CN117630924B - Three-dimensional imaging method and device for through-wall radar based on priori information - Google Patents
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Abstract
The invention provides a three-dimensional imaging method and device of a through-wall radar based on priori information, which belong to the technical field of radars, consider three-dimensional characteristics of a wall structure, characterize local similarity of images through 3D-TV constraint, inhibit influence of wall artifacts and random half-points by using group sparse constraint, and can keep global coherence of the wall structure under the influence of noise by combining tensor Tucker decomposition constraint, so that perspective three-dimensional imaging quality is improved. According to the invention, the three-dimensional characteristics of the wall structure are considered in the solving process, so that the solving result is more consistent with the real wall structure.
Description
Technical Field
The invention belongs to the technical field of radars, and particularly relates to a three-dimensional imaging method and device of a through-wall radar based on priori information.
Background
The through-wall radar sensing technology acquires the internal information of the building by detecting and sensing the outer side of the building, and has important practical significance and research value in the military field and the civil field. Because of the importance of the wall structure in the through-wall perception, through-wall structure imaging technology gradually enters the sight of researchers, and the research target is to detect and perceive through multiple angles on the outer side of a building, so that partial or whole structural layout results of the whole building are inverted.
The research literature on perspective building structural layout imaging is found that the perspective structural layout imaging can be divided into perspective imaging and scattering imaging according to the system. The receiving and transmitting module of the radar system under the scattering imaging is positioned in the same side range of the building, electromagnetic waves penetrate through the wall structure and are scattered, then the electromagnetic waves are received by the receiver, the receiving end obtains a backward scattering diagram of the wall structure through signal processing of echoes of the radar, and then the image results under a plurality of view angles are fused, so that an overall structure layout diagram is obtained. Compared with a scattering imaging mode, the transmitting end and the receiving end of the radar in the perspective imaging mode are respectively arranged on two sides of a building, an electromagnetic wave wall body is received by the receiving end after attenuation, and the receiving end inverts the structure by utilizing the attenuation of the electromagnetic wave by utilizing the wall body structural degree to obtain the overall structure layout result. The two working modes respectively utilize the scattering and transmission of electromagnetic waves to perform structural inversion, and the two working modes have advantages and disadvantages and have no special description. For perspective type through-wall layout imaging technology, a space sampling method and a sparse imaging method under a sparse view angle are generally adopted, space sampling is firstly carried out along a sparse and small amount of directions to obtain attenuation values of electromagnetic waves, then a solving model between attenuation value vectors and two-dimensional or three-dimensional arrays of a wall structure in all sampling directions is established, and a two-dimensional or three-dimensional wall layout structure result of a building is obtained by solving the model. When perspective imaging is carried out, because the sparse angle observation is carried out, the established solving model is a seriously ill-conditioned underdetermined equation set, and the problems can be reduced to a ill-conditioned equation solving problem, so that the reconstructed image detection result has obvious phenomena such as artifacts, noise and the like.
Disclosure of Invention
Aiming at the phenomenon that artifacts exist in a reconstruction result caused by sparse angle sampling in perspective three-dimensional imaging, the invention provides a three-dimensional imaging method of a wall penetrating radar based on priori information, which considers three-dimensional characteristics of a wall structure, characterizes local similarity of images through 3D-TV constraint, suppresses the influence of the wall artifacts and random half points by using group sparse constraint, and can keep global coherence of the wall structure under the influence of noise by combining tensor Tucker decomposition constraint, so that perspective three-dimensional imaging quality is improved. According to the invention, the three-dimensional characteristics of the wall structure are considered in the solving process, so that the solving result is more consistent with the real wall structure.
The method is realized by the following technical scheme:
a three-dimensional imaging method of a through-wall radar based on priori information comprises the following steps:
Step 1, obtaining received signal attenuation value vectors in a plurality of sampling directions;
Step 2, obtaining received signal attenuation value vectors in all directions and at all heights by adopting a mode of two-dimensional tomography and then elevation movement, and establishing a perspective three-dimensional imaging observation matrix based on an Rytov approximate model;
Step 3, establishing an objective function by combining prior information of the wall structure;
Step 4, aiming at the objective function established in the step 3, solving the objective function by utilizing alternate direction projection calculation to obtain an estimation result of the parameter to be inverted;
And 5, after obtaining an estimation result of the inversion parameter, performing filtering processing on the estimation result, setting a threshold value, setting a pixel smaller than the threshold value to zero, and setting a pixel larger than the threshold value to 1, so as to obtain a binarized wall layout result.
