An Automatic Generation Method for the OBA Table of a Phased Array Secondary Radar Based on ADS-B

Abstract

The present invention provides a method for automatically generating an OBA table of a phased array secondary radar based on ADS-B, including five processes: ADS-B target autocorrelation, SSR target autocorrelation, SSR target and ADS-B target matching, eigenvalue processing of target matching, and calculation of OBA table application values to obtain the OBA table. This method does not require the cooperation of a test site, and there is no need for manual participation during the OBA table generation process. Only the addition of ADS-B function is required for cooperation, with low cost. This method can continuously learn and generate an actual OBA table for air surveillance in the equipment application environment. The obtained OBA table has a high azimuth accuracy and can meet the azimuth accuracy requirements of the vast majority of application scenarios.

Description

Technical Field

[0001] The present invention relates to the field of secondary radars, and particularly to a method for automatically generating an OBA table of a phased array secondary radar based on ADS-B. Background Art

[0002] With the rapid development of phased array technology and the improvement of manufacturing processes, phased array secondary radars are deployed on more application platforms. Compared with mechanically scanned secondary radars, phased array secondary radars have the advantages of flexible scanning, smaller volume, convenient concealment, and higher reliability. However, due to cost limitations, the beam widths of many phased array secondary radar platforms are very wide, usually reaching more than 10 degrees, and many error factors are introduced due to hardware differences at different wave positions, resulting in large azimuth errors. Therefore, in practical engineering applications, how to reduce azimuth errors and improve azimuth accuracy is of great significance for project implementation.

[0003] Currently, on phased array secondary radars, we commonly use the monopulse processing method to calculate the azimuth look-up table through the off-boresight angle (OBA). To reduce azimuth errors, we need to improve the accuracy of the OBA table. The OBA table stores the azimuth offset value of the target in the beam, and this value needs to be correlated with information such as wave position information, sum-channel sampling amplitude value, difference-channel sampling amplitude value, phase sign bit, and target detection distance.

[0004] There are mainly two methods for generating the OBA table of the current phased array secondary radar. One is to use the theoretical OBA table obtained from antenna simulation data; the other is to generate the OBA table through microwave anechoic chamber testing.

[0005] The theoretical OBA table obtained by the first method has a major drawback. That is, due to the limitations of existing processes and costs, many errors are introduced in the actual device hardware, resulting in a large gap between the theoretical OBA table and the actual OBA table, thus leading to low azimuth accuracy and often not meeting the requirements of many device platforms.

[0006] The tested OBA table obtained by the second method has high azimuth accuracy, but has three drawbacks. One is that the requirements for the test site are very high, usually requiring testing in a microwave anechoic chamber that meets certain requirements. The second is that the test workload is very large because there are differences at each wave position and also differences in different distance segments at the same wave position. The third is that the cost is very high because the use cost of the microwave anechoic chamber is very high and each set of equipment needs to be tested. Summary of the Invention

[0007] Aiming at the problems existing in the prior art, a method for automatically generating the OBA table of a phased array secondary radar based on ADS-B is provided. This method does not require the cooperation of a test site, and there is no need for manual participation during the generation process of the OBA table. Only the ADS-B function needs to be added for cooperation, and the cost is low. This method can continuously learn in the equipment application environment to generate the actual OBA table for the sky, and the azimuth accuracy of the obtained OBA table is relatively high, which can meet the requirements of azimuth accuracy for the vast majority of application scenarios.

[0008] The technical solution adopted by the present invention is as follows: A method for automatically generating the OBA table of a phased array secondary radar based on ADS-B, including:

[0009] ADS-B target autocorrelation: Receive and parse the ADS-B target information, and store it in the ADS-B target storage area;

[0010] SSR target autocorrelation: Receive and parse the SSR target information, and store it in the SSR target storage area;

[0011] SSR target and ADS-B target matching: Match the SSR target and the ADS-B target according to the SSR target information and the ADS-B target information. If the match is successful, establish or update the matching information in the corresponding storage area of the target; if the match fails, clear the corresponding matching information;

[0012] Processing of eigenvalue of target matching: Extract the targets whose matching information meets the conditions, and use the wave position value, distance segment, sum minus difference amplitude, and phase sign bit of the target as a group of eigenvalues for indexing. At the same time, calculate the difference between the azimuth of the ADS-B target corresponding to each group of eigenvalues and the reference azimuth of the wave position where the SSR target is located, as the lookup table value corresponding to this group of eigenvalues, that is, an OBA record value;

[0013] Calculation of OBA table application value: When the number of OBA record values corresponding to the same group of eigenvalues reaches the threshold number of times, remove the OBA record values with large deviations, and calculate the average value of the remaining OBA record values as the OBA table application value under the current group of eigenvalues.

[0014] Further, the specific process of the ADS-B target autocorrelation is as follows:

[0015] Step 1.1: Receive and parse the ADS-B target information in real time, including detection time, ICAO address, position information, and MA code;

[0016] Step 1.2: According to the position information of the secondary radar center and the ADS-B target, calculate the included angle azimuth and projection distance of the ADS-B target relative to the secondary radar center and due north;

[0017] Step 1.3. Traverse the ADS-B target storage area. If there is a historical ADS-B target with the same ICAO address as the current ADS-B target, directly update the current ADS-B target information to the corresponding ADS-B target storage area; otherwise, create a new ADS-B storage area to store the current ADS-B target information.

