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

Abstract

The present invention relates to an imaging method and system based on clutter suppression of through-the-wall radar, comprising: acquiring an original echo signal received by a through-wall radar; performing imaging processing on the original echo signal to determine an original image; The image determines the discrete coefficient of the pixel vector of the original image; sorts the pixel vector of the original image according to the discrete coefficient to obtain the sorted pixel vector; determines the step length according to the original image; The pixel elimination ratio is determined by the input length; the first elimination ratio is determined by using the sorted pixel vector and the pixel elimination ratio; the second elimination ratio is determined according to the first elimination ratio and the pixel elimination ratio; according to the second elimination ratio The pixel value corresponding to the ratio is reproduced to obtain the imaging result. The method and system provided by the present invention improve the imaging quality by improving the suppression effect of clutter and background pixel vector.

Description

An 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 technique

Different from other radars in free space, through-the-wall radar (TWIR) needs to detect and image the target behind the wall. In addition to the noise signal, the amplitude of the main clutter signal caused by the primary reflection of the wall is much larger than that of the target signal, occupying the dominant position in the image; while the residual clutter of the wall after multiple reflections is often the same as the target signal in the time domain. Overlapping, making the target image more blurred. Effective suppression of wall clutter is an important prerequisite for TWIR to accurately image targets behind walls.

Common clutter suppression algorithms mostly start from the echo domain and directly separate the target signal from the echo signal. However, such algorithms can often only filter out most of the clutter, and there are still residual clutter near the target in the imaging. Therefore, the image signal-to-noise ratio and the accuracy of target imaging are relatively low.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide an imaging method and system based on through-wall radar clutter suppression, so as to improve the imaging quality by improving the suppression effect of clutter and background pixel vector.

For achieving the above object, the present invention provides the following scheme:

An imaging method based on through-wall radar clutter suppression, comprising:

Obtain the original echo signal received by the through-wall radar;

Perform imaging processing on the original echo signal to determine the original image;

determining the discrete coefficient of the pixel vector of the original image according to the original image;

Sort the pixel vector of the original image according to the discrete coefficient to obtain the sorted pixel vector;

determining the step length according to the original image;

Determine the pixel elimination ratio according to the step length;

Using the sorted pixel vector and the pixel elimination ratio to determine a first elimination ratio;

determining a second elimination ratio according to the first elimination ratio and the pixel elimination ratio;

Reproducing is performed according to the pixel value corresponding to the second elimination ratio to obtain an imaging result.

Optionally, the determining the discrete coefficient of the original image pixel vector according to the original image specifically includes:

According to the original image, the following formula is used to determine the discrete coefficient of the pixel vector of the original image:

Among them, V _i is the discrete coefficient, σ _i is the standard deviation of the vector elements, μ _i is the mean value of the vector elements, K is the dimension of the pixel vector, q _ik is the pixel vector, i is the number of pixel vectors, and k is the pixel vector The number of vector dimensions.

Optionally, sorting the pixel vectors of the original image according to the discrete coefficients to obtain sorted pixel vectors, specifically including:

Arrange the pixel vectors of the original image in descending order according to the discrete coefficients to obtain the sorted pixel vectors.

Optionally, the determining the step length according to the original image specifically includes:

The step length is determined according to the ratio of the minimum resolution unit of the original image to the imaging area.

Optionally, determining the first elimination ratio by using the sorted pixel vector pixel vector and the pixel elimination ratio specifically includes:

Using the sorted pixel vector and the pixel removal ratio to determine the image intensity under the pixel removal ratio;

The image intensity is drawn into an image intensity change curve, and the first point in the image intensity change curve that tends to be stable is determined as the first elimination ratio.

Optionally, the use of the sorted pixel vector and the pixel elimination ratio to determine the image intensity under the pixel elimination ratio specifically includes:

Use the sorted pixel vector and the pixel removal ratio to determine the image intensity at the pixel removal ratio according to the following formula:

where _II is the image intensity, Q is the total number of pixels, and A _i is the magnitude of the ith pixel.

Optionally, the determining the second elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:

Determine the residual pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio;

The residual pixel mean value is drawn into a residual pixel mean value change curve, and the first point in the residual pixel mean value change curve that tends to be stable is determined as the second elimination ratio.