Further, in the step 2, obtaining the observation matrix based on the Rytov approximation model includes: under the Rytov approximation model, the relation between the signal intensity at the receiving end and the pixel units between the imaging areas is obtained through the Rytov approximation model; the relationship between the total field at the receiving end and the pixels between the imaging regions under the Rytov approximation model is as follows:
Where E t(rn,tn) represents the total field at the receiving end, φ s(rn,tn) represents the fringe field at the receiving end, j represents the imaginary number, j 2＝-1,k0 denotes a wavelength, ++. D () dr 'denotes a volume fraction with a region D as an integral region, g (r n, r') is a green's function, E i(r′,tn) represents the incident field at position r', r n,tn represents the position of the transmitting end and the position of the receiving end, respectively, j represents an imaginary number, E i(rn,tn) represents the incident field at the receiving end, representing the total field at the receiving end when there is no object in the imaging region; o (r ') represents the target contrast function at position r' and is expressed as: o (r ') =ε r(r′)-1,εr (r') is the complex relative permittivity of the target; and (3) conjugate is taken from two ends of the formula (1) and multiplied to obtain the product:
Where P (r n,tn) represents the energy at the receiving end, im () represents the imaginary part taking operation;
By the above, the power attenuation due to the wall structure is modeled as:
Pr(rn,tn)＝|Et(rn,tn)|2-|Ei(rn,tn)|2＝-20logeIm(φs(rn,tn)) (3)
Wherein, P r(rn,tn) represents the signal attenuation energy due to the wall at the receiving end;
grid discretization is carried out on the imaging area, and a matrixed signal model is obtained as follows:
P＝WO (4)
wherein P is a vector composed of received signal power attenuation values, W is an observation matrix established based on Rytov approximation model, and O is a vector composed of parameters to be inverted of an imaging region grid; wherein the element expression of the observation matrix is as follows:
Where n, r 'represent the nth row and the r' column of the matrix, respectively, the lambda parameter is used to define the range size, t and a are intermediate parameters, a=20log 10 e respectively, All represent a first class of zero-order hanker functions.
Further, the propagation range of electromagnetic waves is limited to a certain range by using an elliptical model, and only grid cells inside the ellipse are considered.
The invention also provides a three-dimensional imaging device of the through-wall radar based on prior information, which comprises a transmitting module, a data transmission module and a receiving module, wherein the data transmission module is respectively connected with the transmitting module, the receiving module and the notebook computer and is used for carrying out data communication between the notebook computer and the transmitting module and between the notebook computer and the receiving module; the transmitting module is used for transmitting the WIFI frequency band signal, the receiving module is used for receiving the WIFI frequency band signal transmitted by the transmitting module, and the received signal attenuation value vector is received by the notebook computer through the data transmission module.
Further, the mobile scanning device also comprises a mobile slide rail module and a panel antenna, wherein the transmitting module, the panel antenna and the receiving module are respectively fixed on the mobile slide rail module by utilizing a rigid structure bracket and are used for mobile scanning to acquire data.
The beneficial effects are that:
1) Aiming at the perspective three-dimensional imaging technology, the invention provides the three-dimensional imaging method of the through-wall radar based on prior information, the prior characteristics of the wall structure are fully considered in the solving process, and the constraint item about the prior characteristics of the wall structure is added in the solving objective function, so that the three-dimensional layout result of the wall obtained by solving is more consistent with the real layout result.
2) The algorithm disclosed by the invention is used for carrying out processing aiming at perspective three-dimensional imaging, can be also used for scattering three-dimensional through-wall imaging, and has a certain reference value for scattering three-dimensional imaging.