[0018] Further, the specific process of SSR target autocorrelation is as follows:

[0019] Step 2.1. Receive and parse SSR target information in real time, including detection time, detection beam azimuth, distance, MA code, and MC code.

[0020] Step 2.2. Calculate the reference azimuth and projection distance of the wave position where the SSR target is located.

[0021] Step 2.3. Traverse the SSR target storage area, correlate the current SSR target with historical SSR targets. If the correlation is successful, directly update the current SSR target information to the corresponding correlated SSR target storage area; otherwise, create a new SSR storage area to store the current SSR target information.

[0022] Further, in step 2.3, the correlation process is as follows: perform MA code correlation, set different azimuth correlation thresholds and distance correlation thresholds according to the correlation results; calculate the difference in reference azimuth and projection distance between the wave positions where the current SSR target and the historical SSR target are located. If the difference is within the corresponding thresholds, it indicates that the correlation is successful. Among them, the MA code correlation process is to determine whether the MA codes are the same. If the MA codes are the same, the threshold range can be set larger; if the MA codes are different, the threshold range is set smaller.

[0023] Further, the specific process of matching the SSR target with the ADS-B target is as follows:

[0024] Step 3.1. Determine whether a matching relationship has been established between the current SSR target and the ADS-B target. If so, perform priority matching and go to step 3.2; otherwise, perform new matching and go to step 3.4.

[0025] Step 3.2. Calculate the azimuth, projection distance, and altitude predicted by the ADS-B target.

[0026] Step 3.3. Perform correlation matching between the reference azimuth, projection distance, and altitude of the wave position where the current SSR target is located and the azimuth, projection distance, and altitude predicted by the ADS-B target. If the matching is successful, update the matching information and go to step 3.9; otherwise, clear the matching information, perform new matching, and go to step 3.4.

[0027] Step 3.4: Traverse the ADS-B target storage area for rough position correlation. For ADS-B targets that meet the rough position correlation threshold, proceed to Step 3.5; otherwise, keep the matching information empty.

[0028] Step 3.5: Perform MA code matching on the ADS-B targets that meet the rough correlation threshold. If the MA code exists in the ADS-B target decoding information and is consistent with the current SSR target MA code, it indicates successful MA code matching; otherwise, it indicates matching failure. Set the corresponding precise position correlation threshold according to the MA code matching result.

[0029] Step 3.6: Perform azimuth, projected distance, and altitude prediction for the ADS-B targets that meet the rough correlation threshold. Step 3.7: Calculate the differences between the current SSR target and the ADS-B targets that meet the rough correlation threshold in sequence, and compare the differences with the corresponding precise correlation thresholds. If the differences are within the thresholds, it indicates successful precise correlation. If there is one or more ADS-B targets that are precisely correlated successfully with the SSR target, proceed to Step 3.8; otherwise, keep the matching information empty.

[0030] Step 3.8: Perform multi-matching screening: Calculate the difference between the projected distance of the SSR target and the projected distances of the ADS-B targets that are precisely correlated successfully, and establish a matching relationship between the ADS-B target with the smallest difference and the current SSR target.

[0031] Step 3.9: Complete the matching and update the matching information between the SSR target and the ADS-B target.

[0032] Furthermore, the correlation matching process in Step 3.3 is as follows: Set the azimuth correlation threshold, distance correlation threshold, and altitude correlation threshold according to the actual platform environment. Calculate the differences between the reference azimuth, projected distance, and altitude of the current SSR target's wave position and the azimuth, projected distance, and altitude predicted by the ADS-B target. If the differences are within the corresponding thresholds, it indicates successful matching; otherwise, it indicates matching failure.

[0033] Furthermore, the eigenvalue processing of the target matching specifically includes:

[0034] Step 4.1: Read the matching information of the SSR target and record the OBA data for the targets that meet the matching times.

[0035] Step 4.2: Obtain four eigenvalue parameters of the SSR target, namely the wave position value, distance segment, sum and difference amplitude, and phase sign bit, and use them as index parameters.

[0036] Step 4.3: Calculate the difference between the reference azimuth of the SSR target's wave position and the azimuth of the ADS-B target, and use this value as the look-up table value corresponding to the index parameter, that is, an OBA record value.

[0037] Step 4.4: Repeat steps 4.2 to 4.3 until all OBA data records that meet the matching number target are completed, forming an OBA table with four eigenvalues as index parameters.

[0038] Furthermore, the OBA table application value calculation process is:

[0039] Step 5.1: Determine whether the number of OBA record values corresponding to the same set of characteristic values is greater than the set OBA application value calculation threshold. If yes, proceed to step 5.2; otherwise, continue with OBA data recording.

[0040] Step 5.2: Sort all OBA record values corresponding to the set of eigenvalues and remove some record values that are too large or too small;

[0041] Step 5.3: Calculate the average value of the OBA record values after the elimination process as the application value of the OBA table under this set of characteristic values.

