Method and device for resisting same-frequency asynchronous interference based on time-frequency domain joint correlation

Abstract

The invention belongs to the technical field of radar data processing, and particularly relates to a same-frequency asynchronous interference resisting method and device based on time-frequency domain joint correlation, and the method comprises the steps: S1, determining a main beam center of time domain data X of a frame of echo; s2, calculating base noise for the power spectrum data P corresponding to the time domain data X; s3, determining left and right boundaries of a main beam on the frequency gate according to the center of the main beam and the base noise; s4, for the spectrum data, performing zero clearing on the data in the left and right boundary ranges of the main beam; s5, calculating time domain multi-cycle power data of the reset data; step S6, constructing a binary matrix corresponding to the time domain multi-period power data, and performing 0, 1 assignment operation on the binary matrix based on the power mean value of multiple segments of the time domain multi-period power data; and S7, multiplying the binary matrix by the time domain data to obtain new time domain data. According to the invention, the anti-interference capability of the radar is improved.

Description

Technical Field

[0001] The present application belongs to the field of radar data processing technology, and in particular relates to a method and device for resisting co-frequency asynchronous interference based on joint correlation in time and frequency domains. Background Art

[0002] With the development of radar technology, radar is being used more and more widely. The number of various radars, such as airborne, shipborne, warning, navigation, military, and civilian, is gradually increasing. The electromagnetic environment is becoming more complex, and electromagnetic compatibility issues are becoming increasingly prominent. The same-frequency operation of radars will inevitably lead to mutual interference, which will seriously affect the radar target detection performance. In particular, during ground detection, the ground echo signal of the main beam is very strong, and the same-frequency interference signal is superimposed, making the traditional time-domain anti-same-frequency asynchronous interference measures ineffective, affecting the detection and tracking of valuable targets, and greatly affecting the performance of the radar.

[0003] The traditional anti-co-frequency asynchrony method in the ground detection process has the following disadvantages:

[0004] The co-frequency asynchronous interference signal is determined and eliminated through time domain amplitude correlation, but the influence of ground clutter cannot be eliminated, resulting in the inability to effectively remove the co-frequency asynchronous interference signal;

[0005] The threshold of the traditional time domain multi-period data correlation method for determining the co-frequency asynchronous interference signal cannot be adaptive, resulting in the performance of resisting co-frequency asynchronous interference fluctuating with the strength of the echo. Summary of the invention

[0006] In order to solve the above problems, the present application provides a method and device for resisting co-frequency asynchronous interference based on joint correlation in time and frequency domains, so as to solve the adverse effect of the inability to effectively separate the co-frequency asynchronous interference signal due to the superposition of ground clutter, and to solve the impact of the reduced detection performance of the co-frequency asynchronous interference signal caused by the inability of the threshold to adapt.

[0007] The first aspect of the present application provides a method for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation, mainly comprising:

[0008] Step S1: Determine the main beam center N of the time domain data X of a frame of echo fdc ;

[0009] Step S2: for the power spectrum data P corresponding to the time domain data X, a one-dimensional frequency data curve is obtained by accumulating the power spectrum data of the designated long-distance segment of each pulse, and the average value is calculated based on the middle segment data of the one-dimensional frequency data curve to obtain the base noise K. noise ;

[0010] Step S3: On the frequency gate, with the main beam center N fdc As the starting point, search for the base noise K on both sides. noiseThe first difference is less than the threshold value K p point to determine the left boundary of the main beam N lpos and right boundary N rpos ;

[0011] Step S4: For the spectrum data Y corresponding to the time domain data X, clear the data within the left and right boundaries of the main beam to obtain the spectrum data Y. 1 ;

[0012] Step S5: Spectrum data Y 1 After conversion to the time domain, calculate the time domain multi-cycle power data X 2 ;

[0013] Step S6: construct a time domain multi-cycle power data X 2 The corresponding binary matrix X 01 , the time domain multi-period power data X 2 Each range gate is divided into multiple segments according to the azimuth dimension, and the power mean of each segment is calculated as the adaptive threshold base value in the segment. After each data in the segment is subtracted from the adaptive threshold base value, if it is higher than the filtering threshold k, the binary matrix X 01 The data at the corresponding position is set to 0, otherwise it is set to 1;

[0014] Step S7: Binary matrix X 01 Multiply it with the time domain data X to get new time domain data.