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FIG. 1 is a perspective three-dimensional imaging geometry schematic; wherein, (a) is a data acquisition schematic diagram, and (b) is a two-dimensional scanning schematic diagram;
FIG. 2 is an algorithm flow chart of a three-dimensional imaging method of a through-wall radar based on prior information according to the present invention;
Fig. 3 is a schematic diagram of a three-dimensional imaging device of a through-wall radar based on prior information according to the present invention.
Detailed Description
The invention will now be described in detail with reference to the accompanying drawings and examples.
Fig. 1 is a schematic three-dimensional imaging geometry diagram of a through-wall radar based on prior information, where T and R respectively represent a transmitting antenna and a receiving antenna, D represents an imaging area, T represents a transmitting antenna, R represents a receiving antenna, and the transmitting antenna and the receiving antenna are disposed on a movable sliding rail platform and respectively observe at multiple angles along a first path (0 degree), a second path (45 degrees), a third path (90 degrees) and a fourth path (135 degrees), so as to collect received signal attenuation value vectors at different angles.
Referring to fig. 1 and 2, the three-dimensional imaging method of the through-wall radar based on priori information of the invention specifically comprises the following steps:
Step 1, a signal attenuation value vector received in each sampling direction (N sampling directions in total) is acquired. When data acquisition is performed, the intensity value of the received signal in the condition without the target can be obtained in advance, and then the intensity value of the received signal when the target exists is acquired, wherein the difference between the intensity value and the intensity value is the intensity attenuation value of the received signal caused by the target. In the experiment, the received signal strength attenuation value vectors under four observation angles of 0 degree, 45 degrees, 90 degrees and 135 degrees are obtained, the received signal strength attenuation value vectors under different heights are obtained by moving the height of the antenna, and the received signal attenuation value vectors obtained in all sampling directions and different heights are arranged into one-dimensional vectors, so that the final received signal attenuation value vector P is obtained.
And 2, establishing an observation matrix W. According to step 1, a linear model between the intensity of a received signal and the relative dielectric constant of a target in an electromagnetic wave action area is obtained based on an Rytov approximation model, and in order to reduce the influence of non-line-of-sight propagation of electromagnetic waves on the received signal, a directional receiving and transmitting antenna is adopted to limit the main energy of the electromagnetic waves within a certain range. When the observation matrix is calculated, an ellipse model is adopted to calculate the element value of the observation matrix.
And 3, establishing an objective function. In order to solve the problem that the reconstruction result has the influence of artifacts, noise points and the like due to sparse view sampling, the invention provides perspective three-dimensional imaging combined with prior information of a wall structure. For the results obtained in step 1 and step 2, based on the received signal attenuation value vector P obtained in step 1 and the observation matrix W obtained in step 2, a linear expression p=wo between the received signal attenuation value vector obtained in step 2 and the target relative permittivity is obtained, and O represents the target relative permittivity vector in the imaging region. The above linear expression equation is ill-conditioned, in that the number of observations is much smaller than the number of objects to be solved. Aiming at the problems, a regularization solving method can be adopted to realize the unique solution of the linear expression equation of the pathological condition, and the following objective function is established:
wherein argmin represents the minimum value of the objective function, Third-order tensor representing target relative permittivity, P is a received signal attenuation value vector, W is an observation matrix,/>Represents the regularization term and λ represents a penalty factor to balance the degree of action of the regularization term. And 2 represents a two-norm. The objective function establishes a proper expression by combining the constraint term of the prior information of the wall body, namely, considering the second expression at the right end of the equation, and combining the characteristics of the wall body structure. The invention considers the following characteristics of the wall:
Local similarity of three-dimensional wall structures. The wall structures are the same in material, occupy the space position of a smaller part in the whole three-dimensional space, and have obvious edges. The wall structure has the characteristics characterized by 3D-TV, and the mathematical expression is as follows:
Wherein, Third-order tensor/>, representing the relative permittivity of the targetI, j, k represent the element index of the third-order tensor in three dimensions, respectively.