[0042] Furthermore, the elimination process in step 5.2:

[0043] For a set of OBA records corresponding to the eigenvalues OBA record [n][…], where n ranges from {0, 1, …, N-1}, N represents the total number of OBA record values, and […] is [BeamNum][RangStep][SumDel][Sign];

[0044] If N≤2, retain the OBA record value corresponding to n=0;

[0045] If N=3, retain the OBA record value corresponding to n=1;

[0046] If N ≥ 4 and N is an even number, retain the OBA record value corresponding to n = {N / 2-1, N / 2};

[0047] If N ≥ 4 and N is an odd number, the OBA record value corresponding to n = {N / 2-1, N / 2, N / 2+1} is retained.

[0048] Furthermore, the calculation expression of the application value in step 5.3 is:

[0049]

[0050] Among them, OBA record [n][…] represents all OBA record values of a set of eigenvalues, where n ranges from {0, 1, …, N-1}, N represents the total number of OBA record values, and […] is [BeamNum][RangStep][SumDel][Sign].

[0051] Compared with the prior art, the beneficial effects of adopting the above technical solution are as follows:

[0052] 1. By utilizing the feature that the OBA table in the present invention can automatically generate the OBA table during use, a large amount of manual testing and statistics work in the early stage can be reduced. Moreover, after the hardware changes, the OBA table can be adaptively generated, reducing the maintenance work of the equipment in the later stage.

[0053] 2. By utilizing the feature that the OBA table in the present invention is generated based on ADS-B, ADS-B is widely applied in the current air traffic control field, and most of the targets in the airspace have ADS-B functions. Therefore, the speed of automatically generating the OBA table will be very fast, with high efficiency, and the OBA table can be quickly improved.

[0054] 3. The solution proposed by the present invention can be applied to many phased array secondary radar platforms quickly and at low cost, and has high azimuth accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is the overall flowchart proposed by the present invention.

[0056] Figure 2 It is the self-correlation flowchart of ADS-B targets proposed by the present invention.

[0057] Figure 3 It is the self-correlation flowchart of SSR targets proposed by the present invention.

[0058] Figure 4 It is the matching flowchart of ADS-B and SSR targets proposed by the present invention.

[0059] Figure 5 It is the eigenvalue processing flowchart of target matching proposed by the present invention.

[0060] Figure 6 It is the OBA table application value calculation flowchart proposed by the present invention.

[0061] Figure 7 It is the comparison chart of the theoretical OBA and the measured OBA of the same wave position of a certain phased array secondary radar proposed by the present invention.

[0062] Figure 8 It is the comparison chart of the measured OBAs of two different wave positions of a certain phased array secondary radar proposed by the present invention.

[0063] Figure 9 It is the comparison chart of the theoretical OBA table, the automatic OBA table, and ADS-B targets of a certain wave position of a certain phased array secondary radar proposed by the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0064] The present invention will be further described below with reference to the accompanying drawings.

[0065] Example 1

[0066] like Figure 1 As shown, this embodiment proposes a method for automatically generating an OBA table for a phased array secondary radar based on ADS-B, including:

[0067] ADS-B target autocorrelation: Receive and parse ADS-B target information and store it in the ADS-B target storage area;

[0068] SSR target autocorrelation: Receive and parse SSR target information and store it in the SSR target storage area;

[0069] Matching of SSR targets and ADS-B targets: Matching of SSR targets and ADS-B targets based on SSR target information and ADS-B target information. If the match is successful, the matching information is created or updated in the target's corresponding storage area; if the match fails, the corresponding matching information is cleared;

[0070] Target matching eigenvalue processing: Targets whose matching information meets the conditions are extracted, and the target's wave position value, range segment, sum difference amplitude, and phase sign bit are used as a set of eigenvalues for indexing. At the same time, the difference between the ADS-B target azimuth corresponding to each set of eigenvalues and the reference azimuth of the wave position where the SSR target is located is calculated as the lookup value corresponding to the set of eigenvalues, that is, an OBA record value;

[0071] OBA table application value calculation: When the number of OBA record values corresponding to the same set of characteristic values reaches the threshold, the OBA record values with large deviations are removed, and the average value of the retained OBA record values is calculated as the OBA table application value under the current set of characteristic values.

[0072] Specifically, during the ADS-B target autocorrelation process, the stored ADS-B target information includes detection time, ICAO address, MA code, longitude, latitude, altitude, relative azimuth, relative projection distance, azimuth change rate, distance change rate, altitude change rate, and number of matches. adsb , relative projection distance Range adsb-throw Need to be based on the ADS-B target latitude and longitude Pos adsb (Lon, Lat) and the latitude and longitude of the secondary radar center position Pos ssr (Lon,Lat) is calculated.

[0073] Specifically, during the SSR target autocorrelation process, the stored SSR target information includes: detection time, detection beam azimuth, relative projection distance, response height, and MA code. ssr-throwIt needs to be calculated based on the slant range Range detected by the secondary radar ssr-slant , the target reply altitude Height ssr-trans and the secondary radar antenna altitude Height ssr-ant .

[0074] In this embodiment, during the matching process of SSR targets and ADS-B targets, the matching information includes the matching information of SSR targets and the matching information of ADS-B targets respectively, which represents the corresponding matching relationship. Specifically, the matching information corresponding to the SSR target includes: the ICAO address Addr of the ADS-B target ICAO , the ADS-B target storage area index value Index adsbbuf , the number of successful matches MatchCnt adsb-ssr ; the matching information corresponding to the ADS-B target includes: the SSR target storage area index value Index ssrbuf , the number of successful matches MatchCnt adsb-ssr .

