A method for suppressing rain and snow clutter

Abstract

The present invention discloses a method for suppressing rain and snow clutter, belonging to the technical field of radar clutter suppression. The method comprises the following steps: obtaining noise data of a radar system when the radar is not transmitting; performing pulse compression processing on the noise data; performing MTD processing on the noise data after pulse compression to estimate the noise of the system; obtaining radar echo data; performing pulse compression processing on the radar echo data; performing MTD processing on the echo data after pulse compression; performing constant false alarm detection on the echo data after MTD processing; estimating the rain and snow clutter background for each target detected by the constant false alarm; determining whether the target is in the rain and snow clutter background based on the noise of the system when the radar is not transmitting; if the target is in the rain and snow clutter background, increasing the constant false alarm gain and performing a secondary constant false alarm detection; and directly reporting the target if the target is not in the rain and snow clutter background, thereby achieving rain and snow clutter suppression.

Description

Technical Field

[0001] The invention belongs to the technical field of radar clutter suppression and relates to a rain and snow clutter suppression method based on background estimation. Background Art

[0002] Radar radiates electromagnetic waves through a transmitter and receives echo signals from the target to obtain information such as the target's range, direction, and speed. In the actual radar operating environment, the echo signal contains not only target information but also information such as clutter, which can interfere with target signal detection.

[0003] Rain and snow clutter refers to the echoes reflected back to the radar receiver by rain, hail, and snow surrounding a target. These echoes can generate false target information, leading to erroneous radar decisions. During radar operation, the presence of rain and snow clutter can increase the probability of false alarms or reduce the probability of target detection when the false alarm rate remains constant. This severely restricts radar performance in rainy and snowy weather conditions. Rain and snow clutter suppression technology can reduce the impact of rain and snow on target detection.

[0004] Existing rain and snow clutter suppression technologies include constant false alarm detection algorithms and wavelet transform suppression algorithms. Constant false alarm detection estimates the clutter mean based on the background of the echo signal, thereby achieving the purpose of clutter removal. However, this method requires high stability of the target environment. If the background fluctuates greatly, the suppression effect is not ideal. The wavelet transform method for suppressing rain and snow clutter is based on the different frequency ranges of the target and rain and snow clutter in the spectrum. It decomposes the signal based on the idea of ​​multi-resolution analysis. Typically, clutter is located in the low-frequency approximate part, and the target is located in the high-frequency detail part. The rain and snow clutter suppression function is achieved by suppressing the coefficients where the clutter is located. However, when the target speed is low, the target and clutter will alias in the spectrum, resulting in the coefficients after wavelet decomposition being unable to distinguish between the target and clutter. Therefore, it is necessary to develop a suppression method that can accurately and effectively address different rain and snow clutter backgrounds. Summary of the Invention

[0005] To address the problem of increased radar false alarm rates in rainy and snowy weather conditions, the present invention aims to provide a rain and snow clutter suppression method based on background estimation. Using the radar system's noise as a reference, a statistical method is employed to estimate the rain and snow clutter background for targets detected using constant false alarm (CFAR) detection. This method eliminates the effects of noise and target background fluctuations on the decision-making process, leaving targets with high signal-to-noise ratios unaffected and only targeting targets with relatively low signal-to-noise ratios unaffected. The method also achieves rain and snow clutter suppression. This method is simple to implement and requires minimal computation.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions.

[0007] The present invention discloses a rain and snow clutter suppression method, which comprises the following steps: obtaining noise data of a radar system when the radar is not transmitting; performing pulse compression processing on the noise data; performing moving target detection (MTD) processing on the noise data after pulse compression to estimate the noise of the system; obtaining radar echo data; performing pulse compression processing on the radar echo data; performing MTD processing on the echo data after pulse compression; performing constant false alarm detection on the echo data after MTD processing; estimating the rain and snow clutter background for each target detected by the constant false alarm; determining whether the target is in the rain and snow clutter background according to the noise of the system when the radar is not transmitting; performing secondary constant false alarm detection after increasing the constant false alarm gain if the target is in the rain and snow clutter background; and directly reporting the target if the target is not in the rain and snow clutter background, thereby achieving rain and snow clutter suppression.

