CN113341408B - Imaging method and system based on through-wall radar clutter suppression - Google Patents

Imaging method and system based on through-wall radar clutter suppression Download PDF

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CN113341408B
CN113341408B CN202110613091.6A CN202110613091A CN113341408B CN 113341408 B CN113341408 B CN 113341408B CN 202110613091 A CN202110613091 A CN 202110613091A CN 113341408 B CN113341408 B CN 113341408B
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CN113341408A (en
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但波
王明泽
王亮
高山
翟龙军
杨富程
卢中原
尉豪轩
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Naval Aeronautical University
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    • 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
    • G01S13/887—Radar or analogous systems specially adapted for specific applications for detection of concealed objects, e.g. contraband or weapons
    • G01S13/888—Radar or analogous systems specially adapted for specific applications for detection of concealed objects, e.g. contraband or weapons through wall detection
    • 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
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • 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
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/292—Extracting wanted echo-signals
    • G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
    • 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
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers
    • G01S7/354—Extracting wanted echo-signals

Abstract

The invention relates to an imaging method and system based on through-the-wall radar clutter suppression, comprising the following steps: acquiring an original echo signal received by a through-wall radar; imaging the original echo signal to determine an original image; determining discrete coefficients of pixel vectors of the original image according to the original image; sorting the pixel vectors of the original image according to the discrete coefficients to obtain the sorted pixel vectors; determining a stepping length according to the original image; determining a pixel elimination proportion according to the stepping length; determining a first elimination ratio by using the sorted pixel vectors and the pixel elimination ratio; determining a second elimination proportion according to the first elimination proportion and the pixel elimination proportion; and reproducing according to the pixel value corresponding to the second elimination proportion to obtain an imaging result. The method and the system provided by the invention improve the imaging quality by improving the inhibition effect of clutter and background pixel vectors.

Description

Imaging method and system based on through-wall radar clutter suppression
Technical Field
The invention relates to the field of clutter suppression, in particular to an imaging method and system based on through-wall radar clutter suppression.
Background
Unlike other radars in free space, through-the-wall radar (TWIR) requires detection imaging of objects behind a wall. Besides the noise signal, the amplitude of a main clutter signal caused by the primary reflection of the wall is far larger than that of a target signal, and the main clutter signal occupies a dominant position in the image; and the wall residual clutter after multiple reflections is often overlapped with the target signal in the time domain, so that the target imaging is more fuzzy. The method effectively inhibits the clutter of the wall body, and is an important precondition for accurate imaging of the TWIR on the target behind the wall.
Common clutter suppression algorithms mostly start from the echo domain, and directly separate a target signal from an echo signal. However, such algorithms often only filter out most of the clutter, and residual clutter still remains near the target in the imaging. Therefore, the image signal-to-noise ratio and the accuracy of target imaging are relatively low.
Disclosure of Invention
The invention aims to provide an imaging method and an imaging system based on through-wall radar clutter suppression, so that the imaging quality is improved by improving the suppression effect of clutter and background pixel vectors.
In order to achieve the purpose, the invention provides the following scheme:
an imaging method based on through-wall radar clutter suppression comprises the following steps:
acquiring an original echo signal received by a through-wall radar;
imaging the original echo signal to determine an original image;
determining discrete coefficients of pixel vectors of the original image according to the original image;
sorting the pixel vectors of the original image according to the discrete coefficients to obtain sorted pixel vectors;
determining a stepping length according to the original image;
determining a pixel elimination ratio according to the stepping length;
determining a first elimination ratio by using the sorted pixel vectors and the pixel elimination ratio;
determining a second elimination proportion according to the first elimination proportion and the pixel elimination proportion;
and reproducing according to the pixel value corresponding to the second elimination proportion to obtain an imaging result.
