An improved CFAR detection method based on inter-circle abnormal unit identification

Abstract

The present invention relates to an improved CFAR detection method based on inter-circle abnormal unit identification, comprising the following steps: 1) radar signal processing and detection; 2) abnormal unit identification; 3) abnormal unit elimination and target output. Compared with the prior art, the present invention has the following significant advantages: it can effectively suppress the false alarm problem caused by sea spikes, and at the same time solve the problem of weak targets on the sea surface being shielded by sea spikes, providing convenience for the detection of weak targets on the sea surface. The present invention only optimizes the signal processing process, does not require additional hardware, and has high flexibility. The CFAR detection method based on inter-circle abnormal unit identification of the present invention is suitable for shore-based sea warning radars.

Description

Technical Field

[0001] The invention relates to a radar sea target detection method, in particular to an improved CFAR detection method based on inter-circle abnormal unit recognition. Background Art

[0002] Radar detection of sea targets is easily affected by complex sea conditions. Under medium and high sea conditions, a large amount of debris generated by wave breaking forms sea spikes, which are highly random and stronger. The characteristics of sea spike targets are very similar to real targets. It is difficult for traditional detection methods to directly distinguish targets from sea spikes. Due to the strong intensity of sea spikes, they also cause a shielding effect on weak targets on the sea surface, seriously interfering with radar detection of sea targets. Therefore, achieving the suppression of sea spikes is of great significance for radar detection of sea surface targets.

[0003] Existing studies have shown that sea clutter is decorrelated within tens of milliseconds, and the duration of a sea spike is almost equal to the duration of a large amount of debris generated after the wave breaks, which is about hundreds of milliseconds to a few seconds, which is completely different from the duration of the real target. Most existing methods use the non-coherent detection results between multiple frames of radar to perform binary accumulation to eliminate sea spikes. Since the amplitude of sea spikes is very strong, it causes a shielding effect on weak targets, but the existing methods do not backtrack the detection process, resulting in weak targets being submerged in sea spikes. In addition, abnormal clutter units with sudden power increase may also appear in sea detection. These two types of interference are collectively referred to as abnormal units. The present invention proposes an improved CFAR detection method based on inter-circle abnormal unit identification, which uses the correlation of radar multi-circle detection targets to identify abnormal units in the detection unit, and then performs CFAR detection after eliminating the abnormal units, thereby effectively improving the detection performance of small targets on the sea surface.

[0004] According to the existing data, the improved CFAR method based on eliminating abnormal units between circles proposed in the present invention has not been found yet. Summary of the invention

[0005] The present invention provides a CFAR detection method based on inter-circle abnormal unit identification, which provides a new way to suppress sea spikes and improve the detection performance of weak targets on the sea surface, thereby improving the radar's weak target detection performance on the sea. The CFAR detection method based on inter-circle abnormal unit identification of the present invention is suitable for shore-based sea warning radars.

[0006] In order to achieve the purpose of the invention, the technical solution adopted is as follows:

[0007] An improved CFAR detection method based on inter-circle abnormal unit identification includes the following steps:

[0008] 1) Radar signal processing and detection: After acquiring the sampling signal of each wave position, complete the signal processing processes such as pulse compression, MTI, non-coherent accumulation and CFAR detection, and accumulate the detection results of M consecutive circles to identify abnormal units;

[0009] 2) Abnormal unit identification: The present invention adopts a multi-circle accumulation method to identify abnormal units: first, the MN criterion and the multi-circle correlation threshold are initialized according to the radar working mode. When the current circle number is Q, the abnormal unit is identified by using the correlation between the detection results of Q-M+1 circle to Q circle. After multi-frame accumulation, the MN criterion is used to screen out the abnormal detection unit;

[0010] 3) Abnormal unit elimination and target output: The Q-M+1 circle detection unit is judged. If it is judged as an abnormal unit, the detection result is deleted and the CFAR detection is performed again on the detection unit near the abnormal unit. If it is judged as a normal detection unit, the detection unit is output.

[0011] Furthermore, the radar signal processing and detection in step 1) includes the following steps:

[0012] 11) Obtaining echo time domain sampling signal: Radar signal processing and detection are performed according to wave position. Assuming that there are L wave positions in each circle when the shore-based sea warning radar scans, m pulses are sent at each wave position, and the time domain sampling matrix of the radar pulse echo signal is obtained. The echo of each wave position can be expressed as:

[0013]

[0014] Where n is the number of gate sampling points, m is the number of continuously emitted pulses, and r mn Represents the nth echo sampling value of the mth pulse.