[0015] Preferably, step S1 further comprises:

[0016] Step S11, obtaining the first main beam center according to the phase gradient calculation;

[0017] Step S12, calculating the second main beam center according to a theoretical formula;

[0018] Step S13: When the center of the first main beam deviates from the center of the second main beam by more than one quarter of the coherent accumulation point, the center of the second main beam is used as the final main beam center N. fdc , otherwise the first main beam center is taken as the final main beam center N fdc .

[0019] Preferably, in step S11, the first main beam center N is calculated according to the following formula: 1 fdc :

[0020]

[0021] Among them, X 1is the data of the same distance segment of all pulses selected in the time domain data X, Na is the number of coherent accumulation points, conj is the conjugate function, mean is the average function, and atan is the inverse tangent function.

[0022] Preferably, in step S2, the power spectrum data of the specified long-distance segment refers to the power spectrum data of the 0.875Nr-Nr distance segment, and the middle segment data of the one-dimensional frequency data curve refers to the data located in the middle 1 / 2 segment after the one-dimensional frequency data curve is sorted in ascending order.

[0023] The second aspect of the present application provides a device for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation, mainly comprising:

[0024] The main beam center calculation module is used to determine the main beam center N of the time domain data X of a frame of echo fdc ;

[0025] The base noise calculation module is used to obtain a one-dimensional frequency data curve by accumulating the power spectrum data P corresponding to the time domain data X at the specified long-distance segment of each pulse, and to obtain the base noise K based on the average value of the middle segment data of the one-dimensional frequency data curve. noise ;

[0026] The main beam range determination module is used to determine the main beam center N on the frequency gate. fdc As the starting point, search for the base noise K on both sides. noise The first difference is less than the threshold value K p point to determine the left boundary of the main beam N lpos and right boundary N rpos ;

[0027] The spectrum data correction module is used to clear the data within the left and right boundaries of the main beam for the spectrum data Y corresponding to the time domain data X to obtain the spectrum data Y 1 ;

[0028] The time domain multi-cycle power data calculation module is used to convert the spectrum data Y 1 After conversion to the time domain, calculate the time domain multi-cycle power data X 2 ;

[0029] Binary matrix construction module, used to construct a multi-period power data X in the time domain 2 The corresponding binary matrix X 01 , the time domain multi-period power data X 2 Each range gate is divided into multiple segments according to the azimuth dimension, and the power mean of each segment is calculated as the adaptive threshold base value in the segment. After each data in the segment is subtracted from the adaptive threshold base value, if it is higher than the filtering threshold k, the binary matrix X 01The data at the corresponding position is set to 0, otherwise it is set to 1;

[0030] The time domain data correction module is used to convert the binary matrix X 01 Multiply it with the time domain data X to get new time domain data.

[0031] Preferably, the main beam center calculation module includes:

[0032] A first main beam center calculation unit, used for obtaining the first main beam center by calculating the phase gradient;

[0033] A second main beam center calculation unit, used to calculate the second main beam center according to a theoretical formula;

[0034] A main beam center selection unit is used to select the second main beam center as the final main beam center N when the first main beam center deviates from the second main beam center by more than one quarter of the coherent accumulation point. fdc , otherwise the first main beam center is taken as the final main beam center N fdc .

[0035] Preferably, the first main beam center N is calculated according to the following formula: 1 fdc :

[0036]

[0037] Among them, X 1 is the data of the same distance segment of all pulses selected in the time domain data X, Na is the number of coherent accumulation points, conj is the conjugate function, mean is the average function, and atan is the inverse tangent function.

[0038] Preferably, the power spectrum data of the specified long-distance segment refers to the power spectrum data of the 0.875Nr-Nr distance segment, and the middle segment data of the one-dimensional frequency data curve refers to the data located in the middle 1 / 2 segment after the one-dimensional frequency data curve is sorted in ascending order.

[0039] The present application can be applied to resisting co-frequency asynchronous interference in the radar coherent mode, thereby improving the anti-interference capability of the radar. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flowchart of a preferred embodiment of the method for combating co-frequency asynchronous interference based on joint correlation in the time-frequency domain of the present application.

[0041] Figure 2 This is a schematic diagram of time domain data.

[0042] Figure 3 This is a schematic diagram for calibrating the position of the co-frequency asynchronous interference signal.

[0043] Figure 4 Schematic diagram of the power spectrum before processing.

[0044] Figure 5 This is a schematic diagram of the power spectrum after processing by this application. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical scheme and advantages of the implementation of this application clearer, the technical scheme in the implementation of this application will be described in more detail in combination with the drawings in the implementation of this application. In the drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described implementation is a part of the implementation of this application, not all of the implementations. The implementation described below with reference to the drawings is exemplary and is intended to be used to explain this application, and cannot be understood as a limitation on this application. Based on the implementation in this application, all other implementations obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. The implementation of this application is described in detail below in combination with the drawings.