Optionally, the determining a discrete coefficient of the pixel vector of the original image according to the original image specifically includes:
determining discrete coefficients of pixel vectors of the original image according to the original image by using the following formula:
Figure BDA0003096797970000021
wherein, ViAs discrete coefficient, σiIs the standard deviation of the vector elements, muiIs the mean of the vector elements, K is the dimension of the pixel vector, qikIs the pixel vector, i is the number of pixel vectors, and k is the number of pixel vector dimensions.
Optionally, the sorting the pixel vectors of the original image according to the discrete coefficients to obtain the sorted pixel vectors specifically includes:
and performing descending order arrangement on the pixel vectors of the original image according to the discrete coefficients to obtain the ordered pixel vectors.
Optionally, the determining the step length according to the original image specifically includes:
and determining the stepping length according to the proportion of the minimum resolution unit of the original image to the imaging area.
Optionally, the determining a first elimination ratio by using the ordered pixel vectors and the pixel elimination ratio specifically includes:
determining the image intensity under the pixel elimination proportion by using the sorted pixel vectors and the pixel elimination proportion;
and drawing the image intensity into an image intensity change curve, and determining a first point tending to be stable in the image intensity change curve as a first elimination proportion.
Optionally, the determining the image intensity at the pixel elimination ratio by using the sorted pixel vectors and the pixel elimination ratio specifically includes:
determining the image intensity under the pixel elimination ratio according to the following formula by using the sorted pixel vector and the pixel elimination ratio:
Figure BDA0003096797970000031
wherein IIIs the image intensity, Q is the total number of pixels, AiIs the amplitude of the ith pixel.
Optionally, the determining a second elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:
determining the residual pixel mean value under the pixel elimination proportion according to the first elimination proportion and the pixel elimination proportion;
and drawing the residual pixel mean value into a residual pixel mean value change curve, and determining a first point which tends to be stable in the residual pixel mean value change curve as a second elimination proportion.
Optionally, the determining the remaining pixel average value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:
and determining the residual pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio by using the following formula:
Figure BDA0003096797970000032
wherein M isRPIs the residual pixel mean, n is the upper limit of the residual pixel label, m is the lower limit of the residual image quantity label, AiIs the amplitude of the ith pixel.
An imaging system based on through-wall radar clutter suppression, comprising:
the acquisition module is used for acquiring an original echo signal received by the through-wall radar;
the imaging module is used for imaging the original echo signal and determining an original image;
a discrete coefficient determining module, configured to determine a discrete coefficient of a pixel vector of the original image according to the original image;
the sorting module is used for sorting the pixel vectors of the original image according to the discrete coefficients to obtain the sorted pixel vectors;
the step length determining module is used for determining the step length according to the original image;
the pixel elimination ratio determining module is used for determining the pixel elimination ratio according to the stepping length;
a first elimination ratio determination module for determining a first elimination ratio using the sorted pixel vectors and the pixel elimination ratio;
a second elimination ratio determining module, configured to determine a second elimination ratio according to the first elimination ratio and the pixel elimination ratio;
and the recurrence module is used for performing recurrence according to the pixel value corresponding to the second elimination proportion to obtain an imaging result.
