Rotary phased array radar azimuth calibration method and device based on ground object echo correlation

Abstract

The invention relates to a rotating phased array radar azimuth calibration method and device based on ground object echo correlation, and the method comprises the steps: processing the data of a current circle obtained through the scanning of a rotating phased array radar rotating a circle through employing a fuzzy logic algorithm, and extracting ground object echo sample points of each azimuth angle region; and for each azimuth angle region based on the ground object echo sample points, calculating the correlation between the azimuth angle region and a plurality of adjacent azimuth angle regions in the previous circle of data, and calibrating the azimuth angle of the current circle of azimuth angle region by using the azimuth angle corresponding to the azimuth angle region in the previous circle of data with the maximum correlation. By adopting the method, the azimuth calibration accuracy of the rotary phased array radar can be effectively improved.

Description

Technical Field

[0001] The present application relates to the technical field of calibration of meteorological observation radars, and in particular to a method and device for azimuth calibration of a rotating phased array radar based on ground object echo correlation. Background Art

[0002] As a high-precision remote sensing device, meteorological radar has a wide range of application value in precipitation dynamic analysis, cloud microphysical characteristics monitoring, and biological migration trajectory tracking. As weather radar technology has gradually developed from analog technology to digital technology, Doppler technology, polarization technology and other information processing technology stages. At present, the introduction of rotating phased array technology has significantly improved the spatial and temporal resolution of meteorological observations. Rotating phased array radar is a low-cost and effective radar architecture that is widely used in high-timeliness and high-precision meteorological observations. It generally performs mechanical rotation scanning in the azimuth dimension and electronic scanning in the elevation direction.

[0003] However, the rotating phased array radar system suffers from azimuth pointing deviation during the scanning process, which poses a huge challenge to data accuracy. Summary of the invention

[0004] Based on this, it is necessary to provide a rotating phased array radar azimuth calibration method and device based on ground object echo correlation that can achieve high-precision azimuth calibration in response to the above technical problems.

[0005] A method for azimuth calibration of a rotating phased array radar based on ground object echo correlation, the method comprising:

[0006] Acquire the PPI base data obtained by the current scan, wherein the PPI base data of the current scan is obtained by scanning the rotating phased array radar in one circle, and is referred to as the current circle data;

[0007] The current round data is processed by using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle regions;

[0008] Based on the ground object echo sample points, for each azimuth area, the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data is calculated;

[0009] The azimuth angle of the azimuth angle area in the previous round data with the maximum correlation is used to calibrate the azimuth angle of the current round azimuth angle area.

[0010] In one embodiment, when calculating the correlation between two azimuth angle regions between two adjacent scanning passes, the calculation is performed based on the Pearson correlation coefficient.

[0011] In one embodiment, when calculating the correlation, the calculation is performed based on the echo reflectivity of all ground object echo sample points in two azimuth regions.

[0012] In one embodiment, the following formula is used to calculate the correlation:

[0013]

[0014] In the above formula, ρ(Z n-1 ,Z n ) represents the correlation between the two azimuth areas of the nth round, i.e. the current round, and the n-1th round, i.e. the previous round, Z n (i, r) represents the echo reflectivity of the ground object echo sample point at a distance of r in the i-th azimuth area of ​​the n-th circle, Z n represents the sampling point sequence of ground object echo in a certain azimuth area, R represents the maximum value of r, cov(Z n-1 ,Z n ) represents Z n-1 and Z n The covariance of , the superscript * indicates conjugate, σ indicates variance, and μ indicates mean.

[0015] In one embodiment, when calculating the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data, a correction range is set with the current azimuth area as the center, and the correlation between each azimuth area in the previous round of data within the correction range and the current azimuth area is calculated.

[0016] In one embodiment, the correction range is centered on the current azimuth area, three adjacent azimuth areas in the counterclockwise direction and three adjacent azimuth areas in the clockwise direction, wherein the correction range includes calibration values ​​corresponding to each azimuth area.

[0017] In one embodiment, if the calculated maximum correlation is less than a preset threshold:

[0018] Calculate the weight of the maximum correlation;

[0019] Performing a smoothing convolution operation according to the weight and the calibration value corresponding to the maximum correlation to obtain an updated calibration value;

[0020] In the previous round data, the corresponding azimuth angle is extracted according to the updated calibration value based on the correction range, and the azimuth angle of the current round azimuth angle area is calibrated using the azimuth angle.

[0021] In one embodiment, the weight of the maximum correlation is calculated using the following formula:

[0022]

[0023] in,

[0024] In the above formula, represents the maximum correlation, W n,i represents the weight, and T represents the preset correlation threshold.

[0025] In one embodiment, a smoothing convolution operation is performed according to the weight and the calibration value corresponding to the maximum correlation, and the process is expressed as follows:

[0026]

[0027] In the above formula, L n,i represents the calibration value corresponding to the maximum correlation, represents the updated calibration value, K represents the convolution kernel, represents the convolution operation, and round[·] represents the rounding operation.

[0028] The present application also provides a rotating phased array radar azimuth calibration device based on ground object echo correlation, the device comprising:

[0029] A real-time base data acquisition module is used to acquire the PPI base data obtained by the current scan. The PPI base data of the current scan is obtained by scanning the rotating phased array radar in one circle, and is called the current circle data;

[0030] A ground object echo sample point extraction module is used to process the current round data using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle areas;

[0031] A correlation calculation module based on ground object echoes, used to calculate the correlation between each azimuth area and multiple adjacent azimuth areas in the previous round of data based on ground object echo sample points for each azimuth area;

[0032] The azimuth calibration module is used to calibrate the azimuth angle of the current round azimuth angle area using the azimuth angle corresponding to the azimuth angle area in the previous round data with the maximum correlation.

[0033] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0034] Acquire the PPI base data obtained by the current scan, wherein the PPI base data of the current scan is obtained by scanning the rotating phased array radar by one circle, and is referred to as the current circle data;

[0035] The current round data is processed by using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle regions;

[0036] Based on the ground object echo sample points, for each azimuth area, the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data is calculated;

[0037] The azimuth angle of the azimuth angle area in the previous round data with the maximum correlation is used to calibrate the azimuth angle of the current round azimuth angle area.

[0038] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0039] Acquire the PPI base data obtained by the current scan, wherein the PPI base data of the current scan is obtained by scanning the rotating phased array radar by one circle, and is referred to as the current circle data;

[0040] The current round data is processed by using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle regions;

[0041] Based on the ground object echo sample points, for each azimuth area, the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data is calculated;

[0042] The azimuth angle of the azimuth angle area in the previous round data with the maximum correlation is used to calibrate the azimuth angle of the current round azimuth angle area.

[0043] The above-mentioned rotating phased array radar azimuth calibration method and device based on ground object echo correlation processes the current round data obtained by scanning the rotating phased array radar by rotating one circle by using fuzzy logic algorithm, extracts ground object echo sample points in each azimuth area, and calculates the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round data for each azimuth area based on the ground object echo sample points, and calibrates the azimuth angle of the current round azimuth area using the azimuth angle corresponding to the azimuth area in the previous round data with the maximum correlation. This method can effectively improve the accuracy of the rotating phased array radar azimuth calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of a flow chart of a rotating phased array radar azimuth calibration method based on ground object echo correlation in one embodiment;

[0045] Figure 2 is a distribution diagram of ground object echoes in two consecutive scans in one embodiment;

[0046] Figure 3This is the distribution diagram of ground object echo after calibration based on radar reading method in an experiment;

[0047] Figure 4 This is the distribution diagram of ground object echo after calibration based on this method in an experiment;

[0048] Figure 5 It is a structural block diagram of a rotating phased array radar azimuth calibration device based on ground object echo correlation in one embodiment;

[0049] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application 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 application and are not used to limit the present application.

[0051] The sources of azimuth pointing deviation of rotating phased array radar system include mechanical transmission system error, environmental factors, electronic sensor error and beam tailing effect.

[0052] Mechanical transmission system error means that the antenna of the rotating phased array radar usually achieves azimuth scanning through mechanical rotation, but due to design defects of the mechanical transmission device (such as gear recoil and bearing wear), there will be a deviation between the antenna rotation angle and the preset azimuth angle. Due to the inaccuracy of the transmission device, the azimuth deviation can be as high as 0.2°, and even a larger range of deviations will occur under high wind speed conditions. This mechanical deviation becomes more and more significant in long-term use, especially factors such as gear wear, lag of the drive system, and decreased accuracy of the angle sensor, which will cause the azimuth angle to gradually deviate from the predetermined trajectory.

[0053] The influence of environmental factors means that environmental factors are also one of the important reasons for azimuth pointing deviation. Rotating phased array radar works in an open natural environment and is affected by external factors such as wind and temperature changes. For example, in strong winds, the radar tower may tilt, causing the antenna installation angle to change, thereby causing azimuth errors. Studies have shown that in the case of high wind speeds or uneven wind force, the tower tilt angle can exceed 0.1°, further leading to scanning azimuth deviation. In addition, temperature changes can cause thermal expansion or contraction of the equipment, causing physical deformation of the bracket and mechanical system.

[0054] Electronic sensor error means that the accuracy of the azimuth angle depends on high-precision angle sensors. However, during the rotation process, the angle sensor is easily affected by electromagnetic interference and mechanical vibration, resulting in pointing errors. Some radars have significant azimuth errors due to sensor failure and signal drift during observation, especially in harsh environments, where the pointing deviation of the radar may reach 1°.

[0055] The beam smearing effect refers to the fact that the rotating phased array radar needs to maintain the beam consistency in azimuth during the rotation process, which will cause the beam smearing effect, thereby affecting the data accuracy. Beam smearing refers to the deviation caused by the inability of the antenna beam to completely point to the predetermined direction when rotating. Especially at a higher rotation speed, the real-time performance of the beam pointing decreases, resulting in a deviation between the actual scanning angle and the target azimuth. This effect will accumulate during continuous scanning, resulting in a dynamic deviation in the azimuth.

[0056] In order to solve the above problems, various calibration methods, including the use of drone-assisted measurement and the improvement of angle sensor accuracy, are time-consuming and costly. Figure 1 As shown, a rotating phased array radar azimuth calibration method based on ground object echo correlation is provided, which specifically includes the following steps:

[0057] Step S100, obtaining the PPI base data obtained by the current scan, the PPI base data of the current scan is obtained by scanning the rotating phased array radar in one circle, and is called the current circle data.

[0058] Step S110, using a fuzzy logic algorithm to process the current round data, and extracting ground object echo sample points in each azimuth area.

[0059] Step S120, based on the ground object echo sample points, for each azimuth area, calculate the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data.

[0060] Step S130, calibrating the azimuth angle of the azimuth angle area of ​​the current round by using the azimuth angle corresponding to the azimuth angle area in the previous round data with the maximum correlation.

[0061] In this application, an efficient solution for azimuth calibration based on ground object echo correlation is proposed. This method can correct the cumulative deviation of azimuth angle during continuous scanning based on the correlation of ground object echoes in two adjacent scanning data. Compared with the traditional method relying on mechanical sensors, the calibration method based on ground object echo correlation avoids the accumulation of sensor errors and mechanical errors, and can obtain and correct the azimuth angle deviation in a very short time, effectively reducing the azimuth angle deviation during the rotation process.

[0062] In step S100, the PPI base data to be processed is obtained by scanning a rotating phased array radar. The radar antenna of the rotating phased array radar performs a 360° mechanical rotation at a certain speed, thereby achieving all-round coverage on the horizontal plane. In this method, the PPI base data obtained after the radar antenna rotates one circle, that is, the current circle data, is processed in real time and the angles corresponding to each azimuth area are corrected. Among them, the azimuth area is obtained by dividing according to a preset angle, and the angles of each azimuth area are equal.

[0063] In step S110, the azimuth is corrected using the data related to the ground objects in the PPI base data, namely the ground object echo data. The ground object echo usually includes clutter generated by buildings, terrain features, etc. at low elevation angles. These clutters are fixed and unchanged, and the azimuth is calibrated by these fixed echoes.

[0064] In this embodiment, a fuzzy logic algorithm is used based on PPI basic data, such as horizontal polarization reflectivity Zh, differential reflectivity ZDR and correlation coefficient CC, which can effectively distinguish ground clutter and meteorological targets.

[0065] In this embodiment, for each azimuth region in the current round data, the signal-to-noise ratio (CNR) of the object echo is analyzed to adaptively select the optimal number of ground object echo sample points to ensure high correlation of the ground object echo. The optimization of the number of sample points can reduce the computational cost and reduce noise interference to a certain extent, thereby improving the accuracy of calibration.

[0066] Specifically, the number of ground object echo sample points is dynamically adjusted according to the amount of clutter and noise in the echo area, ensuring that the azimuth calibration is performed in an area with sufficient ground object echoes.

[0067] In step S120, when correcting the angle of a certain azimuth area in the current round data, the correction is performed through the corrected angles corresponding to the azimuth area of ​​the azimuth area in the previous round data and its adjacent multiple azimuth areas. Furthermore, by calculating the correlation between the azimuth areas, the corrected angle corresponding to the azimuth area in the previous round that has the greatest correlation with the current azimuth area to be corrected is selected for correction.

[0068] Specifically, when correcting the azimuth angle of the current azimuth angle area to be corrected, the azimuth angle is adjusted to the azimuth angle corresponding to the maximum correlation.

[0069] In this embodiment, when calculating the correlation between two azimuth angle regions between two adjacent scanning passes, the calculation is performed based on the Pearson correlation coefficient. It is conceivable that the calculation of the correlation may also use correlation algorithms including Spearman rank correlation coefficient, Kendall correlation coefficient or mutual information.

[0070] In this embodiment, when calculating the correlation, the calculation is performed based on the echo reflectivity of all ground object echo sample points in the two azimuth regions.

[0071] Specifically, the following formula is used to calculate the correlation:

[0072]

[0073] In formula (1), ρ(Z n-1 ,Z n ) represents the correlation between the two azimuth areas of the nth round, i.e. the current round, and the n-1th round, i.e. the previous round, Z n (i, r) represents the echo reflectivity of the ground object echo sample point at a distance of r in the i-th azimuth area of ​​the n-th circle, Z n represents the sampling point sequence of ground object echo in a certain azimuth area, R represents the maximum value of r, cov(Z n-1 ,Z n ) represents Z n-1 and Z n The covariance of , the superscript * indicates conjugate, σ indicates variance, and μ indicates mean.

[0074] Furthermore,

[0075]

[0076] In this embodiment, when calculating the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data, a correction range is set with the current azimuth area as the center, and the correlation between each azimuth area in the previous round of data within the correction range and the current azimuth area is calculated.

[0077] In one embodiment, the correction range is centered on the current azimuth area, three adjacent azimuth areas in the counterclockwise direction and three adjacent azimuth areas in the clockwise direction. That is, if the current azimuth area to be corrected is represented by A n i , where n represents the number of scans, and i represents the ith azimuth area. n i The azimuth area for correlation calculation is A n-1 i , A n-1 i-1 , A n-1 i-2 , A n-1 i-3 , A n-1 i+1 , A n-1 i+2 and An-1 i+3 7 azimuth zones.

[0078] Specifically, the correction range includes calibration values ​​corresponding to each azimuth area. When calculating the correlation between each azimuth area and obtaining the maximum correlation, the process is to find a calibration value corresponding to the maximum correlation, and then obtain the corresponding azimuth area through the calibration value. The process can be expressed as:

[0079] C n,i (l) = ρ(Z n (i),cirshift[Z n-1 (i),l]) (2)

[0080] In formula (2), cirshift[,] represents the cyclic shift function. When the calibration value l is 0, C n,i (l) represents Z n (i) With Z n-1 (i) When the calibration value l is 1, then C n,i (l) represents Z n (i) With Z n-1 (i+1), when the calibration value l is -1, then C n,i (l) represents Z n (i) With Z n-1 (i-1), and so on.

[0081] Further, it can be obtained through the following formula And the corresponding calibration value l:

[0082]

[0083] In formula (3), the value range of the calibration value l is taken as [-3, 3] as an example for explanation.

[0084] Next, in step S130, The corresponding calibration value l finds the azimuth angle corresponding to the corresponding azimuth area, and uses this angle as a reference to adjust the azimuth angle currently to be calibrated.

[0085] The azimuth angle calibration can be achieved by calibrating the azimuth angles corresponding to all azimuth angle areas in the current round in sequence according to the above calibration method.

[0086] Furthermore, considering that there are fewer ground object echoes or stronger noise in some azimuth areas, in order to avoid azimuth deviation caused by sudden changes in calibration values, the maximum correlation weighted smoothing method is used to find another calibration value l for azimuth calibration.

[0087] In this embodiment, if the calculated maximum correlation is less than the preset threshold: the weight of the maximum correlation is calculated, and a smoothing convolution operation is performed based on the weight and the calibration value corresponding to the maximum correlation to obtain an updated calibration value. In the previous round of data, the corresponding azimuth angle is extracted based on the correction range according to the updated calibration value, and the azimuth angle of the current round azimuth angle area is calibrated using the azimuth angle.

[0088] Specifically, the weight of the maximum correlation is calculated using the following formula:

[0089]

[0090] in,

[0091] In formula (4), represents the maximum correlation, W n,i represents the weight, and T represents the preset correlation threshold. Preferably, T can be set to 0.6.

[0092] It should be noted here that, in fact, when judging the maximum correlation, we use Among them, T is the preset threshold.

[0093] Specifically, a smoothing convolution operation is performed according to the calibration values ​​corresponding to the weights and maximum correlations, and the process is expressed as follows:

[0094]

[0095] In formula (5), L n,i represents the calibration value corresponding to the maximum correlation, represents the updated calibration value, K represents the convolution kernel, represents the convolution operation, and round[·] represents the rounding operation.

[0096] In one embodiment, the convolution kernel is selected as K = [1, 1, 1, 1, 1]

[0097] In this way, weighted smoothing processing ensures the continuity of azimuth calibration and avoids calibration errors caused by insufficient ground echo.

[0098] In this application, a specific algorithm is also proposed to implement the rotating phased array radar azimuth calibration method proposed in this paper, as shown below:

[0099] Input: n: total number of scans; Z n (i):PPI reflectivity

[0100] Output: Correction number When p=2; p<n, p++

[0101] When l∈[-3,3], calculate C n,i (l) = ρ(Z n (i),cirshift[Z n-1 (i),l]).

[0102] pass Get the l value and

[0103] Perform calculations in

[0104] Perform calculations,

[0105] Get the final correction number

[0106] End the loop

[0107] End the loop

[0108] In this paper, experimental data is also provided to prove the effectiveness of this method. Since the position of the ground object echo is fixed, if the two scan echoes are aligned, that is, the same azimuth when the radar measures, then they should be canceled out after subtraction. However, if one of the scans is not aligned, the clutter at the place measured by the radar is not in the same radial direction, and the subtraction of the two scans will still leave clutter. Figure 2 As shown, it is the distribution diagram of ground object echo in two consecutive scans, showing the azimuth deviation before calibration.

[0109] like Figure 3 The figure shows the distribution of ground object echoes after calibration based on the radar reading method.

[0110] like Figure 4 The figure shows the echo distribution of ground objects after calibration using this method. Figure 3 It can be seen that there are a lot of clutter. In contrast, after processing with this method, the amount of remaining clutter is greatly reduced. Construct the residual factor F to evaluate it:

[0111] use The remaining clutter is evaluated. The results are shown in the following table. Among them, the proposed method has the best performance.

[0112]

[0113]

[0114] The OMGCC method involves calculating the Pearson correlation coefficient between two scans. As the sequence length increases, the computational complexity also increases. The time complexity of calculating the average in Equation 1 and Equation 1 is O(n) and O(1), respectively. Assuming that there are m azimuths per scan, the time complexity of OMGCC is O(m×n), which confirms the importance of optimizing the radial length of each azimuth of the clutter to minimize unnecessary calculations. Then, the computational performance of the OMGC algorithm was evaluated. On a laptop equipped with a 2.3GHz CPU, the time complexity of the OMGCC algorithm was O(n). Figure 2 The average execution time of the algorithm for the medium scenario is about 4.6 seconds. Although the OMGCC algorithm involves multiple complex processes, including adaptive clutter region selection and correlation-based azimuth calibration adjustment, its computational efficiency is still high due to the application of optimization techniques.

[0115] In the above-mentioned rotating phased array radar azimuth calibration method based on ground object echo correlation, compared with traditional azimuth calibration methods that mostly rely on mechanical sensors or external calibration equipment, this method utilizes the high correlation characteristics of ground object echoes, and calculates and optimizes the azimuth calibration value through the consistency of ground object echoes in continuous scanning data. This calibration method based on echo correlation has the characteristics of strong adaptability and high real-time performance, and is suitable for rapid calibration of rotating polarization phased arrays in dynamic environments. At the same time, this method automatically identifies the ground object echo area through fuzzy logic algorithm, screens out valid sample points, and dynamically adjusts the number of sample points based on echo correlation, thereby reducing the amount of calculation while ensuring calibration accuracy. The adaptive optimization of the number of sample points can effectively reduce noise interference and improve calculation efficiency, so that the method can still maintain good calibration performance in a high noise environment.

[0116] This method uses a weighted smoothing algorithm based on correlation to address the situation where ground object echoes are insufficient in certain azimuths. By setting the maximum correlation weight, the calibration value is smoothed and convolved to ensure that correlation weighted smoothing is used in the azimuth direction where ground object echoes are lacking, reducing the impact of irrelevant noise on the calibration result, so that the azimuth calibration result remains continuous and stable.

[0117] This method can be directly applied to the existing rotating phased array radar system without additional hardware modification, so it has high feasibility in actual deployment. The algorithm design is simple and easy to implement, easy to integrate into the radar software system, suitable for the calibration and maintenance of various operating radars, and has good compatibility with existing radar systems and is easy to implement.

[0118] The azimuth calibration method based on ground object echo correlation has many advantages such as high accuracy, excellent efficiency and strong adaptability. It is suitable for the high-precision azimuth calibration needs of rotating phased array radar in complex meteorological observations.

[0119] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0120] In one embodiment, Figure 5 As shown, a rotating phased array radar azimuth calibration device based on ground object echo correlation is provided, comprising: a real-time base data acquisition module 200, a ground object echo sample point extraction module 210, a ground object echo-based correlation calculation module 220 and an azimuth calibration module 230, wherein:

[0121] The real-time base data acquisition module 200 is used to acquire the PPI base data obtained by the current scan. The PPI base data of the current scan is obtained by scanning the rotating phased array radar in one circle, and is called the current circle data.

[0122] The ground object echo sample point extraction module 210 is used to process the current round data using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle regions.

[0123] The correlation calculation module 220 based on the ground object echo is used to calculate the correlation between each azimuth area and multiple adjacent azimuth areas in the previous round data based on the ground object echo sample points.

[0124] The azimuth calibration module 230 is used to calibrate the azimuth angle of the azimuth angle area of ​​the current round by using the azimuth angle corresponding to the azimuth angle area in the previous round data with the maximum correlation.

[0125] For the specific definition of the rotating phased array radar azimuth calibration device based on ground object echo correlation, please refer to the definition of the rotating phased array radar azimuth calibration method based on ground object echo correlation in the above text, which will not be repeated here. Each module in the above-mentioned rotating phased array radar azimuth calibration device based on ground object echo correlation can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0126] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a rotating phased array radar azimuth calibration method based on ground object echo correlation is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0127] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0128] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0129] Acquire the PPI base data obtained by the current scan, wherein the PPI base data of the current scan is obtained by scanning the rotating phased array radar in one circle, and is referred to as the current circle data;

[0130] The current round data is processed by using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle regions;

[0131] Based on the ground object echo sample points, for each azimuth area, the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data is calculated;

[0132] The azimuth angle of the azimuth angle area in the previous round data with the maximum correlation is used to calibrate the azimuth angle of the current round azimuth angle area.

[0133] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0134] Acquire the PPI base data obtained by the current scan, wherein the PPI base data of the current scan is obtained by scanning the rotating phased array radar in one circle, and is referred to as the current circle data;

[0135] The current round data is processed by using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle regions;

[0136] Based on the ground object echo sample points, for each azimuth area, the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data is calculated;

[0137] The azimuth angle of the azimuth angle area in the previous round data with the maximum correlation is used to calibrate the azimuth angle of the current round azimuth angle area.

[0138] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0139] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0140] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for azimuth calibration of rotating phased array radar based on ground object echo correlation, characterized in that: The method comprises: Acquire the PPI base data obtained by the current scan, wherein the PPI base data of the current scan is obtained by scanning the rotating phased array radar in one circle, and is referred to as the current circle data; The current round data is processed by using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle regions; Based on the ground object echo sample points, for each azimuth area, the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data is calculated; The azimuth angle of the azimuth angle area in the previous round data with the maximum correlation is used to calibrate the azimuth angle of the current round azimuth angle area.

2. The rotating phased array radar azimuth calibration method according to claim 1, characterized in that: When calculating the correlation between two azimuth angle regions between two adjacent scanning passes, the calculation is performed based on the Pearson correlation coefficient.

3. The rotating phased array radar azimuth calibration method according to claim 2, characterized in that: When calculating the correlation, the calculation is performed based on the echo reflectivity of all ground object echo sample points in the two azimuth regions.

4. The method for azimuth calibration of a rotating phased array radar according to claim 3, characterized in that: The following formula is used to calculate the correlation: In the above formula, ρ(Z n-1 ,Z n ) represents the correlation between the two azimuth areas of the nth round, i.e. the current round, and the n-1th round, i.e. the previous round, Z n (i, r) represents the echo reflectivity of the ground object echo sample point at a distance of r in the i-th azimuth area of ​​the n-th circle, Z n represents the sampling point sequence of ground object echo in a certain azimuth area, R represents the maximum value of r, cov(Z n-1 ,Z n ) represents Z n-1 and Z n The covariance of , the superscript * indicates conjugate, σ indicates variance, and μ indicates mean.

5. The method for azimuth calibration of a rotating phased array radar according to any one of claims 1 to 4, characterized in that: When calculating the correlation between the azimuth area and multiple adjacent azimuth areas in the previous round of data, a correction range is set with the current azimuth area as the center, and the correlation between each azimuth area in the previous round of data within the correction range and the current azimuth area is calculated.

6. The method for azimuth calibration of a rotating phased array radar according to claim 5, characterized in that: The correction range is centered on the current azimuth area, three adjacent azimuth areas in the counterclockwise direction, and three adjacent azimuth areas in the clockwise direction, wherein the correction range includes calibration values ​​corresponding to each azimuth area.

7. The method for azimuth calibration of a rotating phased array radar according to claim 6, characterized in that: If the calculated maximum correlation is less than the preset threshold: Calculate the weight of the maximum correlation; Performing a smoothing convolution operation according to the weight and the calibration value corresponding to the maximum correlation to obtain an updated calibration value; In the previous round data, the corresponding azimuth angle is extracted according to the updated calibration value based on the correction range, and the azimuth angle of the current round azimuth angle area is calibrated using the azimuth angle.

8. The method for azimuth calibration of a rotating phased array radar according to claim 7, characterized in that: The weight of the maximum correlation is calculated using the following formula: in, In the above formula, represents the maximum correlation, W n,i represents the weight, and T represents the preset correlation threshold.

9. The method for azimuth calibration of a rotating phased array radar according to claim 8, characterized in that: A smoothing convolution operation is performed according to the weight and the calibration value corresponding to the maximum correlation, and the process is expressed as follows: In the above formula, L n,i represents the calibration value corresponding to the maximum correlation, represents the updated calibration value, K represents the convolution kernel, represents the convolution operation, and round[·] represents the rounding operation.

10. A rotating phased array radar azimuth calibration device based on ground object echo correlation, characterized in that: The device comprises: A real-time base data acquisition module is used to acquire the PPI base data obtained by the current scan. The PPI base data of the current scan is obtained by scanning the rotating phased array radar in one circle, and is called the current circle data; A ground object echo sample point extraction module is used to process the current round data using a fuzzy logic algorithm to extract ground object echo sample points in various azimuth angle areas; A correlation calculation module based on ground object echoes, for calculating the correlation between each azimuth area and a plurality of adjacent azimuth areas in the previous round of data based on ground object echo sample points for each azimuth area; The azimuth calibration module is used to calibrate the azimuth angle of the current round azimuth angle area using the azimuth angle corresponding to the azimuth angle area in the previous round data with the maximum correlation.

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