[0075] Due to the hardware differences of each TR in the phased array secondary radar, the OBA table for each wave position is different, and the OBA tables for the same wave position also vary in different distance segments. Therefore, it is very difficult to obtain the OBA information for all distance segments of all wave positions. Through an automatic OBA table generation method for phased array secondary radar based on ADS-B proposed in this embodiment, this problem can be perfectly solved. Moreover, this method does not require the cooperation of a test site, and no manual participation is needed during the OBA table generation process. Only the ADS-B function needs to be added for cooperation, with low cost. At the same time, it can continuously learn to generate the actual OBA table for airspace in the equipment application environment. The obtained OBA table has a high azimuth accuracy and can meet the azimuth accuracy requirements of most application scenarios.

[0076] Figure 7 Figure [ID] is a comparison chart of the theoretical OBA and the measured OBA of the same wave position of a phased array secondary radar. It can be seen that there are differences between the theoretical OBA and the measured OBA of the same wave position, and there are also differences in the measured OBAs at different distances. Therefore, it is reasonable for the OBA table automatic generation method to generate OBA application data according to different distance segments in the actual airspace, which is an important means to reduce the azimuth error.

[0077] Figure 8 Figure [ID] is a comparison chart of the measured OBAs of two different wave positions of a phased array secondary radar at the same distance. It can be clearly seen that there are differences in the measured OBAs of different wave positions in the same distance segment. Therefore, the OBA table automatic generation method can effectively reduce the azimuth error caused by the differences between different wave positions by generating OBA application data for different wave positions respectively.

[0078] Figure 9A comparison chart of a theoretical OBA table, an automatic OBA table, and ADS-B targets for a certain beam position of a phased array secondary radar. In this chart, taking the ADS-B target as the reference position, the standard deviations of the target azimuth obtained using the theoretical OBA table and the automatic OBA table are calculated respectively. The standard deviation of the target azimuth using the theoretical OBA table is 1.49, and the standard deviation of the target azimuth using the automatic OBA table is 0.27. The larger standard deviation of the target azimuth obtained by the theoretical OBA table indicates that the azimuth angle has a larger deviation compared with the azimuth of the ADS-B target, so the azimuth accuracy is lower. The smaller standard deviation of the target azimuth obtained by the automatic OBA table indicates that the azimuth angle has a smaller deviation compared with the azimuth of the ADS-B target, so the azimuth accuracy is higher, and the overall effect is significantly better than that of the theoretical OBA table. Therefore, when there is a large difference between the theoretical OBA and the actual beam space coverage, using the automatic OBA table to calculate the SSR target azimuth can effectively improve the azimuth accuracy.

[0079] Example 2

[0080] This embodiment is implemented on the basis of Embodiment 1 and provides a specific ADS-B target autocorrelation method as follows:

[0081] As Figure 2 shown is the ADS-B target autocorrelation flowchart proposed in this embodiment, including the following steps:

[0082] Step 1.1: Receive the original decoded information of the ADS-B target in real time, and parse to obtain the ADS-B target information required for subsequent processes, including detection time, ICAO address, position information, and MA code;

[0083] Step 1.2: Calculate the included angle azimuth and projection distance of the ADS-B target relative to the center of the secondary radar and due north;

[0084] Step 1.3: According to the ICAO address, perform correlation processing on the new ADS-B target and the historical ADS-B targets. Traverse the ADS-B storage area. If there is a target with the same ICAO address, update the information to the ADS-B target storage area and enter Step 24; if there is no target with the same ICAO address, then create a new ADS-B target information storage area and enter Step 25;

[0085] When updating the ADS-B information, the content to be updated includes: detection time, MA code, longitude, latitude, altitude, relative azimuth, relative projection distance, azimuth change rate, distance change rate, altitude change rate, and matching times.

[0086] Step 1.5: Create a new ADS-B target storage area, and the stored content includes: detection time, ICAO address, MA code, longitude, latitude, altitude, relative azimuth, relative projected distance, and number of matches; where the number of matches is MatchCnt adsb = 1.

[0087] Specifically, in Step 1.2, the calculation methods for the azimuth angle between the ADS-B target relative to the secondary radar center and due north and the projected distance are as follows:

[0088] (Azi adsb , Range adsb-throw ) = f(Pos adsb (Lon, Lat), Pos ssr (Lon, Lat))

[0089] where the function of the f function is to convert longitude and latitude to azimuth and distance, Pos adsb (Lon, Lat) is the longitude and latitude of the ADS-B target, Pos ssr (Lon, Lat) is the longitude and latitude of the secondary radar center position, Azi adsb is the relative azimuth (the azimuth angle between the ADS-B target relative to the secondary radar center and due north), Range adsb-throw is the relative projected distance (the projected distance between the ADS-B target relative to the secondary radar center and due north).