Optionally, the discrete coefficient determining module specifically includes:
a discrete coefficient determining unit, configured to determine a discrete coefficient of a pixel vector of the original image according to the original image by using the following formula:
Figure BDA0003096797970000041
wherein, ViAs discrete coefficient, σiIs the standard deviation of the vector elements, muiIs the mean of the vector elements, K is the dimension of the pixel vector, qikIs the pixel vector, i is the number of pixel vectors, and k is the number of pixel vector dimensions.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides an imaging method and system based on through-wall radar clutter suppression. And (5) stepping by length to gradually eliminate the pixel vector with larger discrete coefficient. In order to better mark the pixel vector elimination process, the first elimination proportion is utilized to carry out main clutter suppression, and the second elimination proportion is utilized to carry out target focusing, so that clutter and background pixel vectors are suppressed to the maximum extent, the optimal imaging result is obtained, and the imaging quality is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of an imaging method based on through-wall radar clutter suppression according to the present invention;
FIG. 2 is a schematic diagram of pixel vector formation under the BP-TWI algorithm;
FIG. 3 is a flow chart of a clutter suppression algorithm;
FIG. 4 is a schematic diagram of an imaging system based on through-wall radar clutter suppression according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The invention aims to provide an imaging method and an imaging system based on through-wall radar clutter suppression, so that the imaging quality is improved by improving the suppression effect of clutter and background pixel vectors.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Determining a through-wall radar echo model:
the through-wall imaging radar is arranged to receive and transmit the same antenna array to detect an ideal point target behind a wall, the antenna array is parallel to a homogeneous wall, and a time domain echo signal received by a kth antenna can be expressed as a time domain echo signal from the echo composition alone
R(k,t)＝Rtg(k,t,p)+Rw(k,t)+Rn(k,t) (1)
Wherein R (k, t) is the time domain echo signal received by the kth antenna, Rtg(k, t, p) is the target echo, Rw(k, t) are clutter signals, Rn(k, t) is a noise signal. Here, it is considered that the antenna coupling wave has been eliminated by preprocessing. In order to facilitate subsequent analysis and calculation, further formula definition and model simplification are carried out on each component:
set point target Xp＝(xp,yp) At a target amplitude factor apWith a two-way propagation delay taukpTo represent the target echo, have
Rtg(k,t,p)＝aps(t-τkp) (2)
Wherein, s (t- τ)kp) Is a signal obtained by transmitting a signal s (t) after target echo delay, simultaneously, uses primary reflected waves on the front surface and the rear surface of a wall body to represent clutter signals, considers the consistency of the properties of the two during imaging, and uses a clutter amplitude factor awSum clutter time delay tauwExpress it uniformly as
Rw(k,t)＝aws(t-τw) (3)
Wherein R isw(k, t) is a clutter signal, s (t- τ)w) For the signal after clutter echo delay of the transmitting signal s (t), according to the existing theory, for the noise signal, its amplitude a obeys Rayleigh distribution, phase angle
Figure BDA0003096797970000064
At (0,2 pi)]Are uniformly distributed on the upper part with
Figure BDA0003096797970000061
Wherein R isn(k, t) is a noise signal, and j is an imaginary unit.
In summary, from equations (1) to (4), the echo signal can be obtained as
Figure BDA0003096797970000062
Formation and characterization of pixel vectors:
the echo signal in the time domain may reproduce important information such as the shape and position of the detection target in the form of an image through a certain signal processing method. The mesh model is used as a target imaging model, a set detection region is divided into M multiplied by N (azimuth direction multiplied by distance direction) meshes, and each mesh can be regarded as a space point. Correspondingly, the image has Q × N pixels in total.
Using BP-TWI algorithm to carry out spatial point Xi＝(xi,yi) The amplitude of the ith pixel in the image is
Figure BDA0003096797970000063
In the formula, τkiIs the kth antenna and XiThe two-way propagation delay.
To better describe the pixel characteristics, the concept of pixel vectors is introduced, namely: for any pixel in the image, there is a unique pixel vector qiCorresponding to it. K is a determined number, which is both the total number of channels in the antenna array and the dimension in any pixel vector; pixel vector qiAre K-dimensional vectors whose elements are the sampling values of the K antenna channel signals in the pixel formation process, respectively. The concept is expressed in mathematical language, which has
Figure BDA0003096797970000071
FIG. 2 is a schematic diagram of pixel vector formation under the BP-TWI algorithm. It can be seen that clutter signals in the time domain have consistency to each antenna channel, and target signals are distributed in a front-back staggered manner; and through time delay compensation, elements of the target pixel vector have better amplitude consistency, and elements of the clutter pixel vector have a few particularly large values. From a statistical point of view, the pixel vector can be characterized as: the clutter pixel vector has a more discrete element distribution than the target pixel vector.
