Two-dimensional CFAR threshold calculation method based on integral image

Abstract

The invention relates to a two-dimensional constant false alarm threshold calculation method based on an integral image, and belongs to the field of radar technology. The method includes constructing an integral image matrix; calculating the vertex coordinate positions corresponding to the reference window and the protection window according to a given reference window and a protection window, and the element values ​​of the corresponding points of the integral image matrix can be known from the vertex coordinate positions; calculating the cumulative sum of all elements in the reference window and the protection window; calculating the total number of elements contained in the reference window and the protection window; then calculating the mean value and sum of the clutter amplitude in the zigzag window area; and calculating the CFAR threshold value according to the mean value and sum of the clutter amplitude in the zigzag window area. Compared with the traditional method, the number of calculations is independent of the given reference window and the protection window size, and the total number of calculations is less than that of the traditional two-dimensional constant false alarm threshold calculation method, which greatly reduces the algorithm time consumption, can meet the real-time requirements of the project, and has stronger applicability.

Description

Technical Field

[0001] The invention belongs to the technical field of radars, relates to a constant false alarm detection algorithm of a radar, and specifically relates to a new two-dimensional constant false alarm threshold calculation method based on an integral image. Background Art

[0002] The constant false alarm target detection technology is to adaptively adjust the radar detection threshold when the amplitude of the clutter changes, so that the false alarm probability remains constant. The use of constant false alarm detection technology can ensure that the signal processor is not overloaded due to strong interference, so that the radar target detection system can work normally. Therefore, the use of constant false alarm detection technology is of great significance. In radar target detection, constant false alarm detection technology must be used. The specific implementation form of CFAR detection technology is CFAR detector. When traditional radar target detection projects are implemented, mean-type CFAR detection is mostly used, including CA-CFAR, GO-CFAR, SO-CFAR, etc. Figure 1 Schematic diagram of mean-class CFAR detection.

[0003] The study found that the noise and clutter in the radar background exist in both the distance and Doppler domains, and the local noise can be considered a stable Gaussian random process after removing outliers. Obviously, the two-dimensional CFAR detection uses the units in the two-dimensional distance-Doppler space near the unit to be detected as reference sliding windows, which makes the CFAR detection process more reasonable and effective than the traditional one-dimensional distance domain or Doppler frequency domain reference sliding windows. Figure 2 Schematic diagram of two-dimensional CFAR detection.

[0004] Integral image was proposed by Viola et al. in 2001. They pointed out that by constructing integral image, the calculation of the sum of pixels in a rectangular area can be completed by three additions. This can be used to speed up the detection.

[0005] For an array a(x), the prefix addition output b(x) can be expressed as

[0006]

[0007] Suppose there is an image I(x,y), then the integral image can be expressed as

[0008]

[0009] like Figure 3 As shown, the value of the integral image at (x, y) is the sum of the pixels of the original image in the rectangular area determined by (0, 0) and (x, y). Summary of the invention

[0010] Technical issues to be solved

[0011] The technical problem to be solved by the present invention is: Figure 2 As shown in the figure, the traditional two-dimensional CFAR threshold calculation method is to use the accumulation method to calculate the sum of all elements in the reference window and protection window corresponding to the target to be measured after a reasonable reference window and protection window are given, and then the difference between the sum of elements in the reference window and the sum of elements in the protection window is divided by the number of elements in the corresponding circular window area to obtain the mean value of the clutter amplitude in the circular window area. The mean value multiplied by the threshold factor is the two-dimensional CFAR threshold. The number of additions required to solve the threshold using this method is related to the size of the selected reference window and protection window, and the number of repeated calculations is large, the amount of calculation is large, and the time is long, so the engineering practicality is not strong.