[0090] Specifically, in Step 1.4, the number of matches MatchCnt adsb = (MatchCnt adsb + 1), and the azimuth change rate AziRate, distance change rate RangRate, and altitude change rate HeightRate need to be calculated from the historical ADS-B information, and the calculation methods are as follows:

[0091]

[0092] where t0 / t1 / t2 / t3 respectively represent the ADS-B target decoding times of the 1st / 2nd / 3rd / 4th to last times, and ΔAzi / ΔRang / ΔHeight respectively represent the differences in azimuth / distance / altitude.

[0093] Example 3

[0094] This example is implemented based on Example 1 or Example 2, and a specific SSR target self-correlation method is proposed, as follows:

[0095] As Figure 3 shown, the SSR target self-correlation flowchart proposed in this example includes the following steps:

[0096] Step 2.1: The secondary radar initiates a combined MA and MC interrogation, receives the original decoded information of the SSR target in real time, and parses the SSR target information required in the subsequent process, including detection time, detection beam azimuth, distance, MA code, and MC code.

[0097] Step 2.2: Calculate the reference azimuth Azi ssr-beamNorth and the projected distance Range ssr-throw ;

[0098] Step 2.3: Correlate the new SSR target with the historical SSR targets according to the relative north azimuth of the detection beam, the projected distance, and the MA code. Traverse the SSR target storage area. If the correlation is successful, update the information to the SSR target information storage area. If the correlation fails, create a new SSR target information storage area. The information to be stored includes: detection time, detection beam azimuth, relative projected distance, reply altitude, and MA code.

[0099] Specifically, in Step 2.2, the calculation methods for the reference azimuth Azi ssr-beamNorth and the projected distance Range ssr-throw of the SSR target at the wave position are as follows:

[0100] Calculation of the reference azimuth of the SSR target at the wave position:

[0101] Azi ssr-beamNorth = Mod(Azi ssr-beamRef + Azi ssr-North + 360, 360), where Mod represents the remainder function, Azi ssr-beamRef represents the reference azimuth of the detection beam, and Azi ssr-North represents the angle between the reference starting azimuth of the secondary radar and the north.

[0102] Calculation method of the projected distance:

[0103]

[0104] where Range ssr-slant 2 is the slant range detected by the secondary radar, Height ssr-trans is the target reply altitude, and Height ssr-ant is the antenna height of the secondary radar.

[0105] Preferably, the specific method of correlation in Step 2.3 is as follows:

[0106] First, correlate the new SSR target with the MA codes of the historical SSR targets, and set the azimuth correlation threshold AziGate CodeSame / AziGateCodeDiff RangeGate related to distance CodeSame / RangGate CodeDiff , calculate the differences between the relative azimuth and relative projected distance of the new SSR target and the historical SSR target. If the differences are within the corresponding thresholds, it indicates successful correlation; if there is successful one-to-many correlation, filter out the unique SSR correlated target according to the MA code and the change value of the relative projected distance, that is, the new SSR correlated targets with the same MA and smaller differences in relative projected distance.

[0107] Among them, the basis for threshold setting is: if the new SSR target has the same MA code, the threshold range can be set larger; if the MA codes are different, the threshold range is set smaller.

[0108] Embodiment 4

[0109] This embodiment is implemented based on Embodiment 3 and proposes a specific method for matching SSR targets and ADS-B targets, which is as follows:

[0110] As Figure 4 shown is the flowchart of matching SSR targets and ADS-B targets proposed in this embodiment, including the following steps:

[0111] Step 3.1: After the SSR target completes autocorrelation in real time, continue to match the SSR target with the ADS-B target;

[0112] Step 3.2: Determine whether the SSR target establishes a matching relationship with an ADS-B target. If so, perform priority matching, that is, enter Step 3.3; if not, perform new matching, that is, enter Step 3.5;

[0113] Step 3.3: According to the detection time t ssr of the SSR target, the detection time t adsb of the ADS-B target, the relative due north azimuth Azi adsb of the ADS-B target, the projected distance Range adsb-throw of the ADS-B target, the azimuth change rate AziRate, the distance change rate RangRate, and the height change rate HeightRate of the ADS-B target, calculate the predicted azimuth Azi adsb-estimate , projected distance Range adsbThrow-estimate and height Height adsb-estimate of the ADS-B target;

[0114] Specifically, the calculation methods for the predicted azimuth, projected distance, and height of the ADS-B are:

[0115] (Azi adsb-estimate,Range adsbThrow-estimate ,Height adsb-estimate4 )

[0116] =(Azi adsb ,Range adsb-throw ,Height adsb )+(AziRate,RangRate,HeightRate)

[0117] ×(t ssr -t adsb )

[0118] Step 3.4. Correlate the reference azimuth, projected range, and reply height of the current SSR target's wave position with the predicted azimuth, projected range, and height of the ADS-B target. If the correlation is successful, update the target matching information, i.e., proceed to Step 3.10; if the correlation fails, clear the matching information and perform a new correlation, i.e., proceed to Step 3.5;

[0119] In this step, the correlation is based on reasonable azimuth correlation thresholds AziGate priMatch , range correlation thresholds RangGate priMatch , and height correlation thresholds HeightGate priMatch adjusted according to the actual platform application environment; calculate the differences between the reference azimuth, projected range, and height of the current SSR target's wave position and the predicted azimuth, projected range, and height of the ADS-B target. If the differences are within the corresponding thresholds, it indicates a successful match; otherwise, it indicates a failed match..