As shown in fig. 1, the imaging method based on clutter suppression of the through-wall radar provided by the present invention includes:
step 101: and acquiring an original echo signal received by the through-wall radar.
Step 102: and imaging the original echo signal to determine an original image.
Step 103: and determining discrete coefficients of the pixel vector of the original image according to the original image. Step 103, specifically comprising:
determining discrete coefficients of pixel vectors of the original image according to the original image by using the following formula:
Figure BDA0003096797970000072
wherein, ViAs discrete coefficient, σiIs the standard deviation of the vector elements, muiIs the mean of the vector elements, K is the dimension of the pixel vector, qikIs the pixel vector, i is the number of pixel vectors, and k is the number of pixel vector dimensions.
Determining a discrete degree quantitative index:
considering that the amplitude difference of different types of pixels in an image domain is large, in order to avoid influencing the quantification processing of the dispersion degree of the pixel vector, a dispersion coefficient which is a measure of the relative dispersion degree is selected. The dispersion coefficient V is defined as the ratio of the standard deviation σ of the vector elements to its mean μ, which is typically greater than zero. Considering that most of the data of the through-wall echo is complex, the absolute value of the element is taken for calculation. For any pixel vector qiIs provided with
Figure BDA0003096797970000081
For the comprehensiveness of theoretical analysis, the pixel vectors in the through-wall imaging are classified and defined as follows: the target pixel vector refers to a pixel vector of a region corresponding to a real target position in the image; the clutter pixel vector refers to a pixel vector formed by the main clutter of the wall; the background pixel vector is a general term for the residual pixel vector formed by the noise signal, the wall residual clutter signal and other interference signals in the image.
Considering the wide distribution and limited influence of noise, it is assumed that the noise signal can be ignored in the calculation of the target pixel vector and the clutter pixel vector, and the transmission signal s (t) is defined as
Figure BDA0003096797970000082
Calculating the discrete coefficients of the three types of pixel vectors in sequence:
(1) target pixel vector qtg。
Due to the space point XtgWith real target XpCoincidence, τktgTwo-way propagation delay for representing any antenna position and real target is
Figure BDA0003096797970000083
Its discrete coefficients can be written as
Figure BDA0003096797970000084
(2) Clutter pixel vector qc。
In the process of forming clutter pixels, for real targets, there are
Figure BDA0003096797970000085
For any space point at the position of the wall, the time delay of the space point and the mth antenna unit is not equal to the wall echo time delay, wherein taukcAnd τmcThe two respectively represent the two-way propagation delay between the kth antenna position and the space point at the wall position, and the two-way propagation delay between the mth antenna position and the space point at the wall position. m is the particular antenna element whose experimental and echo delays are equal, and k represents any antenna element.
Namely, it is
Figure BDA0003096797970000091
Having a coefficient of dispersion of
Figure BDA0003096797970000092
Wherein, awAs clutter amplitude factor, σcIs the standard deviation, mu, of the clutter pixel vector elementscThe average of the clutter pixel vector elements is the clutter pixel vector formed by the "divergence" of the principal clutter signal in part near the wall, in addition to the clutter pixel vector at the wall location mentioned above. Although not specifically calculated, it is certain that the discrete coefficients of the pixel vectors in this portion are larger than VcAnd is larger.
(3) Background pixel vector qbg。
Considering the characteristic of noise signal in the constitution of background pixel vector and wide coverage, its discrete coefficient is calculated as
Figure BDA0003096797970000093
Wherein σnRoot mean square, σ, of white Gaussian noisebgIs the standard deviation, mu, of the background pixel vector elementsbgAs a background imageMean of the elements of the vector of elements.
Equation 8 is a basic equation for calculating the discrete coefficient of any pixel vector, and the discrete coefficient of each pixel vector is calculated by equation 8.
Equations 9-15 are simplified calculations of discrete coefficients of various pixel vectors, which are only used as qualitative analyses, and corresponding conclusions thereof can be selected as references for subsequent indexes, and have no direct relation with actual coefficient calculations.
