the ground penetrating radar based on the two-dimensional empirical mode decomposition according to claim 1, wherein the hyperbolic mathematical model of the ground penetrating radar in the step 5) is as follows:
<mrow> <mfrac> <msup> <mi>t</mi> <mn>2</mn> </msup> <msubsup> <mi>t</mi> <mn>0</mn> <mn>2</mn> </msubsup> </mfrac> <mo>-</mo> <mfrac> <mrow> <mn>4</mn> <msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>-</mo> <msub> <mi>x</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> <mrow> <msup> <mi>v</mi> <mn>2</mn> </msup> <msubsup> <mi>t</mi> <mn>0</mn> <mn>2</mn> </msubsup> </mrow> </mfrac> <mo>=</mo> <mn>1</mn> </mrow>
where x denotes the antenna position, x0Horizontal coordinates representing the position of the apex of the target, v represents the propagation velocity of the electromagnetic wave in the ground, t0Indicates the position of the antenna as x0T represents the target reflection echo time delay with the antenna position x.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510570738.6A CN105182328B (en) | 2015-09-09 | 2015-09-09 | A kind of GPR buried target detection method based on two-dimensional empirical mode decomposition |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510570738.6A CN105182328B (en) | 2015-09-09 | 2015-09-09 | A kind of GPR buried target detection method based on two-dimensional empirical mode decomposition |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105182328A CN105182328A (en) | 2015-12-23 |
| CN105182328B true CN105182328B (en) | 2017-08-25 |
Family
ID=54904527
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510570738.6A Expired - Fee Related CN105182328B (en) | 2015-09-09 | 2015-09-09 | A kind of GPR buried target detection method based on two-dimensional empirical mode decomposition |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105182328B (en) |
Families Citing this family (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106019257B (en) * | 2016-08-05 | 2018-07-31 | 中国船舶重工集团公司第七一九研究所 | The interpolation method of feature when based on high-frequency ground wave radar Current Observations result sky |
| CN106405660A (en) * | 2016-08-26 | 2017-02-15 | 国脉科技股份有限公司 | Buried depth detecting device and method of communication pipeline |
| CN106443674B (en) * | 2016-09-23 | 2019-03-22 | 中国地质大学（武汉） | A kind of Ground Penetrating Radar Velocity Estimation based on diffraction and imaging and minimum entropy technique |
| CN106772636B (en) * | 2016-11-10 | 2018-07-24 | 中国矿业大学(北京) | The detection method and device of Ground Penetrating Radar discontinuum |
| EP3574340B1 (en) * | 2017-01-27 | 2024-06-26 | Massachusetts Institute of Technology | Method and system for localization of a vehicle using surface penetrating radar |
| CN107329137B (en) * | 2017-07-04 | 2019-08-23 | 河南工业大学 | Ground Penetrating Radar buried target localization method and system based on box spline wavelets frame |
| CN107346023A (en) * | 2017-07-04 | 2017-11-14 | 山东工商学院 | A kind of GPR hyperbolic ripple conspicuousness mapping method based on moment characteristics |
| CN107358617B (en) * | 2017-08-07 | 2020-03-20 | 中南大学 | Method for detecting target vertex in ground penetrating radar recording profile |
| CN107861164B (en) * | 2017-11-01 | 2020-04-03 | 中国煤炭地质总局勘查研究总院 | Three-dimensional ground penetrating radar and data processing method and device thereof |
| CN107766837A (en) * | 2017-11-07 | 2018-03-06 | 蔡璟 | The gardens maintenance system that a kind of distinguished point based compares |
| CN108828027A (en) * | 2018-04-23 | 2018-11-16 | 云南电网有限责任公司临沧供电局 | A kind of saturating ground electromagnetic wave detecting method and device of the inverting of underground utilities multi information |
| CN108627875A (en) * | 2018-05-14 | 2018-10-09 | 中国神华能源股份有限公司 | Radar migration velocity determines and migration processing method, storage medium, electronic equipment |
| CN108776336B (en) * | 2018-06-11 | 2022-06-03 | 电子科技大学 | EMD-based adaptive through-wall radar static human body target positioning method |
| CN108646229A (en) * | 2018-06-14 | 2018-10-12 | 北京师范大学 | Underground column reflector inclination angle detection method |
| CN108986083B (en) * | 2018-06-28 | 2020-08-04 | 西安电子科技大学 | SAR image change detection method based on threshold optimization |
| CN109669169B (en) * | 2018-12-05 | 2022-11-08 | 南京信息工程大学 | Method for detecting weak target signal under sea clutter background |
| CN110471066B (en) * | 2019-07-25 | 2022-04-05 | 东软睿驰汽车技术（沈阳）有限公司 | Position determination method and device |
| CN110531351B (en) * | 2019-08-16 | 2023-09-26 | 山东工商学院 | GPR image hyperbolic wave top detection method based on Fast algorithm |