Optionally, determining the average value of remaining pixels under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:

According to the first elimination ratio and the pixel elimination ratio, the following formula is used to determine the residual pixel mean value under the pixel elimination ratio:

Among them, M _RP is the mean value of the remaining pixels, n is the upper limit of the remaining pixel labels, m is the lower limit of the remaining image volume labels, and A _i is the amplitude of the ith pixel.

An imaging system based on through-wall radar clutter suppression, comprising:

The acquisition module is used to acquire the original echo signal received by the through-the-wall radar;

an imaging module, configured to perform imaging processing on the original echo signal to determine the original image;

a discrete coefficient determination module, configured to determine the discrete coefficient of the pixel vector of the original image according to the original image;

a sorting module, configured to sort the pixel vectors of the original image according to the discrete coefficients to obtain sorted pixel vectors;

a step length determination module, configured to determine the step length according to the original image;

a pixel elimination ratio determination module, configured to determine a pixel elimination ratio according to the step length;

a first elimination ratio determination module, configured to determine a first elimination ratio by using the sorted pixel vector and the pixel elimination ratio;

A second elimination ratio determination module, configured to determine a second elimination ratio according to the first elimination ratio and the pixel elimination ratio;

and a reproduction module, configured to reproduce according to the pixel value corresponding to the second elimination ratio to obtain an imaging result.

Optionally, the discrete coefficient determination module specifically includes:

A discrete coefficient determination unit, configured to determine the discrete coefficient of the original image pixel vector using the following formula according to the original image:

Among them, V _i is the discrete coefficient, σ _i is the standard deviation of the vector elements, μ _i is the mean value of the vector elements, K is the dimension of the pixel vector, q _ik is the pixel vector, i is the number of pixel vectors, and k is the pixel vector The number of vector dimensions.

According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

The present invention provides an imaging method and system based on through-wall radar clutter suppression, in which the components of pixels in each antenna channel form a corresponding pixel vector. Step length, and gradually eliminate pixel vectors with large discrete coefficients. In order to better mark the pixel vector elimination process, the first elimination ratio is used for main clutter suppression, and the second elimination ratio is used for target focusing, so as to maximize the suppression of clutter and background pixel vectors, obtain the best imaging results, and improve the image quality.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings required in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some of the present invention. In the embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative labor.

1 is a flowchart 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 the flow chart of the 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 ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

The purpose of the present invention is to provide an imaging method and system based on through-wall radar clutter suppression, so as to improve the imaging quality by improving the suppression effect of clutter and background pixel vector.

In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

Determination of through-wall radar echo model:

The through-wall imaging radar is set to detect an ideal point target behind the wall with an antenna array that transmits and receives at the same time, and the antenna array is parallel to the homogeneous wall. In terms of echo components, the time domain received by the kth antenna is The echo signal can be expressed as

R(k,t)= _Rtg (k,t,p)+ _Rw (k,t)+ _Rn (k,t) (1)

In the formula, R(k,t) is the time domain echo signal received by the kth antenna, R _tg (k, t, p) is the target echo, R _w (k, t) is the clutter signal, R _n (k,t) is the noise signal. Here, the antenna coupling wave is considered to have been eliminated by preprocessing. In order to facilitate subsequent analysis and calculation, further formula definitions and model simplifications are made for each component:

Set the point target X _p =(x _p , y _p ), and use the target amplitude factor a _p and the two-way propagation delay τ _kp to represent the target echo, we have

R _tg (k,t,p)=a _p s(t-τ _kp ) (2)

Among them, s(t-τ _kp ) is the signal after the transmitted signal s(t) is delayed by the target echo, and at the same time, the clutter signal is represented by the first reflected wave on the front and rear surfaces of the wall, considering that the properties of the two are the same when imaging , which can be expressed uniformly by the clutter amplitude factor a _w and the clutter delay τ _w as

R _w (k,t)=a _w s(t-τ _w ) (3)

在(0,2π]上均匀分布，有Among them, R _w (k,t) is the clutter signal, and s(t-τ _w ) is the signal after the transmitted signal s(t) is delayed by the clutter echo. According to the existing theory, for the noise signal, its The amplitude a follows a Rayleigh distribution, and the phase angle

Uniformly distributed on (0,2π], we have

Among them, R _n (k, t) is the noise signal, and j is the imaginary unit.