[0012] Technical Solution

[0013] A two-dimensional CFAR threshold calculation method based on integral image, characterized by the following steps:

[0014] Step 1: Given that the original amplitude modulus matrix is ​​I, the number of matrix rows is dis, the number of columns is dpl, the number of reference units in the distance dimension is selected as ref_dis, the number of protection units is prt_dis, the number of reference units in the azimuth dimension is ref_dpl, and the number of protection units is prt_dpl; construct all-0 matrices Amp and Num, the number of matrix rows is dis+2*(ref_dis+prt_dis), the number of columns is dpl+2*(ref_dpl+prt_dpl), and the matrix is ​​assigned values ​​as follows:

[0015] Amp(ref_dis+prt_dis+1:dis+ref_dis+prt_dis,ref_dpl+prt_dpl+1:dpl+ref_dpl+prt_dpl)=I

[0016] Num(ref_dis+prt_dis+1:dis+ref_dis+prt_dis,ref_dpl+prt_dpl+1:dpl+ref_dpl+prt_dpl)=1

[0017] Step 2: Sum the two matrices constructed above by row and column respectively, and obtain the amplitude and matrix SumAmp, the number of points and the matrix SumNum as follows:

[0018]

[0019]

[0020] Among them, 0<m≤dis+2*(ref_dis+prt_dis), 0<n≤dpl+2*(ref_dpl+prt_dpl);

[0021] Step 3: Assume that the coordinates of the point to be detected O are (x, y), the reference window corresponding to point O is ABCD, and the protection window is abcd. Calculate the coordinates of A, B, C, D, a, b, c, d A(x+ref_dis+prt_dis, y+ref_dpl+prt_dpl), B(x+ref_dis+prt_dis, y-ref_dpl-prt_dpl), C(x-ref_dis-prt_dis, y-ref_d pl-prt_dpl), D(x-ref_dis-prt_dis,y+ref_dpl+prt_dpl), a(x+prt_dis,y+prt_dpl), b(x+prt_dis,y-prt_dpl), c(x-prt_dis,y-prt_dpl), d(x-prt_dis,y+prt_dpl), calculate the sum of all elements in the reference window and protection window respectively. ABCD 、Sum abcd and the number of elements Sum NABCD 、Sum Nabcd :

[0022] Sum ABCD =SumAmp(m C ,n C )-SumAmp(m B ,n B )-SumAmp(m D ,n D )+SumAmp(m A ,n A )

[0023] Sum abcd =SumAmp(m c ,n c )-SumAmp(m b ,n b )-SumAmp(m d ,n d )+SumAmp(m a ,n a )

[0024] Sum NABCD =SumNum(m C ,n C )-SumNum(m B ,n B )-SumNum(m D ,n D )+SumNum(m A ,n A )

[0025] Sum Nabcd =SumNum(m c ,n c )-SumNum(m b ,n b )-SumNum(m d ,n d )+SumNum(m a ,n a )

[0026] Step 4: Calculate the mean clutter amplitude in the circular window area composed of ABCD and abcd:

[0027]

[0028] Step 5: Assume the constant false alarm threshold value is k, the threshold factor is factor, and we can get

[0029]

[0030] A computer system, characterized in that it comprises: one or more processors, and a computer-readable storage medium for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method.

[0031] A computer-readable storage medium, characterized in that it stores computer-executable instructions, which are used to implement the above method when executed.

[0032] A computer program, characterized by comprising computer executable instructions, which are used to implement the above method when executed.

[0033] Beneficial Effects

[0034] The invention proposes a two-dimensional constant false alarm threshold calculation method based on integral image. Compared with the traditional method, the number of calculations is independent of the given reference window and protection window size, and the total number of calculations is less than that of the traditional two-dimensional constant false alarm threshold calculation method, which greatly reduces the algorithm time consumption, can meet the real-time requirements of engineering, and has stronger applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like components throughout the drawings.