[0015] 12) Pulse compression processing:

[0016] Generate matching signals of linear frequency modulation radar waves according to radar parameters, perform pulse compression processing on each row, and obtain pulse compression matrix signals:

[0017]

[0018] It represents the nth distance gate pulse pressure result of the mth pulse;

[0019] 13)MTI treatment:

[0020] Perform MTI on the pulse pressure results using 3-pulse cancellation:

[0021]

[0022] in, is the signal after MTI, is the echo signal after pulse compression, and the signal after MTI is obtained:

[0023]

[0024] 14) Non-coherent accumulation: Calculate the absolute value of the data after MTI and accumulate it in the pulse dimension to obtain the signal after non-coherent accumulation:

[0025]

[0026] 15) CA-CFAR detection: The unit average algorithm is used to calculate the background. The CA-CFAR detection results are:

[0027] y=R NAC -B CA-CFAR-BACK ≥η

[0028] Among them B CA-CFAR-BACK is the noise floor calculated by CA-CFAR, and η1 is the detection threshold.

[0029] Furthermore, the abnormal unit identification in step 2) includes the following steps:

[0030] 21) Parameter initialization

[0031] According to the working mode of the shore-based sea radar and the scanning time of each circle, determine the M and N values ​​of the window size I0, J0 in distance and azimuth, and the MN criterion of inter-circle accumulation; for example, when the radar scanning time per circle is 6s and the distance gate is 30m, M=5, N=3, I0=2, and J0=20 can be set.

[0032] 22) Multi-circle point trace association

[0033] When the circle number is Q and M detection results have been accumulated, all detection units in the Q-M+1 circle are traversed. Assuming that there are K detection units in the Q-M+1 circle, the kth detection unit is taken as the search center, and the initial detection window is I0 / 2 wave positions on the left and right, and J0 / 2 range gates above and below. If the target is found in the next detection window of the search center, the corresponding detection number D k ++, the search center is replaced with the searched point trace, the detection window is reset to the left and right I0 / 2 wave position, the distance above and below J0 / 2 range gates, and the next circle search is continued until M circles of detection are completed; if the search center does not search for the target in the next circle of detection window, and the target has not been searched for 3 consecutive circles, the detection unit is directly determined to be an abnormal unit, and the search for the remaining circles is no longer continued, otherwise the detection window is set to the left and right I0 wave position, the distance above and below J0 range gates, and the next circle search is continued until M circles of detection are completed.

[0034] Furthermore, the abnormal unit elimination and target output in step 3) include the following steps:

[0035] 31) Abnormal unit determination

[0036] Traverse all detection units in Q - M + 1 circles, and determine whether a unit is an abnormal unit according to the number of times each detection unit is associated. If the number of associations D of the kth detection unit k < N, then determine that this unit is an abnormal unit; otherwise, determine that this unit is a normal target;

[0037] 32) Detection result output

[0038] If the current detection unit is determined to be an abnormal unit, perform noise floor filling on m0 distance units above and below the current detection distance unit, and at the same time re - perform CA - CFAR detection on n0 units above and below this detection unit, and store the detection results in the output track table; if the current detection unit is determined to be a normal target, directly store the track in the output track table. After traversing K detection units, output the track results of the current circle.

[0039] Compared with the prior art, the significant advantages of the present invention are as follows: It can effectively suppress the false alarm problem caused by sea spikes, and at the same time solve the problem that weak targets on the sea surface are obscured by sea spikes, providing convenience for the detection of weak targets on the sea surface. The present invention only optimizes the signal processing flow and does not require additional hardware, having a high degree of flexibility. Description of the drawings

[0040] 1. Figure 1 Is the flow chart of the improved CFAR detection method based on inter - circle abnormal unit recognition of the present invention;

[0041] 2. Figure 2 Is the flow chart of radar signal processing and detection of the present invention;

[0042] 3. Figure 3 Is the flow chart of abnormal unit recognition of the present invention;

[0043] 4. Figure 4 Is the flow chart of abnormal unit elimination and target output of the present invention. Detailed implementation manners

[0044] The following will describe in detail the detailed implementation manners of the present invention with reference to the drawings.

[0045] Figure 1 Is the flow chart of the improved CFAR detection method based on inter - circle abnormal unit recognition of the present invention; Figure 2 Is the flow chart of radar signal processing and detection of the present invention; Figure 3 Is the flow chart of abnormal unit recognition of the present invention; Figure 4 Is the flow chart of abnormal unit elimination and target output of the present invention.

[0046] The improved CFAR detection method based on inter-circle abnormal unit identification of the present invention comprises the following steps:

[0047] 1) Radar signal processing and detection: When shore-based radar detects the sea, it uses a circle scanning method. Each circle consists of several wave positions, and each wave position sends several pulses. After obtaining the sampling signal of each wave position, the signal processing process such as pulse compression, MTI, non-coherent accumulation and CFAR detection is completed. After accumulating the detection results of M consecutive circles, abnormal unit identification is performed;

[0048] 2) Abnormal unit identification: When the shore-based radar detects the sea, it is affected by the sea peak, and the sea peak shielding effect will also interfere with the detection of small targets. The present invention uses a multi-circle accumulation method to identify abnormal units such as sea peaks: first, the MN criterion and the multi-circle correlation threshold are initialized according to the radar working mode. When the current circle number is Q, the abnormal unit is identified by using the correlation between the detection results of Q-M+1 circle to Q circle. After multi-frame accumulation, the MN criterion is used to screen out the abnormal detection unit;

[0049] 3) Abnormal unit elimination and target output: The Q-M+1 circle detection unit is judged. If it is judged as an abnormal unit, considering that the abnormal unit may have a shielding effect on the faint target, it is necessary to delete the detection result and re-perform CFAR detection on the detection unit near the abnormal unit. If it is judged as a normal detection unit, the detection unit is output.

[0050] Furthermore, the radar signal processing and detection in step 1) includes the following steps:

[0051] 11) Obtaining echo time domain sampling signal: Radar signal processing and detection are performed according to wave position. Assuming that there are L wave positions in each circle when the shore-based sea warning radar scans, m pulses are sent at each wave position, and the time domain sampling matrix of the radar pulse echo signal is obtained. The echo of each wave position can be expressed as:

[0052]

[0053] Where n is the number of gate sampling points, m is the number of continuously emitted pulses, and r mn Represents the nth echo sampling value of the mth pulse.

[0054] 12) Pulse compression processing:

[0055] Generate matching signals of linear frequency modulation radar waves according to radar parameters, perform pulse compression processing on each row, and obtain pulse compression matrix signals:

[0056]

[0057] It represents the nth distance gate pulse pressure result of the mth pulse;

[0058] 13)MTI treatment:

[0059] Perform MTI on the pulse pressure results using 3-pulse cancellation:

[0060]

[0061] in, is the signal after MTI, is the echo signal after pulse compression, and the signal after MTI is obtained:

[0062]

[0063] 14) Non-coherent accumulation: Calculate the absolute value of the data after MTI and accumulate it in the pulse dimension to obtain the signal after non-coherent accumulation:

[0064]

[0065] 15) CA-CFAR detection: The unit average algorithm is used to calculate the background. The CA-CFAR detection results are:

[0066] y=R NAC -B CA-CFAR-BACK ≥η

[0067] Among them B CA-CFAR-BACK is the noise floor calculated by CA-CFAR, and η1 is the detection threshold.

[0068] Furthermore, the abnormal unit identification in step 2) includes the following steps:

[0069] 21) Parameter initialization

[0070] According to the working mode of the shore-based sea radar and the scanning time of each circle, determine the M and N values ​​of the window size I0, J0 in distance and azimuth, and the MN criterion of inter-circle accumulation; for example, when the radar scanning time per circle is 6s and the distance gate is 30m, M=5, N=3, I0=2, and J0=20 can be set.

[0071] 22) Multi-circle point trace association

[0072] When the circle number is Q and M detection results have been accumulated, all detection units in the Q-M+1 circle are traversed. Assuming that there are K detection units in the Q-M+1 circle, the kth detection unit is taken as the search center, and the initial detection window is I0 / 2 wave positions on the left and right, and J0 / 2 range gates above and below. If the target is found in the next detection window of the search center, the corresponding detection number D k++, replace the search center with the detected traces, reset the detection window to the left and right I0 / 2 wave positions, and the distance to the upper and lower J0 / 2 range gates. Continue the next search loop until M loops of detection are completed. If the target is not detected at the search center in the next detection window and the target has not been detected for 3 consecutive loops, directly determine that the detection unit is an abnormal unit and do not continue the search for the remaining loops. Otherwise, set the detection window to the left and right I0 wave positions and the distance to the upper and lower J0 range gates, and continue the next search loop until M loops of detection are completed.

[0073] Further, the abnormal unit elimination and target output in step 3) include the following steps:

[0074] 31) Abnormal unit determination

[0075] Traverse all detection units in Q - M + 1 loops. Determine whether a detection unit is an abnormal unit according to the number of times it is associated. If the number of times the k-th detection unit is associated D k < N, then determine that this unit is an abnormal unit; otherwise, determine that this unit is a normal target.

[0076] 32) Detection result output

[0077] If the current detection unit is determined to be an abnormal unit, fill the upper and lower m0 range units of the current detection range unit with the noise floor. At the same time, re - perform CA - CFAR detection on the upper and lower n0 units of this detection unit and store the detection results in the output trace table. If the current detection unit is determined to be a normal target, directly store the trace in the output trace table. After traversing K detection units, output the trace results of the current loop.

[0078] So far, the technical solution of the present invention has been described in combination with the preferred embodiments. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An improved CFAR detection method based on inter-circle abnormal unit identification, characterized in that: The steps include: 1) Radar signal processing and detection: After acquiring the sampling signal of each wave position, complete the pulse compression, MTI, non-coherent accumulation and CFAR detection signal processing process, and accumulate the detection results of M consecutive circles to identify abnormal units; 2) Abnormal unit identification: The abnormal unit is identified by multi-circle accumulation: First, the MN criterion and multi-circle correlation threshold are initialized according to the radar working mode. When the current circle number is Q, the abnormal unit is identified by using the correlation between the detection results of Q-M+1 circle to Q circle. After multi-frame accumulation, the abnormal detection unit is screened out by using the MN criterion; 3) Abnormal unit elimination and target output: The Q-M+1 circle detection unit is judged. If it is judged as an abnormal unit, the detection result is deleted and the detection unit near the abnormal unit is re-CFAR detected. If it is judged as a normal detection unit, the detection unit is output; The radar signal processing and detection in step 1) includes the following steps: 11) Obtaining echo time domain sampling signal: Radar signal processing and detection are performed according to wave position. Assuming that there are L wave positions in each circle when the shore-based sea warning radar scans, m pulses are sent at each wave position, and the time domain sampling matrix of the radar pulse echo signal is obtained. The echo of each wave position is expressed as: Where n is the number of gate sampling points, m is the number of continuously emitted pulses, and r mn Represents the nth echo sampling value of the mth pulse; 12) Pulse compression processing: Generate matching signals of linear frequency modulation radar waves according to radar parameters, perform pulse compression processing on each row, and obtain pulse compression matrix signals: It represents the nth distance gate pulse pressure result of the mth pulse; 13)MTI treatment: Perform MTI on the pulse pressure results using 3-pulse cancellation: in, is the signal after MTI, is the echo signal after pulse compression, and the signal after MTI is obtained: 14) Non-coherent accumulation: Calculate the absolute value of the data after MTI and accumulate it in the pulse dimension to obtain the signal after non-coherent accumulation: 15) CA-CFAR detection: The unit average algorithm is used to calculate the background. The CA-CFAR detection results are: y=R NAC -B CA-CFAR-BACK ≥η Among them B CA-CFAR-BACK is the noise floor calculated by CA-CFAR, η is the detection threshold; The abnormal unit identification in step 2) includes the following steps: 21) Parameter initialization According to the working mode of the shore-based sea radar and the scanning time of each circle, determine the M and N values ​​of the window size I0, J0 in distance and azimuth, and the MN criterion accumulated between circles; 22) Multi-circle point trace association When the circle number is Q and M detection results have been accumulated, all detection units in the Q-M+1 circle are traversed. Assuming that there are K detection units in the Q-M+1 circle, the kth detection unit is taken as the search center, and the initial detection window is I0 / 2 wave positions on the left and right, and J0 / 2 range gates above and below. If the target is found in the next detection window of the search center, the corresponding detection number D k ++, the search center is replaced with the searched point trace, the detection window is reset to the left and right I0 / 2 wave position, the distance is J0 / 2 range gates above and below, and the next circle search is continued until M circles of detection are completed; if the search center does not search for the target in the next circle of detection window, and the target has not been searched for 3 consecutive circles, the detection unit is directly determined to be an abnormal unit, and the search for the remaining circles is no longer continued, otherwise the detection window is set to the left and right I0 wave position, the distance is J0 range gates above and below, and the next circle search is continued until M circles of detection are completed; The abnormal unit elimination and target output in step 3) include the following steps: 31) Abnormal unit determination Traverse all the detection units for Q - M + 1 cycles, and determine whether a unit is an abnormal unit according to the number of times each detection unit is associated. If the number of associations D of the kth detection unit k <N, then determine that this unit is an abnormal unit; otherwise, determine that this unit is a normal target. 32) Test result output The current detection unit is determined to be an abnormal unit, and the m0 distance units above and below the current detection distance unit are filled with noise. At the same time, CA-CFAR detection is re-performed on the n0 units above and below the detection unit, and the detection results are stored in the output point trace table; if the current detection unit is determined to be a normal target, the point trace is directly stored in the output point trace table. After completing the traversal of K detection units, the current circle point trace result is output.

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