[0046] The first aspect of the present application provides a method for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation, such as Figure 1 As shown, it mainly includes:

[0047] Step S1: Determine the main beam center N of the time domain data X of a frame of echo fdc ;

[0048] Step S2: for the power spectrum data P corresponding to the time domain data X, a one-dimensional frequency data curve is obtained by accumulating the power spectrum data of the designated long-distance segment of each pulse, and the average value is calculated based on the middle segment data of the one-dimensional frequency data curve to obtain the base noise K. noise ;

[0049] Step S3: On the frequency gate, with the main beam center N fdc As the starting point, search for the base noise K on both sides. noise The first time the difference is less than the threshold value K p point to determine the left boundary of the main beam N lpos and right boundary N rpos ;

[0050] Step S4: For the spectrum data Y corresponding to the time domain data X, clear the data within the left and right boundaries of the main beam to obtain the spectrum data Y. 1 ;

[0051] Step S5: Spectrum data Y 1 After conversion to the time domain, calculate the time domain multi-cycle power data X 2 ;

[0052] Step S6: construct a time domain multi-cycle power data X 2 The corresponding binary matrix X 01 , the time domain multi-period power data X 2 Each range gate is divided into multiple segments according to the azimuth dimension, and the power mean of each segment is calculated as the adaptive threshold base value in the segment. After each data in the segment is subtracted from the adaptive threshold base value, if it is higher than the filtering threshold k, the binary matrix X 01 The data at the corresponding position is set to 0, otherwise it is set to 1;

[0053] Step S7: Binary matrix X 01 Multiply it with the time domain data X to get new time domain data.

[0054] The present application uses the radar received and channel echo data to complete the distance compression and azimuth coherent accumulation calculation, that is, to obtain the time domain data X, the spectrum Y after coherent accumulation, and the power spectrum data P. In step S1, the main beam center calculation is completed, and in steps S2 and S3, the main beam boundary calculation is completed using the accumulated signal power of the spectrum, that is, the power spectrum data P. In steps S4 and S5, the spectrum is deducted from the main clutter signal and returned to the azimuth time domain. In step S6, the distance frequency domain and azimuth time domain signals are segmented according to the azimuth, and the adaptive threshold of each segment is calculated to complete the selection of the same-frequency asynchronous interference signal in each segment. In step S7, the original time domain signal of the corresponding pulse is subjected to the same-frequency asynchronous interference signal elimination, and finally the same-frequency asynchronous interference is resisted, which is described in detail below.

[0055] Step S1 is used to calculate the main beam center, which can usually be calculated using an existing theoretical formula or by other methods. For example, in some optional implementations, step S1 further includes:

[0056] Step S11, obtaining the first main beam center according to the phase gradient calculation;

[0057] Step S12, calculating the second main beam center according to a theoretical formula;

[0058] Step S13: When the center of the first main beam deviates from the center of the second main beam by more than one quarter of the coherent accumulation point, the center of the second main beam is used as the final main beam center N. fdc , otherwise the first main beam center is taken as the final main beam center N fdc .

[0059] This embodiment calculates the main beam center in two ways, namely, calculating the first main beam center and the second main beam center according to the phase gradient and the theoretical formula respectively, and then selecting one of them as the final main beam center according to the situation.

[0060] In some optional implementations, in step S11, the first main beam center N is calculated according to the following formula: 1 fdc :

[0061]

[0062] Among them, X 1 is the data of the same distance segment of all pulses selected in the time domain data X, Na is the number of coherent accumulation points, conj is the conjugate function, mean is the average function, and atan is the inverse tangent function.

[0063] It should be noted that the time domain data X is Figure 2 As shown in Figure 1, radar data processing is usually divided into range processing and azimuth processing, such as Figure 3 The azimuth dimension and the distance dimension in the azimuth dimension contain 64 frequency gates, and the distance dimension contains 1600 range gates. In the above formula, the number of coherent accumulation points is the frequency gate. For example, a radar data contains 16 pulses, each pulse contains 400 range gates, and each pulse selects the data of the same range segment. For example, pulse 1 selects the data of the 300-350th range gate segment, and pulses 2-16 also select the data of the 300-350th range gate segment. Then, the center N of the first main beam is calculated based on the above formula. 1 fdc .

[0064] In addition to calculating the center of the first main beam by taking the phase gradient, the center of the second main beam is also calculated by the following formula:

[0065] N 2 fdc =Na×(2×Va / λ×cos(θ)×cos(α)) / PRF;

[0066] Where λ is the wavelength, Va is the platform ground speed, θ is the azimuth angle for beam stabilization, α is the pitch angle for beam stabilization, Na is the number of coherent integration points, and PRF is the transmission frequency.

[0067] After the above calculation, when the center of the first main beam N 1 fdc With the second main beam center N 2 fdc When the deviation exceeds one-fourth of the coherent accumulation points Na, the phase gradient calculation is considered to be disturbed and the second main beam center N is used. 2 fdc , otherwise the first main beam center N is used 1 fdc , and finally get the main beam center N fdc .

[0068] Step S2 is used to calculate the base noise K noise Here, the data of the long-distance segment Nr / 8 is usually selected for processing to obtain a one-dimensional frequency data curve. For example, the 400 range gates mentioned above are selected in the long-distance segment for cumulative calculation, and then the data of approximately 1 / 2 in the middle are sorted and selected to calculate the real-time background noise. For example, in some optional embodiments, in step S2, the power spectrum data of the specified long-distance segment refers to the power spectrum data of the 0.875Nr-Nr distance segment, and the middle segment data of the one-dimensional frequency data curve refers to the data located in the middle 1 / 2 segment after the one-dimensional frequency data curve is sorted in ascending order. In an alternative embodiment, the data of the long-distance segment Nr / 8 may also be data such as 0.8Nr-0.925Nr, or data of 0.825Nr-0.95Nr.

[0069] In this embodiment, for the time domain data X, it has the spectrum data Y corresponding to to obtained by Fourier transform, and also has the power spectrum data P corresponding to it obtained after the power calculation, that is, in step S2, a frame of echo power spectrum data P can be obtained by calculating the time domain data X of a frame of echo, and the data of the range gate of 350-400 are selected and accumulated and calculated according to the same frequency gate (16 frequency gates, each frequency gate processes the data of these 50 range gates) and averaged to obtain a one-dimensional frequency data curve P', and P' is sorted in ascending order to obtain P s ' ort , take P s ' ort The mean value K of the middle half noise As the real-time background noise of the spectrum data P.

[0070] With the main beam center N given in step S1 fdc And the base noise K given in step S2 noise After that, the left and right boundaries of the main beam can be determined, with the center of the main beam N fdc As the starting point, search for the base noise K on both sides. noise The first time the difference is less than K p The threshold point is determined as the left boundary of the main clutter N lpos and right boundary N rpos . Threshold value K p Can be determined by summarizing experience.

[0071] Step S4 is used to clear the corresponding data in the spectrum data Y based on the left and right boundary ranges determined above to obtain new spectrum data Y. 1 , then in step S5, it is converted to the time domain through inverse Fourier transform and the power is calculated, as shown in the following formula.

[0072] X 2=abs(IFFT(Y 1 i )) 2 i∈[0,Nr-1];

[0073] Where abs refers to the spectrum data Y 1 Function for power calculation after inverse Fourier transform (IFFT).

[0074] With new power data X 2 Then, in step S6, a binary matrix X needs to be reconstructed. 01 , as the name implies, the binary matrix X 01 All items in have only two optional values, either 1 or 0. Specifically, the time domain multi-cycle power data X 2 Each range gate is divided into multiple segments according to the azimuth dimension, and the power mean P of each segment is calculated. mean , as the adaptive threshold base value in the segment, after subtracting the adaptive threshold base value from each data in the segment, if it is higher than the filtering threshold k, then the binary matrix X 01 The data at the corresponding position is set to 0, otherwise it is set to 1. Each range gate is processed according to the above process, and finally a sum data matrix X is formed. 2 The corresponding 0, 1 binary matrix X 01 , the corresponding binary image is Figure 3 shown.

[0075] Finally, in step S7, the binary matrix X 01 Multiply it with the time domain data X after the echo data is compressed to complete the time-frequency domain joint correlation to resist the same-frequency asynchronous interference.

[0076] Figure 4 is the power spectrum before processing, Figure 5 is the processed power spectrum, Figure 4 and Figure 5 By comparison, it can be seen that the time-frequency domain joint correlation has an obvious effect in resisting co-frequency asynchronous interference. Therefore, the present application realizes the anti-co-frequency asynchronous interference signal processing under the radar downward-looking ground detection mode.