The image of the three-dimensional wall structure has a set of sparse properties. Due to the limitation of the sampling of the coefficient view angle, the result under the constraint of the 3D-TV is used only to have obvious artifact phenomenon, in addition, random noise is introduced into the image due to the influence of measurement errors and environmental noise factors, and the problems are reduced by adopting the group sparse characteristic. The group sparse characteristic of the three-dimensional wall structure is represented by a certain height of the wall structure and is vertically distributed along the height direction, so that pixels on all elevations at a certain plane position are divided into one group, and the group has the sparse characteristic. The above characteristics are expressed by the following mathematical expression:
Wherein, Third-order tensor/>, representing the relative permittivity of the targetN 1,N2,N3 represent the total number of three dimensional elements of the tensor, respectively.
The image of the three-dimensional wall structure also has global coherence. Through the two regular term constraints, namely the formula (7) and the formula (8), the problems of artifacts and random spots in the image result can be greatly restrained, but the sparse constraint of the group intelligently guarantees the sparse view of the group, the reconstruction result of elements in the group cannot be guaranteed, in order to guarantee that the reconstruction result can keep the overall correlation of the wall body, the constraint is carried out by adopting Tucker decomposition, and the wall body image is considered to be low-rank at the moment. Mathematically, this can be expressed as:
wherein, x i represents the cross multiplication, Representing the kernel tensor, U i represents the factor matrix over different dimensions, i=1, 2,3; the solution process is constrained by combining the three prior features, namely, the formula (7), the formula (8) and the formula (9), so that a final objective function can be obtained as follows:
Wherein, Representing tensor difference, lambda 1,λ2 represents the penalty factor. /(I)And/>Is the variable that needs to be updated.
And 4, solving an objective function. Solving the objective function by adopting an alternate direction projection algorithm, wherein the alternate direction projection method changes the optimization problem into an optimization problem comprising a plurality of sub-problems, and the method comprises the following steps:
Sub problem 1, variable Variable U i optimization problem:
Wherein, Is a multiplier vector, β 3 is a penalty factor, is an inner product symbol, and F represents the Frobenius norm.Representing when the objective function takes the minimum value/>U i takes on the value.
The solution can be performed by a higher-order orthogonal iterative algorithm.
Sub problem 2, variableOptimization problem:
Variable/>, representing minimum value of objective function Is a value of (a). Wherein/>Representing 1 norm of tensor,/>Is a multiplier vector,/>Representing tensor difference, β 1 is a penalty factor, which can be solved by a soft threshold method.
Sub-problem 3, variablesProblem optimization:
Wherein, Variable/>, representing minimum value of objective functionIs a value of (a).
The solution of sub-problem 3 is as follows:
Wherein, Representing intermediate parameters,/>Is a multiplier vector; beta 2 represents a penalty factor;
Sub-problem 4, Optimization problem:
Wherein, Third-order tensor/>, representing the relative permittivity of the target when the objective function takes its minimum valueAnd beta 3 represents a penalty factor, and the above formula is iteratively solved by a steepest descent method.
By the method ofUi、/>And sequentially carrying out iterative updating to obtain the parameter result to be inverted. And 5, performing image filtering. The solution described above yields tensors/>Is a gray scale image, and is focused on the existence of wall structures aiming at wall layout imaging. And carrying out binarization processing on the obtained gray image result by adopting a maximum inter-class algorithm to obtain a position result related to the wall structure, wherein the unit with the wall structure is 1, and the unit without the wall structure is 0.
As shown in fig. 3, the three-dimensional imaging device of the through-wall radar based on prior information comprises a transmitting module, a data transmission module and a receiving module, wherein the data transmission module is respectively connected with the transmitting module, the receiving module and a notebook computer and is used for carrying out data communication between the notebook computer and the transmitting module and between the notebook computer and the receiving module. The transmitting module is used for transmitting the WIFI frequency band signal, the receiving module is used for receiving the wireless signal transmitted by the transmitting module, and the received signal attenuation value vector is received by the notebook computer through the data transmission module. Meanwhile, the system comprises a mobile slide rail module, and the transmitting module, the flat antenna and the receiving module are respectively fixed on the mobile slide rail module by utilizing a rigid structure bracket and are used for mobile scanning to acquire data.