[0008] The present invention discloses a method for suppressing rain and snow clutter, comprising the following steps:

[0009] S1. Obtaining noise data of the system when the radar is not transmitting by receiving through the radar receiver;

[0010] S2. performing pulse compression processing on the noise data to obtain noise data after pulse compression;

[0011] The formula for pulse compression processing is as follows:

[0012] n(i)=w(k)*h(-k) (1)

[0013] Where w(k) is the amplitude of the kth noise data; h(-k) is the corresponding pulse compression coefficient; * indicates the convolution operation; n(i) is the noise amplitude of the i-th distance unit after pulse compression processing;

[0014] S3. Perform MTD processing on the noise data after pulse compression to obtain a two-dimensional noise data matrix n(i, j) of range-velocity. Estimate the noise of the system when the radar is not transmitting and save it.

[0015] The method for estimating the system noise when the radar is not transmitting is to select M×N data after MTD and average them. The formula is as follows:

[0016]

[0017] Where N is the number of distance units selected, which is greater than or equal to 1; M is the number of speed units selected, which is greater than or equal to 1; n(i,j) is the noise amplitude at the i-th distance unit and the j-th speed unit; N0 is the obtained system noise;

[0018] S4, repeat steps S1 to S3 for a total of L times to obtain L frames of system noise values, average the obtained noise values ​​N0 to obtain the noise mean N average ;

[0019] According to formula (3), the noise value N0 is averaged:

[0020]

[0021] Where L is the total number of frames, greater than or equal to 1; N l is the noise estimation value of the lth frame;

[0022] S5. Receive a radar target echo signal through a radar receiver to obtain radar echo data, where the collected radar echo data includes target speed, distance, amplitude, and range gate echo signal;

[0023] S6. performing pulse compression processing on the radar echo data to obtain pulse compressed echo data;

[0024] The formula for pulse compression processing is as follows:

[0025] s(i)=m(k)*h(-k) (4)

[0026] Where m(k) is the amplitude of the kth data of the signal; h(-k) is the corresponding pulse compression coefficient; * indicates the convolution operation; s(i) is the signal amplitude of the i-th distance unit after pulse compression processing;

[0027] S7, performing MTD processing on the echo data after pulse compression to obtain a two-dimensional range-velocity echo data matrix s(i, j);

[0028] S8. Perform constant false alarm detection on the echo data after MTD processing to obtain the target's range unit x and velocity unit y;

[0029] S9, performing rain and snow clutter background estimation on each target detected by CFAR to obtain background estimation values ​​S0, S1, S2, and S3, which are used for judgment in S10;

[0030] The method for estimating the rain and snow clutter background is as follows: taking the target (x, y) as the origin, the rain and snow clutter background of the four quadrants is estimated respectively. That is, M×N data are selected from the MTD data and averaged. The formulas for the four quadrants are as follows:

[0031]

[0032]

[0033]

[0034]

[0035] Wherein, N is the number of distance units selected, which is greater than or equal to 1; M is the number of speed units selected, which is greater than or equal to 1; d is the number of distance protection units, which is greater than or equal to 1; q is the number of speed protection units, which is greater than or equal to 1;

[0036] S10, judging whether the radar is under rain or snow clutter background based on the noise of the system when the radar is not transmitting and the judgment criteria;

[0037] The judgment criterion is as follows:

[0038] Y i =S i ≥A*N average ? 1:0 (9)

[0039] B=Y0+Y1+Y2+Y3 (10)

[0040] If B is greater than or equal to 2, the target is judged to be in the rain and snow clutter background, otherwise the target is judged not to be in the rain and snow clutter background; where A is a coefficient, which is greater than or equal to 1;

[0041] S11. When the target is in the rain and snow clutter background, the constant false alarm gain is increased and a secondary constant false alarm detection is performed, thereby achieving rain and snow clutter suppression; when the target is not in the rain and snow clutter background, the target is directly reported, thereby achieving rain and snow clutter suppression.

[0042] Beneficial effects:

[0043] 1. The present invention discloses a method for suppressing rain and snow clutter based on background estimation. The method comprises: obtaining system noise data when the radar is not transmitting by receiving the system noise data through a radar receiver, then performing pulse compression and MTD processing to obtain a two-dimensional range-velocity noise data matrix, and estimating the system noise by averaging. The radar receiver also receives radar target echo signals to obtain radar echo data, which are then subjected to pulse compression and MTD processing to obtain a two-dimensional range-velocity echo data matrix. The target background is estimated by dividing the quadrants. Compared with the method for suppressing rain and snow clutter using wavelet transform, the method for obtaining system noise and target background is simpler and easier to implement. By comparing the relative sizes of the system noise and target background, it is determined whether the target is within the rain and snow clutter background, and the computational complexity is negligible.