[0036] Figure 1 It is a detection diagram of mean-class CFAR;

[0037] Figure 2It is a detection schematic diagram of two-dimensional CFAR;

[0038] Figure 3 It is a schematic diagram of the principle of prefix addition and integral image;

[0039] Figure 4 It is the corresponding diagram of the reference window, protection window and integral image of the two-dimensional CFAR target to be measured;

[0040] Figure 5 It is a schematic diagram of the algorithm flow of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0042] The present invention uses the principle of integral image, firstly uses the cumsum function twice to calculate the cumulative sum of the corresponding rows and columns of the amplitude modulus matrix Amp and the all-one matrix Num, and obtains the integral image matrices SumAmp and SumNum: Secondly, according to the given reference window and protection window, the corresponding vertex coordinates A, B, C, D of the reference window and the protection window are calculated, such as Figure 4 As shown, the element value of the corresponding point in the integral image matrix can be known from the vertex coordinate position; ABCD =SumAmp(m C ,n C )-SumAmp(m B ,n B )-SumAmp(m D ,n D )+SumAmp(m A ,n A )、Sum abcd =SumAmp(m c ,n c )-SumAmp(m b ,n b )-SumAmp(m d ,n d )+SumAmp(m a ,n a ) can calculate the cumulative sum of all elements in the reference window and the protection window, and Sum NABCD =SumNum(m C ,n C )-SumNum(m B,n B )-SumNum(m D ,n D )+SumNum(m A ,n A )、Sum Nabcd =SumNum(m c ,n c )-SumNum(m b ,n b )-SumNum(m d ,n d )+SumNum(m a ,n a ) can calculate the total number of elements contained in the reference window and the protection window, then the mean clutter amplitude in the round-shaped window area is Finally, let the constant false alarm threshold value be k and the threshold factor be factor, and we can get the CFAR threshold value.

[0043] like Figure 5 As shown, the specific implementation steps of the present invention are as follows:

[0044] Step 1. The original amplitude modulus matrix is ​​known to be I, the number of matrix rows is dis, and the number of columns is dpl. According to experience, the number of reference units in the distance dimension is selected as ref_dis, the number of protection units is prt_dis, the number of reference units in the azimuth dimension is ref_dpl, and the number of protection units is prt_dpl; construct all-0 matrices Amp and Num, the number of matrix rows is dis+2*(ref_dis+prt_dis), the number of columns is dpl+2*(ref_dpl+prt_dpl), and the matrix is ​​assigned values ​​as follows:

[0045] Amp(ref_dis+prt_dis+1:dis+ref_dis+prt_dis,ref_dpl+prt_dpl+1:dpl+ref_dpl+prt_dpl)=I (3)

[0046] Num(ref_dis+prt_dis+1:dis+ref_dis+prt_dis,ref_dpl+prt_dpl+1:dpl+ref_dpl+prt_dpl)=1(4)

[0047] Step 2: Sum the two matrices constructed above by row and column respectively, and obtain the amplitude and matrix SumAmp, the number of points and matrix SumNum as follows:

[0048]

[0049]

[0050] Among them, 0<m≤dis+2*(ref_dis+prt_dis), 0<n≤dpl+2*(ref_dpl+prt_dpl);

[0051] Step 3. Figure 4 As shown, suppose the coordinates of the point O to be detected are (x, y), the reference window corresponding to point O is ABCD, and the protection window is abcd. Calculate the coordinates of A, B, C, D, a, b, c, d A(x+ref_dis+prt_dis, y+ref_dpl+prt_dpl), B(x+ref_dis+prt_dis, y-ref_dpl-prt_dpl), C(x-ref_dis-prt_dis, y-ref_dpl-prt_dpl) t_dpl), D(x-ref_dis-prt_dis,y+ref_dpl+prt_dpl), a(x+prt_dis,y+prt_dpl), b(x+prt_dis,y-prt_dpl), c(x-prt_dis,y-prt_dpl), d(x-prt_dis,y+prt_dpl), according to the principle of image integration, calculate the sum of all elements in the reference window and the protection window respectively. ABCD 、Sum abcd and the number of elements Sum NABCD 、Sum Nabcd :

[0052] Sum ABCD =SumAmp(m C ,n C )-SumAmp(m B ,n B )-SumAmp(m D ,n D )+SumAmp(m A ,n A ) (7)

[0053] Sum abcd =SumAmp(m c ,n c )-SumAmp(m b ,n b )-SumAmp(m d ,n d )+SumAmp(m a ,n a ) (8)

[0054] Sum NABCD =SumNum(mC ,n C )-SumNum(m B ,n B )-SumNum(m D ,n D )+SumNum(m A ,n A ) (9)