Claims (5)
1. The three-dimensional imaging method of the through-wall radar based on the priori information is characterized by comprising the following steps of:
Step 1, obtaining received signal attenuation value vectors in a plurality of sampling directions;
Step 2, obtaining received signal attenuation value vectors in all directions and at all heights by adopting a mode of two-dimensional tomography and then elevation movement, and establishing a perspective three-dimensional imaging observation matrix based on an Rytov approximate model;
Step 3, establishing an objective function by combining prior information of the wall structure;
Step 4, aiming at the objective function established in the step 3, solving the objective function by utilizing alternate direction projection calculation to obtain an estimation result of the parameter to be inverted;
And 5, after obtaining an estimation result of the inversion parameter, performing filtering processing on the estimation result, setting a threshold value, setting a pixel smaller than the threshold value to zero, and setting a pixel larger than the threshold value to 1, so as to obtain a binarized wall layout result.
2. The method for three-dimensional imaging of through-wall radar based on prior information according to claim 1, wherein in the step 2, obtaining the observation matrix based on the Rytov approximation model comprises: under the Rytov approximation model, the relation between the signal intensity at the receiving end and the pixel units between the imaging areas is obtained through the Rytov approximation model; the relationship between the total field at the receiving end and the pixels between the imaging regions under the Rytov approximation model is as follows:
Where E t(rn,tn) represents the total field at the receiving end, φ s(rn,tn) represents the fringe field at the receiving end, j represents the imaginary number, j 2＝-1,k0 denotes a wavelength, ++. D () dr 'denotes a volume fraction with a region D as an integral region, g (r n, r') is a green's function, E i(r′,tn) represents the incident field at position r', r n,tn represents the position of the transmitting end and the position of the receiving end, respectively, j represents an imaginary number, E i(rn,tn) represents the incident field at the receiving end, representing the total field at the receiving end when there is no object in the imaging region; o (r ') represents the target contrast function at position r' and is expressed as: o (r ') =ε r(r′)-1,εr (r') is the complex relative permittivity of the target; and (3) conjugate is taken from two ends of the formula (1) and multiplied to obtain the product:
Where P (r n,tn) represents the energy at the receiving end, im () represents the imaginary part taking operation;
By the above, the power attenuation due to the wall structure is modeled as:
Pr(rn,tn)＝|Et(rn,tn)|2-|Ei(rn,tn)|2＝-20logeIm(φs(rn,tn)) (3)
Wherein, P r(rn,tn) represents the signal attenuation energy due to the wall at the receiving end;
grid discretization is carried out on the imaging area, and a matrixed signal model is obtained as follows:
P＝WO (4)
wherein P is a vector composed of received signal power attenuation values, W is an observation matrix established based on Rytov approximation model, and O is a vector composed of parameters to be inverted of an imaging region grid; wherein the element expression of the observation matrix is as follows:
Where n, r 'represent the nth row and the r' column of the matrix, respectively, the lambda parameter is used to define the range size, t and a are intermediate parameters, a=20log 10 e respectively, All represent a first class of zero-order hanker functions.
3. A three-dimensional imaging method of through-wall radar based on a priori information according to claim 2, wherein the propagation range of electromagnetic waves is limited to a certain range by using an elliptical model, and only grid cells inside the ellipse are considered.
4. A perspective three-dimensional imaging device for realizing a three-dimensional imaging method of a through-wall radar based on priori information according to any one of claims 1 to 3, which is characterized by comprising a transmitting module, a data transmission module and a receiving module, wherein the data transmission module is respectively connected with the transmitting module, the receiving module and a notebook computer and is used for carrying out data communication between the notebook computer and the transmitting module and the receiving module; the transmitting module is used for transmitting the WIFI frequency band signal, the receiving module is used for receiving the WIFI frequency band signal transmitted by the transmitting module, and the received signal attenuation value vector is received by the notebook computer through the data transmission module.
5. The perspective three-dimensional imaging device of claim 4, further comprising a mobile slide module and a planar antenna, wherein the transmitting module, the planar antenna and the receiving module are respectively fixed on the mobile slide module by using a rigid structural support for mobile scanning to acquire data.
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