[0044] 2. In view of the fact that the suppression effect of existing rain and snow clutter suppression methods is affected by the fluctuation of the target background, the present invention discloses a rain and snow clutter suppression method based on background estimation. By performing pulse compression and MTD processing on the radar received data, a two-dimensional data matrix of range and velocity is obtained. M×N data are selected from the noise data and averaged to obtain the noise value N0. The operation is repeated for L frames of data to obtain L noise values, and the average processing is performed to obtain the system noise mean N average; Select M×N data of the target data and average them to obtain the background estimation values ​​of the four quadrants S0, S1, S2, and S3; obtain the system noise and target background by using statistical methods to eliminate the influence of noise and target background fluctuations on the judgment.

[0045] 3. The background estimation-based rain and snow clutter suppression method disclosed in the present invention uses a decision criterion to determine whether the target is in a rain and snow environment. If the target is in a rain and snow clutter background, the constant false alarm gain is increased and a secondary constant false alarm detection is performed. This method has no effect on targets with high signal-to-noise ratios and only loses targets with relatively low signal-to-noise ratios, while achieving rain and snow clutter suppression. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a flow chart of an implementation method of rain and snow clutter suppression according to the present invention;

[0047] Figure 2 This is a three-dimensional range-Doppler graph of some rain and snow clutter data. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the embodiments described are part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0049] Example 1

[0050] This embodiment describes the specific implementation of the method of the present invention. Figure 1 FIG. 1 is an implementation flow chart of a method for suppressing rain and snow clutter according to the present invention.

[0051] The data of the embodiment is obtained from an outdoor field experiment in which radar equipment is used to collect rain and snow clutter.

[0052] like Figure 1 As shown, the rain and snow clutter suppression method disclosed in this embodiment is specifically implemented in the following steps:

[0053] S1. When the radar is not transmitting, obtain the noise data of the radar in a coherent accumulation frame. One coherent processing time contains 64 repetition cycles.

[0054] S2. performing pulse compression processing on the noise data to obtain noise data after pulse compression;

[0055] The formula for pulse compression processing is as follows:

[0056] n(i)=w(k)*h(-k) (11)

[0057] Where w(k) is the amplitude of the kth noise data; h(-k) is the corresponding pulse compression coefficient; * indicates the convolution operation; n(i) is the noise amplitude of the i-th distance unit after pulse compression processing;

[0058] S3. Perform MTD processing on the noise data after pulse compression to obtain a two-dimensional noise data matrix n(i, j) of range-velocity. Estimate the noise of the system when the radar is not transmitting and save it.

[0059] The method for estimating the system noise when the radar is not transmitting is to select M×N data after MTD and average them. The formula is as follows:

[0060]

[0061] Select N=32, M=8;

[0062] S4. Repeat steps S1 to S3 for a total of L times to obtain L frames of noise values, and average the obtained noise values ​​N0; the formula is as follows:

[0063]

[0064] Select L = 128;

[0065] S5. The radar starts transmitting, and the radar receiver receives the radar target echo signal and obtains radar echo data. The collected radar echo data includes the target speed, distance, amplitude and range gate echo signal;

[0066] S6. performing pulse compression processing on the radar echo data to obtain pulse compressed echo data;

[0067] The formula for pulse compression processing is as follows:

[0068] s(i)=m(k)*h(-k) (14)

[0069] Where m(k) is the amplitude of the kth data of the signal; h(-k) is the corresponding pulse compression coefficient; * represents the convolution operation; s(i) is the signal amplitude of the i-th distance unit after pulse compression processing;

[0070] S7, performing MTD processing on the echo data after pulse compression to obtain a two-dimensional range-velocity echo data matrix s(i, j);

[0071] S8. Perform constant false alarm detection on the two-dimensional echo data s(i, j) after MTD processing to obtain the target's range unit x and velocity unit y;

[0072] S9, performing rain and snow clutter background estimation on each target detected by CFAR to obtain background estimation values ​​S0, S1, S2, and S3, which are used for judgment in S10;

[0073] The method for estimating the rain and snow clutter background is as follows: taking the target (x, y) as the origin, the rain and snow clutter background of the four quadrants is estimated respectively. That is, M×N data are selected from the MTD data and averaged. The formulas for the four quadrants are as follows:

[0074]

[0075]

[0076]

[0077]

[0078] Select N=16, M=2, d=2, q=2;

[0079] S10. Determine whether the system is under rain and snow clutter based on the system noise. The judgment criterion is as follows:

[0080] Y i =S i ≥A*N average ? 1:0 (19)

[0081] B=Y0+Y1+Y2+Y3 (20)

[0082] Select A=2;

[0083] S11. Calculate Y i The number of 1s is different according to the value of B, specifically:

[0084] S111. If B is greater than or equal to 2, the target is located in the rain and snow clutter background, and the constant false alarm gain is increased to perform a secondary constant false alarm detection.