[0120] Step 3.5. Traverse the ADS-B target storage area for rough position correlation. If the rough correlation is successful, proceed to Step 3.6; otherwise, end the matching and keep the matching information empty;

[0121] In this step, the rough position correlation is performed through corresponding rough correlation thresholds, including azimuth rough correlation threshold AziGate WideMatch , range rough correlation threshold RangGate WideMatch , and height rough correlation threshold HeightGate WideMatch , and the corresponding rough correlation thresholds can be adjusted according to the actual platform application environment; calculate the differences between the relative azimuth, projected range, and height of the current SSR target and the relative azimuth, projected range, and height of all ADS-B targets in the ADS-B target storage area. If the differences are within the corresponding rough correlation thresholds, it indicates a successful rough correlation, and all ADS-B targets with successful rough correlation are obtained.

[0122] Step 3.6: Perform MA code matching on the ADS-B targets that meet the coarse correlation threshold. If there is an MA code in the ADS-B target decoding information and it is the same as the current SSR target MA code, it indicates successful MA code matching; otherwise, it indicates matching failure. Set the corresponding fine correlation threshold according to the MA code matching result.

[0123] Specifically, the fine correlation threshold includes the azimuth fine correlation threshold AziGate NMatch-MA / AziGate NMatch , the range fine correlation threshold RangGate NMatch-MA / RangGate NMatch , and the altitude fine correlation threshold HeightGate NMatch-MA / HeightGate NMatch ; The subscripts NMatch-MA and NMatch represent the thresholds when the MA codes are the same and different, respectively.

[0124] Judge whether the MA codes are the same. If the MA codes are the same, the fine threshold range can be set larger; if the MA codes are different, the fine threshold range is set smaller.

[0125] Step 3.7: Use the same method as in Step 3.3 to perform azimuth, projected range, and altitude pre-estimation on the ADS-B targets that meet the coarse correlation threshold.

[0126] Step 3.8: Calculate the differences between the current SSR target and the ADS-B targets that meet the coarse correlation threshold in sequence, and compare the differences with the corresponding fine correlation thresholds. If the difference is within the threshold, it indicates successful fine correlation; if there is one or more ADS-B targets that are successfully fine correlated with the SSR target, go to Step 3.9; otherwise, keep the matching information empty.

[0127] Step 3.9: Perform multi-match screening. After traversing the ADS-B target storage area, if the SSR target is successfully matched with more than one ADS-B target, it is necessary to sort according to the projected range difference ΔRang NMatch and determine the minimum value match as the final matching relationship; if only one ADS-B target is successfully matched, directly determine the matching relationship with the SSR target

[0128] In this step, the calculation method of the projected range difference is as follows:

[0129] ΔRang NMatch = |Range ssr-throw - Range adsbThrow-estimate |;

[0130] Step 3.10: Complete the matching and update the target matching information. The updated information in the SSR target storage area includes: ICAO address Addr ICAO and the index value Index of the ADS-B target storage area adsbbuf , and the number of successful matches MatchCnt adsb-ssr . The updated information in the ADS-B target storage area includes: the index value Index of the SSR target storage area ssrbuf and the number of successful matches MatchCnt adsb-ssr .

[0131] In this embodiment, the distance threshold corresponds to comparing the relative projection distance difference, the azimuth threshold corresponds to comparing the relative azimuth difference, and the altitude threshold corresponds to comparing the altitude difference.

[0132] Embodiment 5

[0133] This embodiment is implemented based on Embodiment 4, and a specific method for processing the eigenvalue of target matching is proposed as follows:

[0134] As Figure 5 shown in the flowchart of the eigenvalue processing for target matching proposed in this embodiment, it includes the following steps:

[0135] Step 4.1: Obtain the matching information of the SSR target. According to the matching times threshold MatchGate adsb-ssr set by the actual station, for the SSR and ADS-B matching targets with the number of matches MatchCnt adsb-ssr ≥MatchGate adsb-ssr , record the OBA data;

[0136] Step 4.2: Obtain four eigenvalue parameters, namely the beam number BeamNum, the distance segment RangStep, the subtraction amplitude SumDel, and the phase sign bit Sign of the SSR target as index parameters.

[0137] Among them, RangStep is calculated based on the distance segment DisSeg divided by the actual platform and the detected slant range Range ssr-slant of the SSR target. The calculation method is as follows: RangStep = [Range ssr-slant / DisSeg];

[0138] Step 4.3: Calculate the difference between the reference azimuth Azi ssr-beamNorth of the wave position where the SSR target is located and the azimuth Azi adsb of the ADS-B target, and use this value as the look-up table value corresponding to the index parameter, that is, one OBA record value OBA record . The same set of eigenvalue parameters can be associated with multiple sets of OBA record values.