It can be seen that the discrete coefficient of a general background pixel vector is slightly larger than the target pixel vector. In addition, background pixel vectors around the target formed by superposing wall residual clutter signals, target signals and the like have relatively large discrete coefficients and amplitudes, and are key points for elimination; and the background pixel vector formed by other interference signals has small discrete coefficient and amplitude, and basically cannot influence the target imaging.
Step 104: and sequencing the pixel vectors of the original image according to the discrete coefficients to obtain the sequenced pixel vectors.
Step 104, specifically comprising:
and performing descending order arrangement on the pixel vectors of the original image according to the discrete coefficients to obtain the ordered pixel vectors.
Step 105: and determining the step length according to the original image. Step 105, specifically comprising:
and determining the stepping length according to the proportion of the minimum resolution unit of the original image to the imaging area.
Step 106: and determining the pixel elimination proportion according to the step length.
Evaluation index of clutter suppression effect:
in the clutter suppression of the through-wall radar, an evaluation index of the clutter suppression effect is often required to be introduced. In the present invention, the optimum elimination ratio of the pixel vector can be determined by evaluating the dynamic change of the index. The most common method at present is the signal-to-noise ratio, i.e.
Figure BDA0003096797970000101
Wherein, B1、B2Respectively a target region and a clutter region in the image, C1、C2The number of pixels in the respective regions. However, this method must acquire a priori information such as the position of the target, and the selection of the target region can only depend on experience or target detection, which undoubtedly complicates the problem.
Since clutter suppression is performed in the image domain, one does not start with a measure of the image characteristics. It is easy to find that the amplitude of the clutter pixels is much larger than other pixels, and the intensity of the whole image must be significantly reduced with the elimination of the clutter pixel vector. Then, the image intensity may be used as an evaluation index for eliminating the clutter pixel vector, which is defined as
Figure BDA0003096797970000102
Then, part of background pixel vectors with larger discrete coefficients are eliminated, and the image intensity curve is basically stable, so a new evaluation index is searched.
Still starting from the pixel amplitude, the rest is the target pixel vector and the background pixel vector with small amplitude, except for the above-mentioned part of vectors. If the mean level of the remaining pixels is monitored, the mean level of the remaining pixels is definitely decreased with the elimination of the background pixel vector with larger amplitude; when it is completely eliminated, the mean level will also stabilize, because the background pixel vector, which is eliminated later, has little effect on the mean level. Therefore, the residual pixel mean value can be used as an evaluation index for eliminating the background pixel vector, and the residual pixel label is i ∈ [ m, n ], so that the residual pixel mean value is defined as
Figure BDA0003096797970000111
The index in equation 16 is the most common index, but is not suitable for the optimization algorithm of the present invention, and therefore is not used.
The indexes in formulas 17 and 18 are evaluation indexes employed in the invention, and the image intensity is calculated by formula 17 in step 3 to obtain a; the remaining pixel mean is calculated by equation 18 in step 4 to get b.
Step 107: determining a first elimination ratio using the sorted pixel vectors and the pixel elimination ratio. Step 107, specifically including:
and determining the image intensity under the pixel elimination ratio by using the sorted pixel vector and the pixel elimination ratio. The determining the image intensity at the pixel elimination ratio by using the ordered pixel vectors and the pixel elimination ratio specifically includes: determining the image intensity under the pixel elimination ratio according to the following formula by using the sorted pixel vector and the pixel elimination ratio:
Figure BDA0003096797970000112
in which IIIs the image intensity, Q is the total number of pixels, AiIs the amplitude of the ith pixel.
And drawing the image intensity into an image intensity change curve, and determining a first point tending to be stable in the image intensity change curve as a first elimination proportion.