[0077] The second aspect of the present application provides a device for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation corresponding to the above method, mainly comprising:

[0078] The main beam center calculation module is used to determine the main beam center N of the time domain data X of a frame of echo fdc ;

[0079] The base noise calculation module is used to obtain a one-dimensional frequency data curve by accumulating the power spectrum data P corresponding to the time domain data X at the specified long-distance segment of each pulse, and to obtain the base noise K based on the average value of the middle segment data of the one-dimensional frequency data curve. noise ;

[0080] The main beam range determination module is used to determine the main beam center N on the frequency gate. fdc As the starting point, search for the base noise K on both sides. noise The first time the difference is less than the threshold value K p point to determine the left boundary of the main beam N lpos and right boundary N rpos ;

[0081] The spectrum data correction module is used to clear the data within the left and right boundaries of the main beam for the spectrum data Y corresponding to the time domain data X to obtain the spectrum data Y 1 ;

[0082] The time domain multi-cycle power data calculation module is used to convert the spectrum data Y 1 After conversion to the time domain, calculate the time domain multi-cycle power data X 2 ;

[0083] Binary matrix construction module, used to construct a multi-period power data X in the time domain 2 The corresponding binary matrix X 01 , the time domain multi-period power data X 2 Each range gate is divided into multiple segments according to the azimuth dimension, and the power mean of each segment is calculated as the adaptive threshold base value in the segment. After each data in the segment is subtracted from the adaptive threshold base value, if it is higher than the filtering threshold k, the binary matrix X 01 The data at the corresponding position is set to 0, otherwise it is set to 1;

[0084] The time domain data correction module is used to convert the binary matrix X 01 Multiply it with the time domain data X to get new time domain data.

[0085] In some optional implementations, the main beam center calculation module includes:

[0086] A first main beam center calculation unit, used for obtaining the first main beam center by calculating the phase gradient;

[0087] A second main beam center calculation unit, used to calculate the second main beam center according to a theoretical formula;

[0088] A main beam center selection unit is used to select the second main beam center as the final main beam center N when the first main beam center deviates from the second main beam center by more than one quarter of the coherent accumulation point.fdc , otherwise the first main beam center is taken as the final main beam center N fdc .

[0089] In some optional implementations, the first main beam center N is calculated according to the following formula: 1 fdc :

[0090]

[0091] Among them, X 1 is the data of the same distance segment of all pulses selected in the time domain data X, Na is the number of coherent accumulation points, conj is the conjugate function, mean is the average function, and atan is the inverse tangent function.

[0092] In some optional embodiments, the power spectrum data of the specified long-distance segment refers to the power spectrum data of the 0.875Nr-Nr distance segment, and the middle segment data of the one-dimensional frequency data curve refers to the data located in the middle 1 / 2 segment after the one-dimensional frequency data curve is sorted in ascending order.

[0093] The present application utilizes the mutual error correction method of theoretically calculating the clutter center and the phase gradient to calculate the main clutter center, which can effectively avoid the disadvantage that the phase gradient calculation is affected by strong target interference; the present application can realize fast and accurate calculation of the real-time data mean, so as to adaptively determine the threshold of co-frequency asynchronous interference detection, effectively avoiding the disadvantage that the conventional fixed threshold detection is affected by the strength of terrain echo; the present application utilizes the frequency domain to deduct the clutter data and return to the time domain for detection, which solves the problem that the time domain co-frequency asynchronous interference signal is submerged in the clutter and cannot be detected; the present application can be applied to the anti-co-frequency asynchronous interference in the radar coherent mode, and finally improve the anti-interference capability of the radar.

[0094] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for resisting co-frequency asynchronous interference based on joint correlation in time and frequency domains, characterized in that: include: Step S1: Determine the main beam center N of the time domain data X of a frame of echo fdc ; Step S2: for the power spectrum data P corresponding to the time domain data X, a one-dimensional frequency data curve is obtained by accumulating the power spectrum data of the designated long-distance segment of each pulse, and the average value is calculated based on the middle segment data of the one-dimensional frequency data curve to obtain the base noise K. noise ; Step S3: On the frequency gate, with the main beam center N fdc As the starting point, search for the base noise K on both sides. noise The first difference is less than the threshold value K p point to determine the left boundary of the main beam N lpos and right boundary N rpos ; Step S4: For the spectrum data Y corresponding to the time domain data X, clear the data within the left and right boundaries of the main beam to obtain the spectrum data Y. 1 ; Step S5: Spectrum data Y 1 After conversion to the time domain, calculate the time domain multi-cycle power data X 2 ; Step S6: construct a time domain multi-cycle power data X 2 The corresponding binary matrix X 01 , the time domain multi-period power data X 2 Each range gate is divided into multiple segments according to the azimuth dimension, and the power mean of each segment is calculated as the adaptive threshold base value in the segment. After each data in the segment is subtracted from the adaptive threshold base value, if it is higher than the filtering threshold k, the binary matrix X 01 The data at the corresponding position is set to 0, otherwise it is set to 1; Step S7: Binary matrix X 01 Multiply it with the time domain data X to get new time domain data.

