An optimized ground radar detection range index simulation flight test verification method

Abstract

The present application relates to radar performance detection technical field, specifically to a kind of optimized ground radar detection range index simulation flight verification method, based on aircraft target detection performance simulation method, set the same target height layer and corresponding distance section, the midpoint of distance section is calculated corresponding elevation, then keep the elevation unchanged, respectively according to radial direction, back station flight two kinds of ways determine route interval, simultaneously collect detection sample, traverse all sampling intervals to complete the elevation sampling point coverage in vertical plane.The beneficial effects achieved by the present application are: the test can be carried out repeatedly according to the sample size requirement, the efficiency is improved;considering the factors such as hovering time and hovering stability of unmanned aerial vehicle take-off platform, the actual operation is easier to realize;greatly reduce the test duration and test data sample size.

Description

Technical Field

[0001] This invention relates to the field of radar technology, and in particular to an optimized method for simulating and verifying the detection range index of ground radar. Background Technology

[0002] Radar equipment is primarily used for tasks such as air and sea surveillance, monitoring and early warning of ballistic missile targets, near-space targets, and space targets; target designation, guidance, tracking, and measurement; air traffic control and port vessel control; battlefield reconnaissance, fire correction, and artillery aiming (fire control); and meteorological detection. Radar is a key component of air defense early warning and detection systems, playing a crucial role in information acquisition, intelligence gathering, and precision guidance. Currently, a relatively mature set of technical standards has been established for the tactical performance testing and acceptance of radar equipment. Based on relevant national military standards, specially arranged aircraft test flights have long been an important means of verifying the detection power and measurement accuracy of radar equipment, among other key tactical performance indicators.

[0003] However, with the development of radar technology, traditional methods based on actual aircraft flight tests are gradually failing to meet the needs of tactical performance testing and evaluation of radar equipment. Specifically, this is reflected in the following aspects: 1. New radar equipment has a wider range of detection targets and more diversified functions, resulting in a lack of cooperative targets and a significant increase in the demand for test resources, making coordination difficult; 2. The detection performance boundary capabilities of radar equipment are difficult to fully and thoroughly assess using actual aircraft flight tests; 3. Existing purely simulation-based digital verification methods are still in the exploratory stage, and their authenticity and accuracy have certain gaps.

[0004] Based on this, our company has designed an optimized simulation test and verification method for the detection range index of bottom-surface radar, drawing on years of radar R&D experience. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide an optimized method for simulating and verifying radar detection range indicators by reducing the difficulty of testing techniques and shortening the testing time.

[0006] Specifically, the shortcomings of the existing technology will be explained: I. This section explains the existing radar equipment detection capability testing techniques and methods. According to GJB 74A-1998 "General Specifications for Military Radar", the detection power performance of radar is mainly verified through actual aircraft as target aircraft in real-world testing (e.g., Figure 1 , Figure 2 (As shown); When setting up the test environment, the following requirements must be met: (1) Test route setup: The target aircraft should perform radial, equal altitude, and back-to-back station flights at four or more different altitudes, including the minimum test altitude and the maximum test altitude; (2) The minimum test altitude should generally be the minimum detection altitude specified in the tactical specifications. If the target aircraft cannot fly at the specified minimum detection altitude, the minimum test altitude shall be arranged according to the following provisions: a) Plains: The minimum flight altitude of the target aircraft is generally 100m to 300m above the highest point of the ground; b) Mountainous areas: The target aircraft's minimum flight altitude is generally 300m to 600m above the highest point on the ground; (3) The maximum test altitude should be the maximum detection altitude specified in the tactical and technical specifications. If the target aircraft cannot fly at the maximum detection altitude as required, the power reduction method can be used to allow the target aircraft to appropriately reduce its flight altitude. After the test, the actual detection altitude and range of the radar can be calculated and explained in detail in the test report. If the test results at the maximum test altitude show that the maximum detection altitude of the radar cannot meet the requirements, the flight altitude of the target aircraft should be reduced for the test to ensure that the actual maximum detection altitude and range of the radar under test are obtained. In summary, existing testing methods using real aircraft as targets are sampling methods based on a certain level of confidence. These methods place high technical demands on the performance of the real aircraft. However, the detection performance requirements of next-generation radar equipment are significantly higher than before, with maximum detection ranges and altitudes far exceeding the actual performance of real aircraft. Some new radar systems even need to detect missile targets and near-space targets, making the organization and coordination of the tests extremely difficult. Therefore, the traditional live-fire test method using real equipment as targets cannot achieve the goal of understanding the performance baseline of next-generation radar equipment, nor is it suitable for the equipment testing and verification needs under the new circumstances. II. Explanation of conventional simulation testing techniques and methods for the detection power performance of radar equipment; In response to the shortcomings of existing radar equipment detection performance testing techniques, simulation testing methods have emerged on the market. These methods utilize simulation and digital simulation technologies, employing semi-physical simulation methods or equipment to simulate targets, interference, and complex electromagnetic environment background signals. This replaces the use of actual aircraft or minimizes the need for actual aircraft test flights, thereby enabling the testing and evaluation of radar equipment detection performance indicators. Compared to existing traditional real-aircraft flight test verification methods, this simulation verification method has outstanding advantages such as supporting multiple target types, low test cost, high confidentiality, large sample size, clear boundaries, repeatability, and facilitating problem analysis. Through test scenario settings, the test environment can be quickly built, and the detection range performance of radar equipment can be fully grasped, greatly improving the controllability and resource friendliness of the test. In the specific implementation process, towers, drones, and other similar equipment were used as launch platforms. A simulation system was installed to construct the test environment. Based on the elevation angle coverage index of the radar under test, the correlation array between elevation angle and launch platform height was calculated in advance. During the test, the launch platform was first fixed at a height corresponding to a specific elevation angle. After completing the simulation test at that elevation angle height using the same number of flight tests as the actual test flight, the launch platform height was adjusted to simulate target echoes at other elevation angles. Power curves were plotted based on the tests at different elevation angles. Compared to existing traditional on-aircraft flight test verification methods, this simulation method is a full-scale test method. It can more completely and accurately plot multiple radar detection power curves that meet different detection probability requirements, and can obtain the radar's full detection power performance from a detection probability of 1% to 100%. However, this results in an excessively large test sample size for this simulation verification method, which places extremely high demands on the flight platform, especially the UAV flight platform, in terms of loiter time and hovering stability (in layman's terms, due to the large sample size to be measured, current UAVs cannot stay in the air for such a long time to measure all of these samples). The actual operation is technically very difficult (according to analysis and statistics, for the new generation of multi-functional and multi-mode radar equipment on the market, the test time and test data sample size using this test method are tens or even hundreds of times that of the on-aircraft flight test verification method).

[0007] Therefore, in order to overcome the shortcomings of existing simulation methods, this application designs an optimized simulation and flight verification method for ground radar detection range indicators based on existing simulation methods, so as to reduce the technical difficulty of actual operation and greatly shorten the test time.

[0008] To achieve the above-mentioned objectives, the present invention provides the following technical solution: An optimized method for simulating and verifying the detection range index of ground radar includes: S1. Based on the radar's factory parameters, obtain the power curve at the time of manufacture, thereby determining the farthest distance at which the detection probability can be satisfied at the time of manufacture for each altitude level. S2. Conduct flight measurements; S21. Select a height layer and determine the farthest horizontal distance that can satisfy the detection probability when the height layer is manufactured; use the height layer as the vertical axis and the corresponding farthest horizontal distance that can satisfy the detection probability when the height layer is manufactured as the horizontal axis to find the starting point. S22. Construct the first flight segment and calculate the first elevation angle; Starting from the initial position, fly X distances closer to the radar at different altitudes. The segment corresponding to this X distance is the first flight path segment. Starting from the initial position, the point where the plane is located after flying X / 2 distances closer to the radar at different altitudes is the first auxiliary point. Calculate the elevation angle from the first auxiliary point to the radar - referred to as the first elevation angle. S23, The simulation system rises to a certain height; There is an airborne platform at a certain distance from the radar. The airborne platform includes a drone, which is equipped with a simulation system. The drone lifts the simulation system up and hovers together. After lifting and hovering, the elevation angle of the drone relative to the radar is the same as the first elevation angle. S24. In the simulation system, set the simulated target RCS, target heading, and flight speed; Based on the first elevation angle and the horizontal distance of the first auxiliary point relative to the radar, the simulated target RCS, target heading, and flight speed are set in the simulation system. The size of the simulated target RCS is manually set according to the horizontal distance from the first auxiliary point to the radar. The target heading is radial or rearward flight at the altitude layer with the first auxiliary point as the starting point. The flight speed is manually set according to the first elevation angle and the horizontal distance of the first auxiliary point relative to the radar. S25: The radar generates transmit and receive signals, and the simulation system generates multiple simulated target signals; In the first segment of the flight path, there are multiple observation points at different locations. Multiple simulated target signals are generated by the simulation system. The simulated target signals are the signals of the simulated aircraft flying to the corresponding observation points. The radar detects whether these signals can be detected. The number of detected signals / the number of observation points = the detection probability of the first segment of the flight path. S26. Construct the second segment of the flight path, and then complete the detection. The first auxiliary point is defined as the first auxiliary point flying X distances closer to the radar along the altitude layer, and the segment corresponding to this X distance is defined as the second flight path segment; the point where the first auxiliary point is located after flying X / 2 distances closer to the radar along the altitude layer is defined as the second auxiliary point, and the elevation angle of the second auxiliary point relative to the radar is calculated, i.e., the second elevation angle. There is an overlapping area between the second segment of the route and the first segment of the route; Using the second elevation angle as the standard for the UAV's ascent altitude, and setting the corresponding simulated target RCS, target heading, and flight speed based on the second elevation angle and the horizontal distance of the second auxiliary point relative to the radar, the detection of the second flight path section is completed in accordance with the method of S23~S25. S27. Following the method in S26, complete the detection of multiple flight path sections until the elevation angle of the corresponding auxiliary point reaches the required value of 35°. S28. After all flight path intervals corresponding to the altitude layer have been detected, plot the relationship between the detection probability and the horizontal distance with the horizontal distance of each auxiliary point relative to the radar as the abscissa and the detection probability of the corresponding flight path interval as the ordinate. Based on the plot, find the detection probability that meets the technical requirements and find the maximum detection range of the radar at this altitude layer. S29. Select another new altitude layer and, following the steps in S21 to S28, complete the detection of the corresponding flight path section to find the maximum detection range of the radar at that altitude layer. This allows us to obtain the maximum detection range of the radar at various altitude levels; S3. Based on the maximum detection range of the radar at each altitude level obtained in S2, redraw the radar's power curve to complete the verification and calibration of the radar's power curve at the time of manufacture.

[0009] As a preferred technical solution of this application, in S2, during the period when the UAV ascends and hovers, it can detect one or more observation points in a flight path section.

[0010] As a preferred technical solution of this application, the simulation system simulates the echo characteristic information of the simulated target at each observation point, including the distance from the simulated target to the radar, the echo intensity from the simulated target to the radar, and the echo velocity from the simulated target to the radar.

[0011] As a preferred technical solution of this application, the distance from the simulated target to the radar is achieved by adjusting the delay of the simulation system, and the delay time is calculated using the following formula: Where R is the distance from the simulated target to the radar, r is the distance from the simulation system to the radar, tm is the processing and forwarding time of the target simulation system after receiving the radar signal, c is the speed of light in a vacuum, Δt target is the time difference from the transmission of the radar wave signal to the receipt of the simulated target feedback signal, Δt simulation is the time difference from the transmission of the radar wave signal to the receipt of the feedback signal from the UAV carried by the simulation system, and Δt is the delay time of the simulation system.

[0012] As a preferred technical solution of this application, the echo intensity from the simulated target to the radar is achieved by adjusting the output power Ptsim of the simulation system. The formula for calculating the adjusted output power Ptsim is as follows: In the formula, Pt is the radar transmit power, Gt is the main lobe antenna gain, r is the distance from the simulation system to the radar, R is the distance from the simulated target to the radar, Gtsim is the antenna gain of the target simulation system, L1 is the distance-related attenuation from the target to the radar, and L2 is the distance-related attenuation from the simulator to the radar.

[0013] As a preferred technical solution of this application, the echo velocity is achieved by adjusting the frequency offset of the analog system, and the formula for calculating the frequency offset is as follows: In the formula, V is the simulated speed of the aircraft target; λ is the radar signal wavelength; and β is the angle between the simulated target's direction of motion and the radial direction of the target and the radar.

[0014] As a preferred technical solution of this application, the echo characteristic information also includes the energy change caused by the radar target cross-section and distance, which is achieved by adjusting the power of the target simulation system; wherein, the radar target cross-section is represented by RCS.

[0015] The present invention has the following advantages: (1) Improve and optimize the existing "conventional simulation test technology and method for radar equipment detection power performance"; verify and correct the power curve again based on the radar power curve known at the time of manufacture; design the simulated target flight path with reference to the actual equipment test flight method; and take a distance segment at each elevation angle point as the simulated target observation distance interval (i.e., the flight path interval) to carry out the test. a. The advantage is that the present invention has better experimental repeatability, and can be repeated multiple times according to sample size requirements, thereby improving the cost-effectiveness ratio; Specifically, the current ground radar equipment uses real aircraft targets for flight testing. This requires a lot of effort to coordinate the aircraft, flight path, alternate landing point, and test items. It also requires consideration of various safety risks and environmental factors. Therefore, the test may be affected by different factors, which may lead to different degrees of deviation in the test object, test conditions, test process, test data collection, and even test results. It is impossible to achieve "uniformity". The simulation test method of the present invention can maintain the consistency of test objects, test conditions and test process, and can repeat the same test multiple times according to the sample size requirements. Under the same number of test times, the consistency and repeatability of test results are greatly improved. b. The advantage is that this invention can accurately obtain radar detection performance results; Specifically, this invention fully considers factors such as the loiter time and hovering stability of the UAV launch platform. When the UAV flies up from the tower and hovers once, it can complete the measurement of all the observation points in a flight path section (generally, the UAV needs to fly up and hover multiple times to complete the measurement of the corresponding observation points, and the position of the UAV flying up and hovering each time may be deviated). This reduces the influence of external environmental conditions and can be implemented "step by step" to accurately obtain the radar detection performance effect. (2) The test duration and sample size are only a fraction of those of conventional simulation testing methods; Conventional simulation verification techniques are a complete enumeration method, which aims to obtain all detection probability results (from 0 to 100%) of the radar at a certain elevation angle and different ranges (0~600km), and to determine the set of test parameters of "elevation angle-detection range-detection probability result"; The present invention, at the same elevation angle, only needs to be tested around the 80% (the detection probability required by the technology) detection probability result. Then, a distance segment of 10km (or 20km) is selected from the distance range of 0 to 600km near this result. The sample size of the test is greatly reduced (at least to 1 / 60 or 1 / 30), and the test time is also greatly reduced accordingly. Attached Figure Description

[0016] Figure 1 A schematic diagram showing the positions of ground radar, towers, drones, simulation systems, and simulated targets; Figure 2 A schematic diagram simulating the target flight path section; Figure 3 This diagram illustrates the elevation angles between each auxiliary point and the radar, with a first auxiliary point at an altitude of 30,000m and a horizontal distance of 600km, and a distance X of 5km. Figure 4 This diagram illustrates the altitude error caused by flight at the same elevation angle and altitude at altitudes of 30,000m, 10,000m, and 7,000m. Figure 5 The probability curve of radar detection of simulated targets is shown with a height of 30,000m and a horizontal distance of 600km as the first auxiliary point, and a distance X of 5km. Figure 6 Power curves for different discovery probabilities; Figure 7 The schematic diagram for target RCS simulation. Detailed Implementation

[0017] The present invention will be further described below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the following description.

[0018] (Example) like Figures 1-6 As shown, an optimized method for simulating and verifying the detection range index of ground radar includes: S1. Based on the radar's factory parameters, obtain the power curve at the time of manufacture, thereby determining the farthest distance at which the detection probability can be satisfied at the time of manufacture for each altitude level. S2. Conduct flight measurements; S21. Select a 30,000m altitude layer and determine that the furthest horizontal distance at which this altitude layer can satisfy the probability of detection at the time of manufacture is 600km; Figure 2 As shown, with the 30,000m altitude layer as the vertical axis and the corresponding farthest horizontal distance of 600km that satisfies the detection probability at the time of manufacture as the horizontal axis, the starting point is found; S22. Construct the first flight segment and calculate the first elevation angle; like Figure 2 As shown, with the starting point as the initial position, the plane flies 10km away from the radar at an altitude (this 10km distance can be understood as the sampling interval). The 10km section corresponding to this flight path is the first flight path interval. With the starting point as the initial position, the point where the plane flies 595km away from the radar at an altitude is the first auxiliary point. The elevation angle from the first auxiliary point to the radar is calculated - referred to as the first elevation angle. S23, The simulation system rises to a certain height; like Figure 1 As shown, there is an airlift platform at a distance r from the radar. The airlift platform includes a tower fixed to the base, with a height of H1. A drone is placed on the top of the tower, and the drone is equipped with a simulation system (the simulation system is existing technology). After the drone is parked on the top of the tower, it takes off upward or downward. The drone drives the simulation system to rise first, and then the height of the drone and the simulation system relative to the ground is H2. At this time, the elevation angle of the drone and the simulation system relative to the radar is the same as the first elevation angle. S24. In the simulation system, set the simulated target RCS, target heading, and flight speed; Based on the first elevation angle and the horizontal distance of the first auxiliary point relative to the radar, the simulated target RCS, target heading, and flight speed are set in the simulation system. The simulated target RCS is manually set based on the horizontal distance from the first auxiliary point to the radar; here, at an altitude of 30,000 meters, the simulation system generates a SwerLing-I type target with a simulated RCS of 2m². The target heading is radial or back-to-base flight at the altitude, starting from the first auxiliary point; here, it is within the range of 590km to 600km, and can be either simulated radial or back-to-base straight flight. The flight speed is manually set based on the first elevation angle and the horizontal distance of the first auxiliary point relative to the radar. S25: The radar generates transmit and receive signals, and the simulation system generates multiple simulated target signals; In the first segment of the flight path, from 590km to 600km, at least 80 observation points at different locations are set up. The multiple simulated target signals generated by the simulation system are used to simulate the signals generated by the real aircraft at these observation points. That is, the echo characteristic information of the simulated target signals generated by the simulation system is consistent with the echo characteristic information of the signals generated by the real aircraft at these observation points. Then, the number of simulated target signals detected by radar is calculated as follows: Number of simulated target signals detected / Number of observation points = Detection probability of the first segment of the flight path. The formula is: Pi—probability of discovery; Ni—The number of observation points in the corresponding flight path section; Mi—Imagine the number of simulated target signals discovered within a space zone; S26. Construct the second segment of the flight path, and then complete the detection. The rule is that the first auxiliary point (i.e., the 595km point) is used to fly 10km closer to the radar along the altitude layer. The route corresponding to this 10km is the second route interval - i.e., 595km~585km; the point where the first auxiliary point is located after flying X / 2 closer to the radar along the altitude layer is the second auxiliary point - i.e., the 590km point. The elevation angle of the second auxiliary point relative to the radar - i.e., the second elevation angle - is calculated. There is an overlapping area between the second segment of the route and the first segment of the route; Using the second elevation angle as the standard for the UAV's ascent altitude, and setting the corresponding simulated target RCS, target heading, and flight speed based on the second elevation angle and the horizontal distance of the second auxiliary point relative to the radar, the detection of the second flight path section is completed in accordance with the method of S23~S25. S27. Following the method in S26, complete the detection of multiple flight path sections until the elevation angle of the corresponding auxiliary point reaches the required value of 35°. S28. After all flight path intervals corresponding to the altitude layer have been detected, plot the relationship between the detection probability and the horizontal distance with the horizontal distance of each auxiliary point relative to the radar as the abscissa and the detection probability of the corresponding flight path interval as the ordinate. Based on the plot, find the detection probability that meets the technical requirements and find the maximum detection range of the radar at this altitude layer. Specifically, such as Figure 5 As shown, at an altitude of 30,000m, the radar can only detect targets at a certain horizontal distance between 500km and 550km (targets cannot be detected beyond a horizontal distance of 550km). Based on the design requirement that a detection probability of more than 80% is necessary to meet the technical requirements, a horizontal line is drawn to find the horizontal distance that equals the 80% detection probability. This horizontal distance is taken as the maximum detection range at an altitude of 30,000m. S29. Select another new altitude layer and, following the steps in S21 to S28, complete the detection of the corresponding flight path section to find the maximum detection range of the radar at that altitude layer. This allows us to obtain the maximum detection range of the radar at various altitude levels; S3. Based on the maximum detection range of the radar at each altitude level obtained in S2, redraw the radar's power curve to complete the verification and calibration of the radar's power curve at the time of manufacture (refer to...). Figure 6 , Figure 6 The power curves for different detection probabilities are shown in this embodiment. Only the curves that satisfy the 80% detection probability are plotted.