Step 108: and determining a second elimination proportion according to the first elimination proportion and the pixel elimination proportion. Step 108, specifically comprising:
and determining the residual pixel mean value under the pixel elimination proportion according to the first elimination proportion and the pixel elimination proportion. The determining the remaining pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:
and determining the residual pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio by using the following formula:
Figure BDA0003096797970000121
wherein, MRPIs the residual pixel mean, n is the upper limit of the residual pixel label, m is the lower limit of the residual pixel label, AiIs the amplitude of the ith pixel.
And drawing the residual pixel mean value into a residual pixel mean value change curve, and determining a first point which tends to be stable in the residual pixel mean value change curve as a second elimination proportion.
Step 109: and reproducing according to the pixel value corresponding to the second elimination proportion to obtain an imaging result.
As shown in fig. 3, the invention also provides a specific imaging method based on the through-wall radar clutter suppression, which comprises the following steps:
step 1: and imaging the original echo signal received by the through-wall radar, and determining an original image implemented by an algorithm.
Step 2: basic preparation work, namely calculating discrete coefficients of all pixel vectors of the original image according to a formula (8), and performing descending order arrangement on all the pixel vectors in the original image according to the discrete coefficients, namely the larger the discrete coefficient is, the more the position is; the step length β of the pixel elimination ratio, i.e. the ratio of the increment of the pixel vector eliminated each time to the total number of vectors, is determined.
And step 3: the method comprises the following steps of (1) performing primary clutter suppression, namely determining the pixel proportion of each elimination according to the step length in the range of [0,1], calculating the image intensity under each elimination proportion and drawing a change curve, finding a first point at which the curve tends to be stable, confirming that the point finishes the primary clutter suppression work, and marking the elimination proportion as a; [0,1] refers to the range of the pixel removal ratio at a time, which is 0 at the beginning, and gradually increases to 1 according to the step length.
And 4, step 4: and (3) focusing the target, determining the pixel proportion of each elimination according to the step length beta in the range of [ a,1], calculating the average value of the residual pixels under each elimination proportion and drawing a change curve, finding a first point of the curve which tends to be relatively stable, determining that the point finishes the work of focusing the target, and marking the elimination proportion as b.
And 5: and (3) reproducing the image by taking the value of each pixel when the elimination ratio is b, namely the optimal imaging result.
In addition, several details of the algorithm implementation are described below:
(1) β is related to the imaging resolution of the through-wall radar, and the step length is usually approximated by the ratio of the minimum resolution unit of the radar imaging to the imaging area, i.e.:
Figure BDA0003096797970000131
wherein, deltarFor distance resolution, δdFor azimuthal resolution, SIThe area of the imaging area can be obtained from the imaging scene and the original image.
(2) A few part of target pixel vectors can be mixed with background pixel vectors with similar coefficients, and a first point of which the curve tends to be stable is usually taken for the purposes of retaining the target pixels and ensuring the target imaging quality.
(3) Also, on the premise of ensuring the imaging quality of the target, the algorithm eliminates redundant pixel vectors as much as possible to obtain the optimal imaging result, so that the term "optimal" is a relative concept.
As shown in fig. 4, the imaging system based on clutter suppression of the through-wall radar provided by the present invention includes:
an obtaining module 401, configured to obtain an original echo signal received by a through-wall radar.
An imaging module 402, configured to perform imaging processing on the original echo signal, and determine an original image.
A discrete coefficient determining module 403, configured to determine a discrete coefficient of a pixel vector of the original image according to the original image. The discrete coefficient determining module specifically includes:
a discrete coefficient determining unit, configured to determine a discrete coefficient of a pixel vector of the original image according to the original image by using the following formula:
Figure BDA0003096797970000132
wherein, ViAs discrete coefficient, σiIs the standard deviation of the vector elements, muiIs the mean of the vector elements, K is the dimension of the pixel vector, qikI is the number of pixel vectors and k is the number of pixel vector dimensions.
And the sorting module 404 is configured to sort the pixel vectors of the original image according to the discrete coefficients to obtain sorted pixel vectors.
A step length determining module 405, configured to determine a step length according to the original image.
A pixel elimination ratio determining module 406, configured to determine a pixel elimination ratio according to the step length.