| CN111044975A (en) * | 2019-12-10 | 2020-04-21 | 北京无线电计量测试研究所 | Method and system for positioning earth vibration signal |
| CN111257952B (en) * | 2020-01-20 | 2022-07-05 | 广州燃气集团有限公司 | Underground pipeline identification system and method based on wave-absorbing material |
| CN112666552B (en) * | 2020-10-29 | 2023-04-25 | 西安交通大学 | Ground penetrating radar data background clutter self-adaptive removing method |
| CN113567946B (en) * | 2021-07-20 | 2023-08-29 | 同济大学 | Method for detecting real target and virtual image of millimeter wave radar |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103954944A (en) * | 2014-05-14 | 2014-07-30 | 武汉大学 | Radio-frequency interference suppression method of high-frequency ground wave radar |
| CN104766090A (en) * | 2015-03-17 | 2015-07-08 | 山东工商学院 | Ground penetrating radar data visualization method based on BEMD and SOFM |
-
2015
- 2015-09-09 CN CN201510570738.6A patent/CN105182328B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103954944A (en) * | 2014-05-14 | 2014-07-30 | 武汉大学 | Radio-frequency interference suppression method of high-frequency ground wave radar |
| CN104766090A (en) * | 2015-03-17 | 2015-07-08 | 山东工商学院 | Ground penetrating radar data visualization method based on BEMD and SOFM |
Non-Patent Citations (3)
| Title |
|---|
| Texture analysis based on the Bidimensional Empirical Mode Decomposition with Gray-level Co-occurrence models;J.C.Nunes 等;《IEEE》;20031231;633-635 * |
| 一维HHT变换在探地雷达数据处理中的应用;王超 等;《工程地质学报》;20150425;第23卷(第2期);328-334 * |
| 基于改进EMD-小波阈值联合去噪的城市地下管线识别与定位;刘晓艳 等;《中国安全生产科学技术》;20150630;第11卷(第6期);56-62 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105182328A (en) | 2015-12-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105182328B (en) | A kind of GPR buried target detection method based on two-dimensional empirical mode decomposition | |
| CN105005042B (en) | A kind of GPR buried target localization method | |
| Merazi-Meksen et al. | Mathematical morphology for TOFD image analysis and automatic crack detection | |
| CN110866545A (en) | Method and system for automatically identifying pipeline target in ground penetrating radar data | |
| CN107358617B (en) | Method for detecting target vertex in ground penetrating radar recording profile | |
| CN102176000B (en) | Sea clutter suppression method for marine radar | |
| CN108469608B (en) | Method for accurately estimating Doppler centroid of moving platform radar | |
| CN106936964B (en) | A kind of mobile phone screen angular-point detection method based on Hough transformation template matching | |
| CN113359101B (en) | Underground target detection method, system and computer storage medium | |
| CN105403883A (en) | Ground penetrating radar underground target position detection method | |
| CN108168564A (en) | A kind of Data Association based on LHD grey relational grades | |
| CN112130142B (en) | Method and system for extracting micro Doppler features of complex moving target | |
| CN101498788A (en) | Target rotation angle estimating and transverse locating method for inverse synthetic aperture radar | |
| CN105044785B (en) | A kind of GPR Electromagnetic Survey of Underground Pipelines method based on fuzzy clustering Yu Hough transform | |
| CN107390213B (en) | A kind of time lag curve extracting method of the Ground Penetrating Radar record section based on sliding window | |
| CN105699952A (en) | Double-quantile estimation method for sea clutter K distribution shape parameter | |
| CN103886606B (en) | SAR image segmentation method based on joint generalized gamma distribution parameters | |
| CN105738880A (en) | Moment estimation method for reverse inverse gauss texture composite compound gauss sea clutter amplitude distributed parameters | |
| CN104569923B (en) | Velocity restraint-based Hough transformation fast track starting method | |
| CN101872484A (en) | Method for detecting self-adaptive growth of a plurality of dim target tracks in image domain | |
| Milisavljević et al. | Improving mine recognition through processing and Dempster–Shafer fusion of ground-penetrating radar data | |
| CN105652256B (en) | A kind of high-frequency ground wave radar TBD methods based on polarization information | |
| CN116626685B (en) | River sediment real-time monitoring method and system based on machine learning | |
| CN111399038B (en) | Slope parameter extraction method and device and computer readable storage medium | |
| CN113848556A (en) | Multi-beam sounding sonar beam image-based water depth range rapid extraction method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170825 Termination date: 20190909 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |