A method and system for detecting anomalies in the azimuth and elevation angles of ground features using weather radar

Abstract

This invention relates to a method and system for detecting anomalies in the azimuth and elevation angles of ground objects using weather radar. The method includes: acquiring the latest weather radar echo base data and standard ground object base data, and performing format transformation and normalization on the acquired data; comparing the acquired weather radar echo base data with the standard ground object base data using a ground object azimuth and elevation angle anomaly detection algorithm, calculating the matching degree of the ground object echoes to determine whether the elevation and azimuth angles are abnormal, and calculating the degree of deviation of the elevation and azimuth angles; when the azimuth and elevation angle anomaly detection step detects anomalies, issuing alarm prompts to the operator through various means. This invention detects azimuth and elevation angle anomalies by comparing them with standard ground objects. After the algorithm determines that an anomaly has occurred, it issues an audio and text alarm to prompt the operator to perform subsequent operations, improving the utilization rate of radar data.

Description

Technical Field

[0001] This invention relates to the field of radar detection technology, and in particular to a method and system for detecting anomalies in the azimuth and elevation angles of ground objects using weather radar. Background Technology

[0002] Ground object echoes refer to the echoes generated by the scattering of radar electromagnetic waves by mountains and various buildings on them. Ground object echoes are characterized by clear edges, fixed positions, and minimal intensity variations. Therefore, by observing changes in the intensity and position of ground object echoes under clear sky conditions, it is possible to determine whether the radar is experiencing anomalies in azimuth, elevation, or other aspects. Under clear sky conditions, the main data detected by radar scanning is ground object echo data, which has a high intensity. Historical clear sky ground object echoes are used as standard ground object echoes (Zr). Under the same elevation angle and repetition frequency requirements, the real-time detected ground object echoes (Zr) are compared with the standard ground object echoes (Zr) under clear sky conditions. There are numerous Doppler weather radars in service, widely distributed. Due to the long service life of many weather radars, the performance of some components has deteriorated, and antenna azimuth positioning has become inaccurate. This can lead to abnormal data in the radar echoes received. In such cases, the operator should be promptly notified and reminded to reposition the antenna or replace the components. If the operator fails to detect the echo data problems in time, the radar data quality will be poor, resulting in low radar data utilization.

[0003] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and system for detecting anomalies in the azimuth and elevation angles of ground objects in weather radar. This solves the problem that existing weather radars have low automation levels and cannot detect and alert in a timely manner when anomalies occur.

[0005] The objective of this invention is achieved through the following technical solution: a method for detecting anomalies in the azimuth and elevation angles of ground features using weather radar, the detection method comprising:

[0006] Data preprocessing steps: Under clear sky conditions, PPI scanning is performed at a low elevation angle to generate weather radar echo base data, acquire the latest weather radar echo base data and weather radar standard ground object base data, and perform format transformation and normalization processing on the acquired data.

[0007] Azimuth and elevation anomaly detection steps: The acquired weather radar echo base data and weather radar standard ground object base data are detected and compared by the ground object echo anomaly detection algorithm. The matching degree of the ground object echoes of the two is calculated to determine whether the elevation and azimuth angles are abnormal, and the degree of deviation of the elevation and azimuth angles is calculated.

[0008] Abnormal alarm procedure: When the azimuth and elevation angle abnormality detection procedure detects and identifies an abnormality in the azimuth and elevation angle, it will issue an alarm prompt to the operator through various means.

[0009] The azimuth and elevation angle anomaly detection steps specifically include the following:

[0010] Determine whether the elevation angles of the standard ground feature data and the measured echo base data are the same. If they are different, end the detection; if they are the same, proceed to the next step.

[0011] Determine whether the repetition frequency of the standard ground feature base data and the measured echo base data is the same. If they are different, end the detection; if they are the same, proceed to the next step.

[0012] Extract the unsuppressed reflectivity factor data that exceeds the threshold from the standard ground object base data and the measured echo data;

[0013] By changing the azimuth angle Az, the matching degree between each azimuth angle of the real-time detected ground object echo Z and the standard ground object echo Zr is calculated one by one. The correlation coefficient between the azimuth angle of the detected ground object echo Z and the standard ground object echo Zr is calculated. The maximum matching degree Pmax is obtained by the magnitude of the correlation coefficient value. Based on the relationship between the maximum matching degree Pmax and the set threshold, it is determined whether the elevation angle is normal, the elevation angle is abnormal, or the radar is faulty.

[0014] Obtain the azimuth angle Az value corresponding to the maximum matching degree Pmax, and determine whether the azimuth angle is normal;

[0015] Calculate the average intensity difference Avg between the standard ground feature echo Zr and the detected ground feature echo Z, and determine the deviation of the elevation angle based on the calculation results.

[0016] The method of determining whether the elevation angle is normal, abnormal, or the entire radar unit is faulty based on the relationship between the maximum matching degree Pmax and the set threshold includes: when the maximum matching degree Pmax > PValue1, the elevation angle is determined to be normal; when PValue2 ≤ Pmax ≤ PValue1, the elevation angle is determined to be abnormal; and when the maximum matching degree Pmax < PValue2, the entire radar unit is determined to be faulty.

[0017] The determination of whether the azimuth angle is normal includes: if Az≤AValue1 or Az≥AValue2, then the azimuth angle is normal; if the azimuth angle is abnormal, then the value of Az is the azimuth angle deviation angle.

[0018] The determination of the deviation of the elevation angle based on the calculation results includes: when abs(Avg) > GValue, it is a whole machine fault; when abs(Avg) ≤ GValue, an abnormal elevation angle occurs; if Avg > 0, the elevation angle is too small; if Avg < 0, the elevation angle is too large.

[0019] The calculation of the correlation coefficient includes:

[0020] Through formula Calculate the measured echo data Z (iAz,j) and standard ground feature data Zr (i,j) The correlation coefficient is given by iAz, where iAz represents the azimuth variation of the measured echo data, iAz = i + Az, iAz ∈ [0, 359]. When iAz ≥ 360, iAz = iAz - 360; when iAz < 0, iAz = iAz + 360. i represents the azimuth variation of the standard ground feature data, j represents the range database variation, A represents the azimuth number (obtained from the radar data file), and Bin represents the range database number (obtained from the radar data file).

[0021] Record the CORR value corresponding to each Az, and take the largest CORR value as the matching degree Pmax. If the maximum matching degree Pmax > PValue1, it is judged that the elevation angle is normal. If the maximum matching degree PValue2 ≤ Pmax ≤ PValue1, it is judged that the elevation angle is abnormal. If the maximum matching degree Pmax < PValue2, it is judged that the radar is faulty.

[0022] Record the angle Az corresponding to the maximum CORR value, denoted as iMax. If iMax≤AValue1 or iMax≥AValue2, the orientation is normal; if AValue1≤iMax≤AValue2, the orientation is abnormal.

[0023] The calculation of the average difference Avg includes:

[0024] Through formula The measured echo data Z (i,j) and standard features Zr (i,j) The average difference;

[0025] Determine the value of abs(Avg). If abs(Avg) ≥ GValue, then the entire radar unit is faulty.

[0026] When abs(Avg) < GValue and an abnormal elevation angle occurs, i.e. PValue1 ≤ Pmax ≤ PValue2, if Avg > 0, the elevation angle is too small; if Avg < 0, the elevation angle is too large.

[0027] A weather radar ground feature azimuth and elevation angle anomaly detection system includes a data preprocessing module, an azimuth and elevation angle anomaly detection module, and an anomaly alarm module;

[0028] The data preprocessing module: under clear sky conditions, generates weather radar echo base data by performing PPI scanning at a low elevation angle, acquires the latest weather radar echo base data and weather radar standard ground object base data, and performs format transformation and normalization processing on the acquired data.

[0029] The azimuth and elevation anomaly detection module: uses a ground object azimuth and elevation anomaly detection algorithm to detect and compare the acquired weather radar echo base data with the weather radar standard ground object base data, calculates the matching degree of the ground object echoes of the two to determine whether the elevation and azimuth angles are abnormal, and calculates and determines the deviation angles of the elevation and azimuth angles.

[0030] The abnormal alarm module: when the azimuth and elevation angle abnormality detection step detects and identifies an abnormal azimuth and elevation angle, it issues an alarm prompt to the operator in multiple ways.

[0031] The azimuth and elevation angle anomaly detection module includes a first judgment unit, a second judgment unit, and a calculation unit;

[0032] The first judgment unit is used to determine whether the elevation angle of the standard ground object base data and the measured echo base data are the same, and to determine whether the repetition frequency of the standard ground object base data and the measured echo base data are the same.

[0033] The calculation unit extracts unsuppressed reflectivity factor data greater than a threshold from the standard ground object base data and the measured echo data. By changing the azimuth angle Az, it calculates the matching degree between each azimuth angle of the real-time detected ground object echo Z and the standard ground object echo Zr. It calculates the correlation coefficient between the azimuth angle of the detected ground object echo Z and the standard ground object echo Zr. Based on the magnitude of the correlation coefficient value, it obtains the maximum matching degree Pmax and calculates the average intensity difference Avg between the standard ground object echo Zr and the detected ground object echo Z.

[0034] The second judgment unit: Based on the relationship between the maximum matching degree Pmax and the set threshold, it determines whether the elevation angle is normal, abnormal, or the radar is faulty, obtains the azimuth angle Az value corresponding to the maximum matching degree Pmax, judges whether the azimuth angle is normal, and judges the deviation of the azimuth angle based on the calculation results.

[0035] The present invention has the following advantages: a method and system for detecting anomalies in the azimuth and elevation angles of ground objects in weather radar can greatly improve the fully automated operation of Doppler weather radar, significantly reduce the workload of existing radar operators, reduce the number of weather radar operators, and solve the problem of erroneous data such as abnormal ground object echoes caused by the uneven technical level of radar operators, thereby improving the data quality of Doppler weather radar and achieving good economic benefits and practical significance. Attached Figure Description

[0036] Figure 1 This is a schematic flowchart of the method of the present invention;

[0037] Figure 2 This is a schematic diagram of the azimuth and elevation angle anomaly detection process of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of this application provided below with reference to the accompanying drawings is not intended to limit the scope of protection of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. The present invention will be further described below with reference to the accompanying drawings.

[0039] like Figure 1 As shown, this invention specifically relates to a method for detecting anomalies in the azimuth and elevation angles of ground objects in weather radar. Addressing the low level of automation in current Doppler weather radars, this invention designs an algorithm for detecting anomalies in the azimuth and elevation angles of ground objects in Doppler weather radar. This algorithm automatically identifies changes in ground object echoes within the Doppler weather radar. Based on the detection results, it determines whether the radar azimuth and elevation angles are abnormal and provides audio and text prompts to the operator, enabling timely adjustments to radar parameters. When the radar is in normal operating condition, under clear skies, it generates standard ground object echo data files through low elevation angle (0.5°, 1.0°, 1.5°, 2.0°) PPI scans. When a newly acquired PPI scan base data file is detected, the azimuth and elevation angle anomaly detection algorithm compares it with the standard ground object data file. When the algorithm detects an anomaly in the azimuth and elevation angles, it issues audio and text alarms to alert the operator that the radar is malfunctioning. This completes the radar azimuth and elevation angle anomaly detection process, achieving the goal of timely adjustment of radar parameters or radar maintenance, and improving the data quality of subsequent radar data.

[0040] like Figure 2 As shown, it specifically includes the following:

[0041] Step 1: Acquire radar standard ground object base data and newly generated measured base data;

[0042] Step 2: Data preprocessing. Normalize the single-polarization and dual-polarization basis data, save them in a uniform format, and then proceed with subsequent algorithm work.

[0043] Step 3: Determine if the elevation angle EL1 of the standard ground feature data is the same as the elevation angle EL2 of the measured data. Because the echo intensity, location, and shape of ground features at different elevation angles will vary, for the accuracy of the algorithm calculation, first determine if the elevation angles of the standard ground feature data and the measured data are the same. If EL1≠EL2, no further comparison is performed; if EL1=EL2, further comparison is performed.

[0044] Step 4: Determine if the repetition frequency FQ1 of the standard feature data is the same as the repetition frequency FQ2 of the measured data. Because different repetition frequencies have different library lengths, which can cause differences in feature echoes, to avoid the influence of library length, first determine if the repetition frequencies of the standard feature data and the measured data are the same. If FQ1 ≠ FQ2, no further comparison is performed; if FQ1 = FQ2, the algorithm is then executed. Read the repetition frequency parameters from the measured data and the standard feature data, and determine if the two repetition frequencies are the same. Note that if dual-frequency analysis is used, it is necessary to compare whether both repetition frequencies are the same; if one is different, subsequent comparisons are not performed.

[0045] Step 5: Extract the unsuppressed reflectance factor data >40dBz from the standard ground feature data and the measured data;

[0046] Step 6: Calculate the measured data Z by changing the azimuth angle Az. (iAz,j) and standard ground feature data Zr (i,j) The correlation coefficient. The formula for calculating the correlation coefficient is as follows:

[0047]

[0048] Where iAz represents the azimuth variation of the measured data; iAz = i + Az, iAz ∈ [0, 359], when iAz ≥ 360, iAz = iAz - 360, when iAz < 0, iAz = iAz + 360. i represents the azimuth variation of the standard ground feature data. j represents the range database variation. A represents the azimuth number, obtained from the radar data file. Bin represents the range database number, obtained from the radar data file.

[0049] Record the CORR value for each Az, and take the largest CORR value as the matching degree Pmax. If the maximum matching degree Pmax > PValue1, the elevation angle is judged to be normal; if the maximum matching degree PValue2 ≤ Pmax ≤ PValue1, the elevation angle is judged to be abnormal; if the maximum matching degree Pmax < PValue2, the radar system is judged to be faulty. PValue1 defaults to 0.8, and PValue2 defaults to 0.5.

[0050] Step 7: Based on the CORR values, record the Az angle corresponding to the maximum CORR value, denoted as iMax. If iMax≤AValue1 or iMax≥AValue2, the azimuth is normal; if AValue1≤iMax≤AValue2, the azimuth is abnormal. AValue1 defaults to 5°, and AValue2 defaults to 355°.

[0051] Step 8: Calculate the measured data Z (i,j) and standard features Zr (i,j) The average difference. The calculation formula is as follows:

[0052]

[0053] Determine the value of abs(Avg). If abs(Avg) ≥ GValue, then the radar system is faulty.

[0054] When abs(Avg) < GValue, and an abnormal elevation angle occurs (i.e., PValue1 ≤ Pmax ≤ PValue2), if Avg > 0, the elevation angle is too small; if Avg < 0, the elevation angle is too large. GValue defaults to 10.

[0055] The conclusions drawn from the factor criteria include:

[0056] Pmax < PValue2, indicating a radar system malfunction.

[0057] Pmax>PValue1 and iMax≤AValue1 or iMax≥AValue2, the elevation angle and azimuth angle are normal.

[0058] Pmax>PValue1 and AValue1≤iMax≤AValue2, the elevation angle is normal, the azimuth angle is abnormal, and the azimuth angle deviates from the angle iMax.

[0059] PValue2≤Pmax≤PValue1 and iMax≤AValue1 or iMax≥AValue2 and abs(Avg)<GValue and Avg>0, the elevation angle is too large and the azimuth angle is normal.

[0060] PValue2≤Pmax≤PValue1 and iMax≤AValue1 or iMax≥AValue2 and abs(Avg)<GValue and Avg<0, the elevation angle is too small and the azimuth angle is normal.

[0061] PValue2≤Pmax≤PValue1 and AValue1≤iMax≤AValue2 and abs(Avg)<GValue and Avg>0, the elevation angle is too large, the azimuth angle is abnormal, and the azimuth angle deviates from the angle iMax.

[0062] PValue2≤Pmax≤PValue1 and AValue1≤iMax≤AValue2 and abs(Avg)<GValue and Avg<0, the elevation angle is too small, the azimuth angle is abnormal, and the azimuth angle deviates from the angle iMax.

[0063] abs(Avg≥GValue) indicates a radar system malfunction.

[0064] Among them, PValue1 defaults to 0.8, PValue2 defaults to 0.5, AValue1 defaults to 5°, AValue2 defaults to 355°, and GValue defaults to 10.

[0065] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A method for detecting anomalies in the azimuth and elevation angles of ground features using weather radar, characterized in that: The detection method includes: Data preprocessing steps: Under clear sky conditions, PPI scanning is performed at a low elevation angle to generate weather radar echo base data, acquire the latest weather radar echo base data and weather radar standard ground object base data, and perform format transformation and normalization processing on the acquired data. Azimuth and elevation anomaly detection steps: The acquired weather radar echo base data and weather radar standard ground object base data are detected and compared by the ground object echo anomaly detection algorithm. The matching degree of the ground object echoes of the two is calculated to determine whether the elevation and azimuth angles are abnormal, and the degree of deviation of the elevation and azimuth angles is calculated. Abnormal alarm procedure: When the azimuth and elevation angle abnormality detection procedure detects and identifies an abnormal azimuth and elevation angle, it will issue an alarm prompt to the operator through various means; The azimuth and elevation angle anomaly detection steps specifically include the following: Determine whether the elevation angles of the standard ground feature data and the measured echo base data are the same. If they are different, end the detection; if they are the same, proceed to the next step. Determine whether the repetition frequency of the standard ground feature base data and the measured echo base data is the same. If they are different, end the detection; if they are the same, proceed to the next step. Extract the unsuppressed reflectivity factor data that exceeds the threshold from the standard ground object base data and the measured echo data; By changing the azimuth angle Az, the matching degree between each azimuth angle of the real-time detected ground object echo Z and the standard ground object echo Zr is calculated one by one. The correlation coefficient between the azimuth angle of the detected ground object echo Z and the standard ground object echo Zr is calculated. The maximum matching degree Pmax is obtained by the magnitude of the correlation coefficient value. Based on the relationship between the maximum matching degree Pmax and the set threshold, it is determined whether the elevation angle is normal, the elevation angle is abnormal, or the radar is faulty. Obtain the azimuth angle Az value corresponding to the maximum matching degree Pmax, and determine whether the azimuth angle is normal; Calculate the average intensity difference Avg between the standard ground feature echo Zr and the detected ground feature echo Z, and determine the deviation of the elevation angle based on the calculation results.

2. The method for detecting anomalies in the azimuth and elevation angles of ground features using weather radar according to claim 1, characterized in that: The method of determining whether the elevation angle is normal, abnormal, or the entire radar unit is faulty based on the relationship between the maximum matching degree Pmax and the set threshold includes: when the maximum matching degree Pmax > PValue1, the elevation angle is determined to be normal; when PValue2 ≤ Pmax ≤ PValue1, the elevation angle is determined to be abnormal; and when the maximum matching degree Pmax < PValue2, the entire radar unit is determined to be faulty. The determination of whether the azimuth angle is normal includes: if Az≤AValue1 or Az≥AValue2, then the azimuth angle is normal; if the azimuth angle is abnormal, then the value of Az is the azimuth angle deviation angle. The determination of the deviation of the elevation angle based on the calculation results includes: when abs(Avg) > GValue, it is a whole machine fault; when abs(Avg) ≤ GValue, an abnormal elevation angle occurs; if Avg > 0, the elevation angle is too small; if Avg < 0, the elevation angle is too large.

3. The method for detecting anomalies in the azimuth and elevation angles of ground features using weather radar according to claim 1, characterized in that: The calculation of the correlation coefficient includes: Through formula Calculate the measured echo data Z (iAz,j) and standard ground feature data Zr (i,j) The correlation coefficient is given by: where iAz represents the azimuth variation of the measured echo data, iAz = i + Az, iAz ∈ [0, 359]. When iAz ≥ 360, iAz = iAz - 360; when iAz < 0, iAz = iAz + 360. i represents the azimuth variation of the standard ground feature data, j represents the range database variation, A represents the azimuth number (obtained from the radar data file), and Bin represents the range database number (obtained from the radar data file). Record the CORR value corresponding to each Az, take the largest CORR value and record it as the maximum matching degree Pmax. If the maximum matching degree Pmax > PValue1, it is judged that the elevation angle is normal. If the maximum matching degree PValue2 ≤ Pmax ≤ PValue1, it is judged that the elevation angle is abnormal. If the maximum matching degree Pmax < PValue2, it is judged that the radar is faulty. Record the angle Az corresponding to the maximum CORR value, denoted as iMax; if iMax≤AValue1 or iMax≥AValue2, the orientation is normal; if AValue1≤iMax≤AValue2, the orientation is abnormal.

4. The method for detecting anomalies in the azimuth and elevation angles of ground features using weather radar according to claim 1, characterized in that: The calculation of the average difference Avg includes: Through formula The measured echo data Z (i,j) and standard features Zr (i,j) The average difference; Determine the value of abs(Avg). If abs(Avg) ≥ GValue, then the entire radar unit is faulty. When abs(Avg) < GValue and an abnormal elevation angle occurs, i.e. PValue1 ≤ Pmax ≤ PValue2, if Avg > 0, the elevation angle is too small; if Avg < 0, the elevation angle is too large.

5. A weather radar system for detecting anomalies in the azimuth and elevation angles of ground features, characterized in that: The weather radar ground feature azimuth and elevation angle anomaly detection method according to any one of claims 1 to 4 includes a data preprocessing module, an azimuth and elevation angle anomaly detection module, and an anomaly alarm module. The data preprocessing module: under clear sky conditions, generates weather radar echo base data by performing PPI scanning at a low elevation angle, acquires the latest weather radar echo base data and weather radar standard ground object base data, and performs format transformation and normalization processing on the acquired data. The azimuth and elevation anomaly detection module: uses a ground object azimuth and elevation anomaly detection algorithm to detect and compare the acquired weather radar echo base data with the weather radar standard ground object base data, calculates the matching degree of the ground object echoes of the two to determine whether the elevation and azimuth angles are abnormal, and calculates and determines the deviation angles of the elevation and azimuth angles. The abnormal alarm module: when the azimuth and elevation angle abnormality detection step detects and identifies an abnormal azimuth and elevation angle, it issues an alarm prompt to the operator in multiple ways.

6. A weather radar ground feature azimuth and elevation angle anomaly detection system according to claim 5, characterized in that: The azimuth and elevation angle anomaly detection module includes a first judgment unit, a second judgment unit, and a calculation unit; The first judgment unit is used to determine whether the elevation angle of the standard ground object base data and the measured echo base data are the same, and to determine whether the repetition frequency of the standard ground object base data and the measured echo base data are the same. The calculation unit extracts unsuppressed reflectivity factor data greater than a threshold from the standard ground object base data and the measured echo data. By changing the azimuth angle Az, it calculates the matching degree between each azimuth angle of the real-time detected ground object echo Z and the standard ground object echo Zr. It calculates the correlation coefficient between the azimuth angle of the detected ground object echo Z and the standard ground object echo Zr. Based on the magnitude of the correlation coefficient value, it obtains the maximum matching degree Pmax and calculates the average intensity difference Avg between the standard ground object echo Zr and the detected ground object echo Z. The second judgment unit: Based on the relationship between the maximum matching degree Pmax and the set threshold, it determines whether the elevation angle is normal, abnormal, or the radar is faulty, obtains the azimuth angle Az value corresponding to the maximum matching degree Pmax, judges whether the azimuth angle is normal, and judges the deviation of the azimuth angle based on the calculation results.

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