A first elimination ratio determining module 407, configured to determine a first elimination ratio by using the sorted pixel vector and the pixel elimination ratio.
A second elimination ratio determining module 408, configured to determine a second elimination ratio according to the first elimination ratio and the pixel elimination ratio.
And a recurrence module 409, configured to perform recurrence according to the pixel value corresponding to the second elimination ratio, so as to obtain an imaging result.
The invention avoids the complex entangled echo signals and carries out clutter suppression at the pixel level in the image domain. And combining a back projection in through-the-wall imaging (BP-TWI) algorithm to form corresponding pixel vectors by the components of the pixels in each antenna channel. It is easy to find that the element of the target pixel vector is far less discrete than other pixel vectors, thereby introducing a discrete coefficient to quantitatively describe this feature. Then, according to a certain step length, the pixel vector with larger discrete coefficient is eliminated step by step. In order to better mark the elimination process of the pixel vector, the key points of main clutter suppression and target focusing are determined according to the image intensity and the residual pixel mean value, so that clutter and background pixel vectors are suppressed to the maximum extent, and the optimal imaging result is obtained. And finally, verifying the effectiveness and reliability of the algorithm by simulating under a general condition and a strong interference condition and combining the contrast of background cancellation imaging.
An image domain suppression algorithm based on pixel vector elimination is provided for the through-the-wall radar clutter suppression problem, and the algorithm is proved to have good effectiveness and reliability through simulation, so that the clutter can be suppressed more thoroughly, and accurate target information is provided for subsequent detection and identification. In view of the fact that a general echo domain algorithm can only suppress main clutter of a wall body, and the imaging quality of a target is low, the algorithm focuses on the pixel discrete characteristics in an image, the imaging of the target is clear and accurate by eliminating redundant pixel vectors, and meanwhile, the reliability of the algorithm is greatly improved through a double-index evaluation system of the clutter suppression effect.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the foregoing, the description is not to be taken in a limiting sense.

Claims (5)

1. An imaging method based on through-wall radar clutter suppression is characterized by comprising the following steps:
acquiring an original echo signal received by a through-wall radar;
imaging the original echo signal to determine an original image;
determining discrete coefficients of pixel vectors of the original image according to the original image;
sorting the pixel vectors of the original image according to the discrete coefficients to obtain sorted pixel vectors;
determining a stepping length according to the original image;
determining a pixel elimination ratio according to the stepping length;
determining a first elimination ratio by using the sorted pixel vectors and the pixel elimination ratio;
determining a second elimination proportion according to the first elimination proportion and the pixel elimination proportion;
reproducing according to the pixel value corresponding to the second elimination proportion to obtain an imaging result;
the determining the step length according to the original image specifically includes: determining the stepping length according to the proportion of the minimum resolution unit of the original image to the imaging area;
the determining a first elimination ratio by using the ordered pixel vectors and the pixel elimination ratio specifically includes: determining the image intensity under the pixel elimination proportion by using the sorted pixel vectors and the pixel elimination proportion; drawing the image intensity into an image intensity change curve, and determining a first point tending to be stable in the image intensity change curve as a first elimination proportion;
the determining the image intensity at the pixel elimination ratio by using the ordered pixel vectors and the pixel elimination ratio specifically includes: determining the image intensity under the pixel elimination ratio according to the following formula by using the sequenced pixel vector and the pixel elimination ratio:
Figure FDA0003595362530000011
wherein IIIs the image intensity, Q is the total number of pixels, AiIs the amplitude of the ith pixel;
the determining a second elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:
determining a residual pixel mean value under the pixel elimination proportion according to the first elimination proportion and the pixel elimination proportion;
drawing the residual pixel mean value into a residual pixel mean value change curve, and determining a first point which tends to be stable in the residual pixel mean value change curve as a second elimination proportion;
the determining the remaining pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:
and determining the residual pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio by using the following formula:
Figure FDA0003595362530000021
wherein M isRPIs the residual pixel mean, n is the upper limit of the residual pixel label, m is the lower limit of the residual pixel label, AiIs the amplitude of the ith pixel.