[0139] The calculation representation method is as follows: OBA record [n][BeamNum][RangStep][SumDel][Sign] = Azi adsb -Azi ssr-beamNorth , where n represents the serial number of the OBA record value;

[0140] Example 6

[0141] This example is based on Example 5 and proposes a specific calculation method for the application value of the OBA table, which is as follows:

[0142] As Figure 6 shown in the flowchart of the calculation of the application value of the OBA table proposed in this example, it includes the following steps:

[0143] Step 51: Determine whether the number N of OBA record values corresponding to the same set of characteristic values is greater than or equal to the OBA application value calculation threshold NGate. If so, go to Step 52; if not, do not perform the calculation of the OBA table application value;

[0144] Step 5.2: Obtain all OBA record values of the same set of characteristic values

[0145] OBA record [n][BeamNum][RangStep][SumDel][Sign], where the range of n is {0, 1,..., N - 1}, and N represents the total number of OBA record values;

[0146] Step 5.3: Sort the OBA record values by size through a sorting algorithm, (OBA record [0][…], …, OBA record [N - 1][…]) = G(OBA record [0][…], …, OBA record [N - 1][…]), where […] is

[0147] the abbreviation of [BeamNum][RangStep][SumDel][Sign], and the function G represents the sorting algorithm;

[0148] Step 5.4: Adjust the range according to the effect of the actual device, and eliminate some values that are too large or too small.

[0149] The proposed rule in this step is:

[0150] If N ≤ 2, keep n = 0; if N = 3, keep n = 1; if N ≥ 4 and N is even, keep n = {N / 2 - 1, N / 2}; if N ≥ 4 and N is odd, keep n = {N / 2 - 1, N / 2, N / 2 + 1};

[0151] Step 5.5: Obtain the OBA record values after elimination, calculate the average value, and use it as the application value of the OBA table under the same set of characteristic values. The calculation method is expressed as follows:

[0152]

[0153]

[0154] , where […] is the abbreviation of [BeamNum][RangStep][SumDel][Sign].

[0155] The present invention is not limited to the foregoing specific embodiments. The present invention extends to any new feature or any new combination disclosed in this specification, as well as any new method or process step or any new combination disclosed. If those skilled in the art make non-substantial changes or improvements without departing from the spirit of the present invention, they should fall within the scope of protection of the claims of the present invention.

[0156] All the features disclosed in this specification, or all the steps in the disclosed methods or processes, except for mutually exclusive features and / or steps, can be combined in any manner.

[0157] Any feature disclosed in this specification, unless specifically stated, can be replaced by other equivalent or similar-purpose alternative features. That is, unless specifically stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. An automatic generation method for the OBA table of a phased array secondary radar based on ADS-B, characterized in that, include: ADS-B target autocorrelation: Receive and parse ADS-B target information and store it in the ADS-B target storage area; SSR target autocorrelation: Receive and parse SSR target information and store it in the SSR target storage area; Matching of SSR targets and ADS-B targets: Matching of SSR targets and ADS-B targets based on SSR target information and ADS-B target information. If the match is successful, the matching information is created or updated in the target's corresponding storage area; if the match fails, the corresponding matching information is cleared; Target matching eigenvalue processing: Targets whose matching information meets the conditions are extracted, and the target's wave position value, range segment, sum difference amplitude, and phase sign bit are used as a set of eigenvalues for indexing. At the same time, the difference between the ADS-B target azimuth corresponding to each set of eigenvalues and the reference azimuth of the wave position where the SSR target is located is calculated as the lookup value corresponding to the set of eigenvalues, that is, an OBA record value; OBA table application value calculation: When the number of OBA record values corresponding to the same set of characteristic values reaches the threshold, the OBA record values with large deviations are removed, and the average value of the retained OBA record values is calculated as the OBA table application value under the current set of characteristic values.

2. The method for automatically generating an OBA table of a phased array secondary radar based on ADS-B according to claim 1, wherein, The specific process of the ADS-B target autocorrelation is: Step 1.1: Receive and analyze ADS-B target information in real time, including detection time, ICAO address, location information, and MA code; Step 1.2: Based on the position information of the secondary radar center and the ADS-B target, calculate the angle azimuth and projected distance of the ADS-B target relative to the secondary radar center and true north; Step 1.3: Traverse the ADS-B target storage area. If there is a historical ADS-B target with the same ICAO address as the current ADS-B target, directly update the current ADS-B target information to the corresponding ADS-B target storage area; otherwise, create a new ADS-B storage area to store the current ADS-B target information.

3. The method for automatically generating the OBA table of the phased array secondary radar based on ADS-B according to claim 1 or 2, characterized in that The specific process of the SSR target autocorrelation is: Step 2.1: Receive and analyze SSR target information in real time, including detection time, detection beam direction, distance, MA code, and MC code; Step 2.2, calculate the reference azimuth and projection distance of the wave position where the SSR target is located; Step 2.3, traverse the SSR target storage area, correlate the current SSR target with the historical SSR target, if the correlation is successful, directly update the current SSR target information to the corresponding related SSR target storage area; otherwise, create a new SSR storage area to store the current SSR target information.

4. The method for automatically generating an OBA table of a phased array secondary radar based on ADS-B according to claim 3, wherein In step 2.3, the correlation process is: perform MA code correlation, set different azimuth correlation thresholds and distance correlation thresholds according to the correlation results; calculate the reference azimuth difference and projection distance difference between the wave position of the current SSR target and the historical SSR target, and if the difference is within the corresponding threshold, it means that the correlation is successful.

5. The method for automatically generating the OBA table of the phased array secondary radar based on ADS-B according to claim 3, characterized in that, The specific process of matching the SSR target with the ADS-B target is as follows: Step 3.