[0085] S112: If B is less than 2, the target is not in the rain or snow clutter background and the target is reported directly;

[0086] The above specific description further illustrates the purpose, technical solutions and beneficial effects of the invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for suppressing rain and snow clutter, characterized by: The following steps are included: S1. Obtaining noise data of the system when the radar is not transmitting by receiving through the radar receiver; S2. performing pulse compression processing on the noise data to obtain noise data after pulse compression; S3. Perform moving target detection (MTD) processing on the noise data after pulse compression to obtain a two-dimensional noise data matrix n(i, j) of range-velocity. Estimate the noise of the system when the radar is not transmitting and save it. S4, repeat steps S1 to S3 for a total of L times to obtain L frames of system noise values, average the obtained noise values ​​N0 to obtain the noise mean N average ; S5. Receive a radar target echo signal through a radar receiver to obtain radar echo data, where the collected radar echo data includes target speed, distance, amplitude, and range gate echo signal; S6. performing pulse compression processing on the radar echo data to obtain pulse compressed echo data; S7, performing MTD processing on the echo data after pulse compression to obtain a two-dimensional range-velocity echo data matrix s(i, j); S8. Perform constant false alarm detection on the echo data after MTD processing to obtain the target's range unit x and velocity unit y; S9, performing rain and snow clutter background estimation on each target detected by CFAR to obtain background estimation values ​​S0, S1, S2, and S3, which are used for judgment in S10; S10, judging whether the radar is under rain or snow clutter background based on the noise of the system when the radar is not transmitting and the judgment criteria; S11. When the target is in the rain and snow clutter background, the constant false alarm gain is increased and a secondary constant false alarm detection is performed, thereby achieving rain and snow clutter suppression; when the target is not in the rain and snow clutter background, the target is directly reported, thereby achieving rain and snow clutter suppression.

2. The method for suppressing rain and snow clutter according to claim 1, wherein: In step S2, The formula for pulse compression processing is as follows: n(i)=w(k)*h(-k) (1) Where w(k) is the amplitude of the kth noise data; h(-k) is the corresponding pulse compression coefficient; * indicates the convolution operation; and n(i) is the noise amplitude of the i-th distance unit after pulse compression processing.

3. The method for suppressing rain and snow clutter according to claim 2, wherein: In step S3, The method for estimating the system noise when the radar is not transmitting is to select M×N data after MTD and average them. The formula is as follows: Where N is the number of distance units selected, which is greater than or equal to 1; M is the number of velocity units selected, which is greater than or equal to 1; n(i, j) is the noise amplitude at the i-th distance unit and the j-th velocity unit; N0 is the obtained system noise.

4. The method for suppressing rain and snow clutter according to claim 3, wherein: In step S4, According to formula (3), the noise value N0 is averaged: Where L is the total number of frames, greater than or equal to 1; N l is the noise estimation value of the lth frame.

5. The method for suppressing rain and snow clutter according to claim 4, characterized in that: In step S6, The formula for pulse compression processing is as follows: s(i)=m(k)*h(-k) (4) Where m(k) is the amplitude of the kth data of the signal; h(-k) is the corresponding pulse compression coefficient; * represents the convolution operation; and s(i) is the signal amplitude of the i-th distance unit after pulse compression processing.

6. The method for suppressing rain and snow clutter according to claim 5, characterized in that: In step S9, The method for estimating the rain and snow clutter background is as follows: take the target (x, y) as the origin and estimate the rain and snow clutter background of the four quadrants respectively. That is, select M×N data after MTD and average them. The formulas for the four quadrants are as follows: Among them, N is the number of distance units selected, which is greater than or equal to 1; M is the number of speed units selected, which is greater than or equal to 1; d is the number of distance protection units, which is greater than or equal to 1; q is the number of speed protection units, which is greater than or equal to 1.

7. The method for suppressing rain and snow clutter according to claim 6, characterized in that: The implementation method of step S10 is: The judgment criterion is as follows: Y i =S i ≥A*N average ?1:0 (9) B=Y0+Y1+Y2+Y3 (10) If B is greater than or equal to 2, the target is judged to be in the rain and snow clutter background, otherwise the target is judged not to be in the rain and snow clutter background; where A is a coefficient, which is greater than or equal to 1.

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