2. The imaging method based on through-wall radar clutter suppression according to claim 1, wherein the determining discrete coefficients of the pixel vector of the original image from the original image comprises:
determining discrete coefficients of pixel vectors of the original image according to the original image by using the following formula:
Figure FDA0003595362530000022
wherein, ViAs discrete coefficient, σiIs the standard deviation of the vector elements, muiIs the mean of the vector elements, K is the dimension of the pixel vector, qikIs the pixel vector, i is the number of pixel vectors, and k is the number of pixel vector dimensions.
3. The imaging method based on through-wall radar clutter suppression according to claim 1, wherein the sorting the pixel vectors of the original image according to the discrete coefficients to obtain sorted pixel vectors specifically comprises:
and performing descending order arrangement on the pixel vectors of the original image according to the discrete coefficients to obtain the ordered pixel vectors.
4. An imaging system based on through-wall radar clutter suppression, comprising:
the acquisition module is used for acquiring an original echo signal received by the through-wall radar;
the imaging module is used for imaging the original echo signal and determining an original image;
a discrete coefficient determining module, configured to determine a discrete coefficient of a pixel vector of the original image according to the original image;
the sorting module is used for sorting the pixel vectors of the original image according to the discrete coefficients to obtain the sorted pixel vectors;
the step length determining module is used for determining the step length according to the original image;
the pixel elimination ratio determining module is used for determining the pixel elimination ratio according to the stepping length;
a first elimination ratio determination module, configured to determine a first elimination ratio by using the sorted pixel vectors and the pixel elimination ratio;
a second elimination ratio determining module, configured to determine a second elimination ratio according to the first elimination ratio and the pixel elimination ratio;
the recurrence module is used for performing recurrence according to the pixel value corresponding to the second elimination proportion to obtain an imaging result;
the determining the step length according to the original image specifically includes: determining the stepping length according to the proportion of the minimum resolution unit of the original image to the imaging area;
the determining a first elimination ratio by using the ordered pixel vectors and the pixel elimination ratio specifically includes: determining the image intensity under the pixel elimination proportion by using the sorted pixel vectors and the pixel elimination proportion; drawing the image intensity into an image intensity change curve, and determining a first point tending to be stable in the image intensity change curve as a first elimination proportion;
the determining the image intensity at the pixel elimination ratio by using the ordered pixel vectors and the pixel elimination ratio specifically includes: determining the image intensity under the pixel elimination ratio according to the following formula by using the sorted pixel vector and the pixel elimination ratio:
Figure FDA0003595362530000031
wherein IIIs the image intensity, Q is the total number of pixels, AiIs the amplitude of the ith pixel;
the determining a second elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:
determining the residual pixel mean value under the pixel elimination proportion according to the first elimination proportion and the pixel elimination proportion;
drawing the residual pixel mean value into a residual pixel mean value change curve, and determining a first point which tends to be stable in the residual pixel mean value change curve as a second elimination proportion;
the determining the remaining pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:
and determining the residual pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio by using the following formula:
Figure FDA0003595362530000041
wherein M isRPIs the residual pixel mean, n is the upper limit of the residual pixel label, m is the lower limit of the residual pixel label, AiIs the amplitude of the ith pixel.
5. The imaging system based on through-wall radar clutter suppression of claim 4, wherein the discrete coefficient determining module specifically comprises:
a discrete coefficient determining unit, configured to determine a discrete coefficient of a pixel vector of the original image according to the original image by using the following formula:
Figure FDA0003595362530000042
wherein, ViAs discrete coefficient, σiIs the standard deviation of the vector elements, muiIs the mean of the vector elements, K is the dimension of the pixel vector, qikIs the pixel vector, i is the number of pixel vectors, and k is the number of pixel vector dimensions.
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