2. The method for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation according to claim 1, characterized in that: Step S1 further comprises: Step S11, obtaining the first main beam center according to the phase gradient calculation; Step S12, calculating the second main beam center according to a theoretical formula; Step S13: When the center of the first main beam deviates from the center of the second main beam by more than one quarter of the coherent accumulation point, the center of the second main beam is used as the final main beam center N. fdc , otherwise the first main beam center is taken as the final main beam center N fdc .

3. The method for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation according to claim 2, characterized in that: In step S11, the first main beam center N is calculated according to the following formula: 1 fdc : Among them, X 1 is the data of the same distance segment of all pulses selected in the time domain data X, Na is the number of coherent accumulation points, conj is the conjugate function, mean is the average function, and atan is the inverse tangent function.

4. The method for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation according to claim 1, characterized in that: In step S2, the power spectrum data of the designated long-distance segment refers to the power spectrum data of the 0.875Nr-Nr distance segment, and the middle segment data of the one-dimensional frequency data curve refers to the data located in the middle 1 / 2 segment after the one-dimensional frequency data curve is sorted in ascending order.

5. A device for resisting co-frequency asynchronous interference based on joint correlation in time and frequency domains, characterized in that: include: The main beam center calculation module is used to determine the main beam center N of the time domain data X of a frame of echo fdc ; The base noise calculation module is used to obtain a one-dimensional frequency data curve by accumulating the power spectrum data P corresponding to the time domain data X at the specified long-distance segment of each pulse, and to obtain the base noise K based on the average value of the middle segment data of the one-dimensional frequency data curve. noise ; The main beam range determination module is used to determine the main beam center N on the frequency gate. fdc As the starting point, search for the base noise K on both sides. noise The first difference is less than the threshold value K p point to determine the left boundary of the main beam N lpos and right boundary N rpos ; The spectrum data correction module is used to clear the data within the left and right boundaries of the main beam for the spectrum data Y corresponding to the time domain data X to obtain the spectrum data Y 1 ; The time domain multi-cycle power data calculation module is used to convert the spectrum data Y 1 After conversion to the time domain, calculate the time domain multi-cycle power data X 2 ; Binary matrix construction module, used to construct a multi-period power data X in the time domain 2 The corresponding binary matrix X 01 , the time domain multi-period power data X 2 Each range gate is divided into multiple segments according to the azimuth dimension, and the power mean of each segment is calculated as the adaptive threshold base value in the segment. After each data in the segment is subtracted from the adaptive threshold base value, if it is higher than the filtering threshold k, the binary matrix X 01 The data at the corresponding position is set to 0, otherwise it is set to 1; The time domain data correction module is used to convert the binary matrix X 01 Multiply it with the time domain data X to get new time domain data.

6. The device for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation according to claim 5, characterized in that: The main beam center calculation module includes: A first main beam center calculation unit, used for obtaining the first main beam center by calculating the phase gradient; A second main beam center calculation unit, used to calculate the second main beam center according to a theoretical formula; A main beam center selection unit is used to select the second main beam center as the final main beam center N when the first main beam center deviates from the second main beam center by more than one quarter of the coherent accumulation point. fdc , otherwise the first main beam center is taken as the final main beam center N fdc .

7. The device for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation according to claim 6, characterized in that: The first main beam center N is calculated according to the following formula: 1 fdc : Among them, X 1 is the data of the same distance segment of all pulses selected in the time domain data X, Na is the number of coherent accumulation points, conj is the conjugate function, mean is the average function, and atan is the inverse tangent function.

8. The device for resisting co-frequency asynchronous interference based on time-frequency domain joint correlation according to claim 5, characterized in that: The power spectrum data of the specified long-distance segment refers to the power spectrum data of the 0.875Nr-Nr distance segment, and the middle segment data of the one-dimensional frequency data curve refers to the data located in the middle 1 / 2 segment after the one-dimensional frequency data curve is sorted in ascending order.

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