To sum up, from equations (1)-(4), the echo signal can be obtained as

The formation and characteristics of the pixel vector:

The echo signal in the time domain will 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. Taking the grid model as the target imaging model, the detection area is set to be divided into M×N (azimuth direction×range direction) grids, and each grid can be regarded as a spatial point. Correspondingly, there are Q=M×N pixels in the image.

Using the BP-TWI algorithm to process the echo signal at the spatial point X _i =(x _i , y _i ), the amplitude of the i-th pixel in the image is

where τ _ki is the round-trip propagation delay between the k-th antenna and X _i .

In order to better describe pixel features, the concept of pixel vector is introduced, that is, for any pixel in the image, there is a unique pixel vector _qi corresponding to it. K is a certain value, which is not only the total number of channels in the antenna array, but also the dimension of any pixel vector; the pixel vector _qi is a K-dimensional vector, and its elements are the sampling values of the K antenna channel signals in the pixel formation process. . Expressing this concept in mathematical language, we have

Figure 2 is a schematic diagram of the formation of pixel vectors under the BP-TWI algorithm. It can be seen that the clutter signal in the time domain is consistent with each antenna channel, and the target signal presents a staggered distribution; after time delay compensation, the elements of the target pixel vector have good amplitude consistency, and the clutter pixel There are a few particularly large values for the elements of the vector. From a statistical point of view, the characteristics of the pixel vector can be expressed as: the clutter pixel vector has a greater degree of dispersion of the element distribution than the target pixel vector.

As shown in FIG. 1 , an imaging method based on through-wall radar clutter suppression provided by the present invention includes:

Step 101: Obtain the original echo signal received by the through-wall radar.

Step 102: Perform imaging processing on the original echo signal to determine an original image.

Step 103: Determine the discrete coefficient of the pixel vector of the original image according to the original image. Step 103 specifically includes:

According to the original image, the following formula is used to determine the discrete coefficient of the pixel vector of the original image:

Among them, V _i is the discrete coefficient, σ _i is the standard deviation of the vector elements, μ _i is the mean value of the vector elements, K is the dimension of the pixel vector, q _ik is the pixel vector, i is the number of pixel vectors, and k is the pixel vector The number of vector dimensions.

Determine the quantitative index of dispersion degree:

Considering the large difference in the amplitudes of different types of pixels in the image domain, in order to avoid it affecting the quantitative processing of the discrete degree of pixel vectors, a measure of the relative discrete degree - discrete coefficient is selected. The dispersion coefficient V is defined as the ratio of the standard deviation σ of the vector elements to its mean μ, and in general, the mean μ is greater than zero. Considering that the data of the echo through the wall are mostly complex numbers, the absolute value of the elements is taken for calculation. For any pixel vector q _i , we have

For the comprehensiveness of theoretical analysis, the pixel vectors in through-wall imaging are classified and defined as follows: the target pixel vector refers to the pixel vector in the area corresponding to the real target position in the image; the clutter pixel vector refers to the pixels formed by the main clutter of the wall. Vector; Background pixel vector is a general term for the residual pixel vector formed by noise signal, wall residual clutter signal and other interference signals in the image.

Considering that the noise distribution is very wide and the influence is limited, it is assumed that the noise signal can be ignored in the calculation process of the target pixel vector and the clutter pixel vector, and the emission signal s(t) is specified as

The discrete coefficients of the three types of pixel vectors are calculated sequentially:

(1) The target pixel vector q _tg .

Since the space point X _tg coincides with the real target X _p , τ _ktg represents the two-way propagation delay between any antenna position and the real target, we have

Then its discrete coefficient can be written as

(2) The clutter pixel vector q _c .

During the formation of clutter pixels, for real targets, there are

For any spatial point at the wall position, it may be assumed that the time delay of the mth antenna element is equal to the wall echo delay, where τ _kc and τ _mc respectively represent the kth antenna position and Two-way propagation delay between spatial points at the wall location, two-way propagation delay between the mth antenna location and the spatial point at the wall location. m is the specific antenna element whose experimental and echo delays are equal, and k denotes any antenna element.

which is

Its dispersion coefficient is

Among them, a _w is the clutter amplitude factor, σ _c is the standard deviation of the clutter pixel vector elements, μ _c is the mean value of the clutter pixel vector elements, except the clutter pixel vector at the wall position mentioned above, in the wall There are also clutter pixel vectors that are partly formed by the "divergence" of the main clutter signal near the volume. Although there is no specific calculation, it is certain that the discrete coefficient of this part of the pixel vector is larger than V _c .