1. Determine whether a matching relationship has been established between the current SSR target and the ADS-B target. If so, perform priority matching and proceed to Step 3.2; otherwise, perform new matching and proceed to Step 3.

4. Step 3.

2. Calculate the azimuth, projected distance, and altitude predicted by the ADS-B target. Step 3.

3. Perform correlation matching between the reference azimuth, projected distance, and altitude of the current SSR target's wave position and the azimuth, projected distance, and altitude predicted by the ADS-B target. If the matching is successful, update the matching information and proceed to Step 3.9; otherwise, clear the matching information, perform new matching, and proceed to Step 3.

4. Step 3.

4. Traverse the ADS-B target storage area and perform rough position correlation. The ADS-B targets that meet the rough position correlation threshold will proceed to Step 3.5 for processing; otherwise, keep the matching information empty. Step 3.

5. Perform MA code matching on the ADS-B targets that meet the rough correlation threshold. If the MA code exists in the decoded information of the ADS-B target and is the same as the current SSR target's MA code, it indicates successful MA code matching; otherwise, it indicates matching failure. Set the corresponding fine position correlation threshold according to the MA code matching result. Step 3.

6. Predict the azimuth, projected distance, and altitude of the ADS-B targets that meet the rough correlation threshold. Step 3.

7. Calculate the differences between the current SSR target and the ADS-B targets that meet the rough correlation threshold in sequence, and compare the differences with the corresponding fine correlation thresholds. If the differences are within the thresholds, it indicates successful fine correlation. If there is one or more ADS-B targets that are successfully fine correlated with the SSR target, proceed to Step 3.8; otherwise, keep the matching information empty. Step 3.

8. Perform multi-matching screening: Calculate the difference between the projected distance of the SSR target and the projected distances of the ADS-B targets that are successfully fine correlated. Establish a matching relationship between the ADS-B target with the smallest difference and the current SSR target. Step 3.

9. Complete the matching and update the matching information between the SSR target and the ADS-B target.

6. The method for automatically generating an OBA table of a phased array secondary radar based on ADS-B according to claim 5, wherein The correlation matching process in Step 3.3 is as follows: Set the azimuth correlation threshold, distance correlation threshold, and altitude correlation threshold according to the actual platform environment. Calculate the differences between the reference azimuth, projected distance, and altitude of the current SSR target's wave position and the azimuth, projected distance, and altitude predicted by the ADS-B target. If the differences are within the corresponding thresholds, it indicates successful matching; otherwise, it indicates matching failure.

7. The method for automatically generating the OBA table of the phased array secondary radar based on ADS-B according to claim 5, characterized in that, The eigenvalue processing of the target matching specifically includes: Step 4.

1. Read the matching information of the SSR target and record the OBA data for the targets that meet the matching times. Step 4.

2. Obtain four eigenvalue parameters of the SSR target, namely the wave position value, distance segment, sum and difference amplitude, and phase sign bit, and use them as index parameters. Step 4.

3. Calculate the difference between the reference azimuth of the SSR target's wave position and the azimuth of the ADS-B target, and use this value as the look-up value corresponding to the index parameter, that is, an OBA record value. Step 4.4: Repeat steps 4.2 to 4.3 until all OBA data records that meet the matching number target are completed, forming an OBA table with four eigenvalues as index parameters.

8. The method for automatically generating an OBA table of a phased array secondary radar based on ADS-B according to claim 7, characterized in that The OBA table application value calculation process is: Step 5.1: Determine whether the number of OBA record values corresponding to the same set of characteristic values is greater than the set OBA application value calculation threshold. If yes, proceed to step 5.2; otherwise, continue with OBA data recording. Step 5.2: Sort all OBA record values corresponding to the set of eigenvalues and remove some record values that are too large or too small; Step 5.3: Calculate the average value of the OBA record values after the elimination process as the application value of the OBA table under this set of characteristic values.

9. The method for automatically generating an OBA table of a phased array secondary radar based on ADS-B according to claim 8, wherein The elimination process in step 5.2: For the sorted OBA record values OBA corresponding to a set of eigenvalues record [n][…], where the range of n is {0, 1, …, N-1}, N represents the total number of OBA record values, and […] is [BeamNum][RangStep][SumDel][Sign]; among them, BeamNum represents the wave position value of the SSR target, RangStep represents the distance segment, SumDel represents the sum-difference amplitude, and Sign represents the phase sign bit; If N≤2, retain the OBA record value corresponding to n=0; If N=3, retain the OBA record value corresponding to n=1; If N ≥ 4 and N is an even number, retain the OBA record value corresponding to n = {N / 2-1, N / 2}; If N ≥ 4 and N is an odd number, the OBA record value corresponding to n = {N / 2-1, N / 2, N / 2+1} is retained.

10. The method for automatically generating an OBA table of a phased array secondary radar based on ADS-B according to claim 9, wherein The calculation expression of the application value in step 5.3 is: Among them, OBA record [n][…] represents all the OBA recorded values of a set of eigenvalue, where the range of n is {0, 1, …, N - 1}, N represents the total number of OBA recorded values, and […] is [BeamNum][RangStep][SumDel][Sign].

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