[0055] Sum Nabcd =SumNum(m c ,n c )-SumNum(m b ,n b )-SumNum(m d ,n d )+SumNum(m a ,n a ) (10)

[0056] Step 4 Figure 4 The amplitude and sum of all points in the gray part of the middle circle ∑ Equal to the amplitude and Sum of all points in the reference window ABCD ABCD Subtract the amplitude and sum of all points in the protection window abcd abcd , Points and Sum N Equal to the sum of all points in the reference window ABCD NABCD Subtract the sum of all points in the protection window abcd Nabcd , then the mean clutter amplitude in the circular window area is:

[0057]

[0058] Step 5: Assume the constant false alarm threshold value is k, the threshold factor is factor, and we can get

[0059]

[0060] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should be included in the protection scope of the present invention.

Claims

1. A two-dimensional CFAR threshold calculation method based on integral image, characterized in that Here are the steps: Step 1: Given that the original amplitude modulus matrix is ​​I, the number of matrix rows is dis, the number of columns is dpl, the number of reference units in the distance dimension is selected as ref_dis, the number of protection units is prt_dis, the number of reference units in the azimuth dimension is ref_dpl, and the number of protection units is prt_dpl; construct all-0 matrices Amp and Num, the number of matrix rows is dis+2*(ref_dis+prt_dis), the number of columns is dpl+2*(ref_dpl+prt_dpl), and the matrix is ​​assigned values ​​as follows: Amp(ref_dis+prt_dis+1:dis+ref_dis+prt_dis,ref_dpl+prt_dpl+1:dpl+ref_dpl+prt_dpl)=I Num(ref_dis+prt_dis+1:dis+ref_dis+prt_dis,ref_dpl+prt_dpl+1:dpl+ref_dpl+prt_dpl)=1 Step 2: Sum the two matrices constructed above by row and column respectively, and obtain the amplitude and matrix SumAmp, the number of points and the matrix SumNum as follows: Among them, 0<m≤dis+2*(ref_dis+prt_dis), 0<n≤dpl+2*(ref_dpl+prt_dpl); Step 3: Assume that the coordinates of the point to be detected O are (x, y), the reference window corresponding to point O is ABCD, and the protection window is abcd. Calculate the coordinates of A, B, C, D, a, b, c, d A(x+ref_dis+prt_dis, y+ref_dpl+prt_dpl), B(x+ref_dis+prt_dis, y-ref_dpl-prt_dpl), C(x-ref_dis-prt_dis, y-ref_d pl-prt_dpl), D(x-ref_dis-prt_dis,y+ref_dpl+prt_dpl), a(x+prt_dis,y+prt_dpl), b(x+prt_dis,y-prt_dpl), c(x-prt_dis,y-prt_dpl), d(x-prt_dis,y+prt_dpl), calculate the sum of all elements in the reference window and protection window respectively. ABCD 、Sum abcd and the number of elements Sum NABCD 、Sum Nabcd : Sum ABCD =SumAmp(m C ,n C )-SumAmp(m B ,n B )-SumAmp(m D ,n D )+SumAmp(m A ,n A ) Sum abcd =SumAmp(m c ,n c )-SumAmp(m b ,n b )-SumAmp(m d ,n d )+SumAmp(m a ,n a ) I am NABCD =SumNum(m C ,n C )-SumNum(m B ,n B )-SumNum(m D ,n D )+SumNum(m A ,n A ) I am Nabcd =SumNum(m c ,n c )-SumNum(m b ,n b )-SumNum(m d ,n d )+SumNum(m a ,n a ) Step 4: Calculate the mean clutter amplitude in the circular window area composed of ABCD and abcd: Step 5: Assume the CFAR threshold value is k and the threshold factor is factor, we can get 2. A computer system, characterized in that include: One or more processors, and a computer-readable storage medium for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method of claim 1.

3. A computer-readable storage medium, characterized in that Computer executable instructions are stored, and when the instructions are executed, they are used to implement the method of claim 1.

4. A computer program product, characterized in that The invention comprises computer executable instructions, which are used to implement the method of claim 1 when being executed.

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