(3) The background pixel vector q _bg .

Considering that the composition of the background pixel vector is especially typical of the noise signal and has a wide coverage, the discrete coefficient is calculated separately as

Among them, σ _n is the root mean square of Gaussian white noise, σ _bg is the standard deviation of the background pixel vector elements, and μ _bg is the mean value of the background pixel vector elements.

Equation 8 is a basic formula for calculating the discrete coefficient of any pixel vector, and the discrete coefficient of each pixel vector is calculated by Equation 8.

Formula 9-15 is a simplified calculation of the discrete coefficients of various pixel vectors, which is only used for qualitative analysis, and its corresponding conclusions can be used as a reference for subsequent index selection, which is not directly related to the actual coefficient calculation.

It is not difficult to see that the discrete coefficient of the general background pixel vector is slightly larger than the target pixel vector. In addition, the background pixel vector around the target formed by the superposition of wall residual clutter signal, target signal, etc. has relatively large dispersion coefficient and amplitude, which is the key point of elimination; while the background pixel vector formed by other interference signals, the dispersion coefficient and amplitude are very small and will not affect the target imaging basically.

Step 104: Sort the pixel vectors of the original image according to the discrete coefficients to obtain sorted pixel vectors.

Step 104 specifically includes:

Arrange the pixel vectors of the original image in descending order according to the discrete coefficients to obtain the sorted pixel vectors.

Step 105: Determine the step length according to the original image. Step 105 specifically includes:

The step length is determined according to the ratio of the minimum resolution unit of the original image to the imaging area.

Step 106: Determine the pixel elimination ratio according to the step length.

Evaluation index of clutter suppression effect:

In the clutter suppression of through-wall radar, it is often necessary to introduce the evaluation index of clutter suppression effect. In the present invention, the optimal elimination ratio of the pixel vector can be determined by the dynamic change of the evaluation index. The most common method at present is the signal-to-noise ratio, which is

Wherein, B ₁ and B ₂ are the target area and the clutter area in the image respectively, and C ₁ and C ₂ are the number of pixels in the respective areas. However, this method must obtain prior information such as the location of the target, and the selection of the target area can only rely on experience or target detection, which undoubtedly complicates the problem.

Since clutter suppression is performed in the image domain, we might as well start with the measurement of image characteristics. It is not difficult to find that the amplitude of the clutter pixel is much larger than other pixels, and with the elimination of the clutter pixel vector, the intensity of the entire image will definitely drop significantly. Then, the image intensity can be used as an evaluation index to eliminate the clutter pixel vector, which is defined as

Subsequently, some background pixel vectors with large discrete coefficients must be eliminated. At this time, the image intensity curve is basically stable, so a new evaluation index must be found.

Still starting from the pixel amplitude, in addition to the above-mentioned part of the vector, the rest is the target pixel vector and the background pixel vector with a small amplitude. If the average level of the remaining pixels is monitored, as the background pixel vector with a larger amplitude is eliminated, its average level will definitely decrease; and when it is completely eliminated, the average level will also stabilize, because it will be eliminated later. The background pixel vector has little effect on the mean level. Therefore, the mean value of the remaining pixels can be used as the evaluation index for eliminating the background pixel vector, and the label of the remaining pixels is i∈[m,n], then it is defined as

The index in formula 16 is the most commonly used index, but it is not suitable for the optimization algorithm in the present invention, so it is not used.

The indexes in formulas 17 and 18 are the evaluation indexes adopted in the invention. In step 3, the image intensity is calculated by formula 17 to obtain a; in step 4, the residual pixel mean value is calculated by formula 18 to obtain b.

Step 107: Determine a first elimination ratio by using the sorted pixel vector and the pixel elimination ratio. Step 107 specifically includes:

The image intensity at the pixel removal ratio is determined using the sorted pixel vector and the pixel removal ratio. The determining the image intensity under the pixel elimination ratio using the sorted pixel vector and the pixel elimination ratio specifically includes: determining the pixel elimination ratio under the pixel elimination ratio by using the sorted pixel vector and the pixel elimination ratio according to the following formula: The image intensity of:

where _II is the image intensity, Q is the total number of pixels, and A _i is the magnitude of the ith pixel.

The image intensity is drawn into an image intensity change curve, and the first point in the image intensity change curve that tends to be stable is determined as the first elimination ratio.

Step 108: Determine a second elimination ratio according to the first elimination ratio and the pixel elimination ratio. Step 108 specifically includes:

The average value of the remaining pixels under the pixel elimination ratio is determined according to the first elimination ratio and the pixel elimination ratio. The determining the average value of the remaining pixels under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes:

According to the first elimination ratio and the pixel elimination ratio, the following formula is used to determine the residual pixel mean value under the pixel elimination ratio:

Among them, M _RP is the mean value of the remaining pixels, n is the upper limit of the remaining pixel labels, m is the lower limit of the remaining pixel labels, and A _i is the amplitude of the ith pixel.

The residual pixel mean value is drawn into a residual pixel mean value change curve, and the first point in the residual pixel mean value change curve that tends to be stable is determined as the second elimination ratio.

Step 109: Perform reproduction according to the pixel value corresponding to the second elimination ratio to obtain an imaging result.

As shown in FIG. 3 , the present invention also provides a specific imaging method based on an imaging method based on through-wall radar clutter suppression, the steps are as follows:

Step 1: Perform imaging processing on the original echo signal received by the through-wall radar to determine the original image implemented by the algorithm.

Step 2: Basic preparatory work, calculate the discrete coefficient of each pixel vector of the original image according to formula (8), and arrange each pixel vector in the original image in descending order according to the discrete coefficient, that is, the pixel vector with the larger discrete coefficient, the higher the position. ; Determine the step length β of the pixel elimination ratio, that is, the ratio of the increment of the pixel vector eliminated each time to the total number of vectors.

Step 3: Main clutter suppression, in the range of [0,1], determine the pixel ratio of each elimination according to the step length, calculate the image intensity under each elimination ratio and draw a change curve, and find that the curve tends to be stable The first point of , it is determined that this point has completed the main clutter suppression work, and its elimination ratio is marked as a; [0,1] refers to the range of each pixel elimination ratio, which is 0 at the beginning, according to the step The length gradually increases to 1.

Step 4: Focus on the target, in the range of [a, 1], determine the pixel ratio of each elimination according to the step length β, calculate the average value of the remaining pixels under each elimination ratio and draw a change curve, and find that the curve tends to be relative. The first point that is stable is determined to have completed the work of focusing the target, and its elimination ratio is marked as b.

Step 5: Reproduce the image with the value of each pixel when the elimination ratio is b, which is the best imaging result.

In addition, several details of the algorithm implementation process are explained as follows:

(1) β is related to the imaging resolution of the through-wall radar. Usually, the step length is approximated by the ratio of the minimum resolution unit of the radar imaging to the imaging area, that is:

Among them, δ _r is the range resolution, δ _d is the azimuth resolution, and S _I is the area of the imaging area, which can be obtained from the imaging scene and the original image.

(2) A small number of target pixel vectors will be mixed with background pixel vectors with similar coefficients. For the purpose of retaining target pixels and ensuring target imaging quality, the first point where the curve tends to be stable is often selected.

(3) Also on the premise of ensuring the image quality of the target, the algorithm eliminates redundant pixel vectors as much as possible to obtain the best imaging result, so the "best" here is a relative concept.

As shown in FIG. 4 , an imaging system based on through-wall radar clutter suppression provided by the present invention includes:

The acquiring module 401 is used for acquiring the original echo signal received by the through-wall radar.

The imaging module 402 is configured to perform imaging processing on the original echo signal to determine the original image.

The discrete coefficient determination module 403 is configured to determine the discrete coefficient of the pixel vector of the original image according to the original image. The discrete coefficient determination module specifically includes:

A discrete coefficient determination unit, configured to determine the discrete coefficient of the original image pixel vector using the following formula according to the original image:

Among them, V _i is the discrete coefficient, σ _i is the standard deviation of the vector elements, μ _i is the mean value of the vector elements, K is the dimension of the pixel vector, q _ik is the pixel vector, i is the number of pixel vectors, and k is the pixel vector The number of vector dimensions.

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.

The step length determination module 405 is configured to determine the step length according to the original image.

The pixel elimination ratio determination module 406 is configured to determine the pixel elimination ratio according to the step length.

A first elimination ratio determination module 407, configured to determine a first elimination ratio by using the sorted pixel vector and the pixel elimination ratio.

The second elimination ratio determination module 408 is configured to determine a second elimination ratio according to the first elimination ratio and the pixel elimination ratio.

The reproduction module 409 is configured to reproduce according to the pixel value corresponding to the second elimination ratio to obtain an imaging result.

The invention avoids entangled complex echo signals, and performs pixel-level clutter suppression in the image domain. Combined with the back projection in through-the-wall imaging (BP-TWI) algorithm, the corresponding pixel vector is formed by the components of pixels in each antenna channel. It is not difficult to find that the discrete degree of the elements of the target pixel vector is much lower than that of other pixel vectors, so the discrete coefficient is introduced to quantitatively describe this feature. Next, according to a certain step length, the pixel vectors with larger discrete coefficients are gradually eliminated. In order to better mark the pixel vector elimination process, the key points of main clutter suppression and target focus are determined according to the image intensity and residual pixel mean value, so as to maximize the suppression of clutter and background pixel vectors and obtain the best imaging results. Finally, the effectiveness and reliability of the algorithm are verified by the simulation under normal conditions and strong interference conditions, combined with the comparison of background cancellation imaging.

Aiming at the problem of clutter suppression of through-wall radar, an image domain suppression algorithm based on pixel vector elimination is proposed. Simulations have proved that the algorithm has good effectiveness and reliability, and can suppress clutter thoroughly, which provides a good basis for subsequent detection and identification. Accurate target information. In view of the fact that the general echo domain algorithm can only suppress the main clutter of the wall, and the image quality of the target is not high, the algorithm focuses on the pixel discrete features in the image, and eliminates the redundant pixel vector to make the target image clear and accurate. The dual-index evaluation system of wave suppression effect also greatly improves the reliability of the algorithm.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments can be referred to each other.

In this paper, specific examples are used to illustrate the principles and implementations of the present invention. The descriptions of the above embodiments are only used to help understand the methods and core ideas of the present invention; meanwhile, for those skilled in the art, according to the present invention There will be changes in the specific implementation and application scope. In conclusion, the contents of this specification should not be construed as limiting the present invention.

Claims (5)

1. an imaging method based on through-wall radar clutter suppression, is characterized in that, comprises: Obtain the original echo signal received by the through-wall radar; Perform imaging processing on the original echo signal to determine the original image; determining the discrete coefficient of the pixel vector of the original image according to the original image; Sort the pixel vector of the original image according to the discrete coefficient to obtain the sorted pixel vector; determining the step length according to the original image; Determine the pixel elimination ratio according to the step length; Using the sorted pixel vector and the pixel elimination ratio to determine a first elimination ratio; determining a second elimination ratio according to the first elimination ratio and the pixel elimination ratio; Perform reproduction according to the pixel value corresponding to the second elimination ratio to obtain an imaging result; The determining the step length according to the original image specifically includes: determining the step length according to the ratio of the minimum resolution unit of the original image to the imaging area; The determining the first elimination ratio by using the sorted pixel vector and the pixel elimination ratio specifically includes: determining the image intensity under the pixel elimination ratio by using the sorted pixel vector and the pixel elimination ratio; The image intensity is drawn into an image intensity change curve, and the first point that tends to be stable in the image intensity change curve is determined as the first elimination ratio; The determining the image intensity under the pixel elimination ratio using the sorted pixel vector and the pixel elimination ratio specifically includes: determining the pixel elimination ratio under the pixel elimination ratio by using the sorted pixel vector and the pixel elimination ratio according to the following formula: The image intensity of:

where _II is the image intensity, Q is the total number of pixels, and A _i is the amplitude of the ith pixel; The determining the second elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes: Determine the residual pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio; Drawing the residual pixel mean value into a residual pixel mean value change curve, and determining that the first point that tends to be stable in the residual pixel mean value change curve is the second elimination ratio; The determining the average value of the remaining pixels under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes: According to the first elimination ratio and the pixel elimination ratio, the following formula is used to determine the residual pixel mean value under the pixel elimination ratio:

Among them, M _RP is the mean value of the remaining pixels, n is the upper limit of the remaining pixel labels, m is the lower limit of the remaining pixel labels, and A _i is the amplitude of the ith pixel. 2 . The imaging method based on through-wall radar clutter suppression according to claim 1 , wherein the determining the discrete coefficient of the pixel vector of the original image according to the original image specifically includes: 3 . According to the original image, the following formula is used to determine the discrete coefficient of the pixel vector of the original image:

Among them, V _i is the discrete coefficient, σ _i is the standard deviation of the vector elements, μ _i is the mean value of the vector elements, K is the dimension of the pixel vector, q _ik is the pixel vector, i is the number of pixel vectors, and k is the pixel vector The number of vector dimensions. 3. The imaging method based on through-wall radar clutter suppression according to claim 1, wherein the pixel vector of the original image is sorted according to the discrete coefficient to obtain the sorted pixel vector, specifically include: Arrange the pixel vectors of the original image in descending order according to the discrete coefficients to obtain the sorted pixel vectors. 4. An imaging system based on through-wall radar clutter suppression, characterized in that, comprising: The acquisition module is used to acquire the original echo signal received by the through-wall radar; an imaging module, configured to perform imaging processing on the original echo signal to determine the original image; a discrete coefficient determination module, configured to determine the discrete coefficient of the pixel vector of the original image according to the original image; a sorting module, configured to sort the pixel vectors of the original image according to the discrete coefficients to obtain sorted pixel vectors; a step length determination module, configured to determine the step length according to the original image; a pixel elimination ratio determination module, configured to determine the pixel elimination ratio according to the step length; a first elimination ratio determination module, configured to determine a first elimination ratio by using the sorted pixel vector and the pixel elimination ratio; A second elimination ratio determination module, configured to determine a second elimination ratio according to the first elimination ratio and the pixel elimination ratio; a reproduction module, configured to reproduce according to the pixel value corresponding to the second elimination ratio to obtain an imaging result; The determining the step length according to the original image specifically includes: determining the step length according to the ratio of the minimum resolution unit of the original image to the imaging area; The determining the first elimination ratio by using the sorted pixel vector and the pixel elimination ratio specifically includes: determining the image intensity under the pixel elimination ratio by using the sorted pixel vector and the pixel elimination ratio; The image intensity is drawn into an image intensity change curve, and the first point that tends to be stable in the image intensity change curve is determined as the first elimination ratio; The determining the image intensity under the pixel elimination ratio using the sorted pixel vector and the pixel elimination ratio specifically includes: determining the pixel elimination ratio under the pixel elimination ratio by using the sorted pixel vector and the pixel elimination ratio according to the following formula: The image intensity of:

where _II is the image intensity, Q is the total number of pixels, and A _i is the amplitude of the ith pixel; The determining the second elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes: Determine the residual pixel mean value under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio; Drawing the residual pixel mean value into a residual pixel mean value change curve, and determining that the first point that tends to be stable in the residual pixel mean value change curve is the second elimination ratio; The determining the average value of the remaining pixels under the pixel elimination ratio according to the first elimination ratio and the pixel elimination ratio specifically includes: According to the first elimination ratio and the pixel elimination ratio, the following formula is used to determine the residual pixel mean value under the pixel elimination ratio:

Among them, M _RP is the mean value of the remaining pixels, n is the upper limit of the remaining pixel labels, m is the lower limit of the remaining pixel labels, and A _i is the amplitude of the ith pixel. 5. The imaging system based on through-wall radar clutter suppression according to claim 4, wherein the discrete coefficient determination module specifically comprises: A discrete coefficient determination unit, configured to determine the discrete coefficient of the original image pixel vector using the following formula according to the original image:

Among them, V _i is the discrete coefficient, σ _i is the standard deviation of the vector elements, μ _i is the mean value of the vector elements, K is the dimension of the pixel vector, q _ik is the pixel vector, i is the number of pixel vectors, and k is the pixel vector The number of vector dimensions.

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