[0019] In this embodiment, during S2, when the UAV is hovering once, it can detect one or more observation points within a flight path section.

[0020] It should be noted that the simulation system in this solution, both the system itself and the simulation logic, are existing technologies.

[0021] In this embodiment, the simulation system simulates the echo characteristic information of the simulated target at each observation point, including the distance from the simulated target to the radar, the echo intensity from the simulated target to the radar, the echo velocity from the simulated target to the radar, the radar target cross-section (RCS), and the energy change caused by the distance. For example, simulating the distance from the target to the radar by adjusting the simulation. The system's delay is implemented, and the delay time is calculated using the following formula: Where R is the distance from the simulated target to the radar, r is the distance from the simulation system to the radar, tm is the processing and forwarding time of the target simulation system after receiving the radar signal, c is the speed of light in a vacuum, Δt target is the time difference from the transmission of the radar wave signal to the receipt of the simulated target feedback signal, and Δt simulation is the time difference from the transmission of the radar wave signal to the receipt of the feedback signal from the UAV carried by the simulation system. For example, the echo velocity from the simulated target to the radar is achieved by adjusting the output power of the simulation system. The formula for calculating the adjusted output power is as follows: In the formula, Pt is the radar transmit power, Gt is the main lobe antenna gain, Gtsim is the target simulation system antenna gain, L1 is the distance-dependent attenuation from the target to the radar, and L2 is the distance-dependent attenuation from the simulator to the radar. For example, simulating the echo velocity from a target to the radar is achieved by adjusting the frequency offset of the simulation system. The formula for calculating the frequency offset is: In the formula, V is the simulated speed of the aircraft target; λ is the radar signal wavelength; β is the angle between the simulated target's direction of motion and the radial direction of the target and the radar. For example, the energy changes caused by the radar target's radar cross-section (RCS) and distance can be achieved by adjusting the power of the target simulation system; For details on the adjustment method, please refer to Figure 7 The target RCS is simulated through power simulation. Based on the known installation distance, radar radiated power, antenna gain, simulation distance, simulation system antenna gain, and the RCS of the target being simulated, the power of the output signal of the target simulation system and the echo signal of the target being simulated reaching the radar aperture is made equal through formula derivation. According to the radar equations, the echo power obtained by radar illuminating a real target can be expressed as: For a target within the simulated radar main lobe range, the power of the echo signal reflected by the target is modulated using equivalent modulation. The radar's received RCS is... The target reflection power can be expressed as: make The equivalent ERP is obtained as follows: In the formula, r is the distance from the simulation system to the radar, R is the distance from the simulated target to the radar, Pt is the radar transmit power, Gt is the transmit gain of the main lobe antenna, Gr is the receive gain of the main lobe antenna; Ptsim is the transmit power of the target simulation system, Gtsim is the antenna gain of the target simulation system, L1 is the distance-related attenuation from the target to the radar, and L2 is the distance-related attenuation from the simulator to the radar. The simulated echo power output by the simulation system is calculated for a given RCS value and distance R.

[0022] It should be noted that, for reference Figure 4 In this invention, when flying close to the ground radar at the corresponding altitude level with the starting point or corresponding auxiliary point as the initial position, it should theoretically be flying radially close to the ground radar along the corresponding elevation angle with the starting point or corresponding auxiliary point as the initial position. However, the difference between the two methods is not significant, so this invention makes an approximation. In addition, when generating the signal of the simulated target using the simulation system, radial flight simulation and back-to-ground flight simulation are also performed by approaching the ground radar along the corresponding elevation angle. At this time, it is also simulated as flying close to the ground radar at the corresponding altitude level. This can reduce the calculation and the workload of the entire detection.

[0023] (Comparative Example) To verify the effectiveness of the simulated flight test verification method of the present invention, the optimized ground radar detection range index simulated flight test verification method of the present invention is compared with the existing traditional actual aircraft flight test verification method and the conventional simulated flight test method in terms of flight path design, sample collection, and test duration, as shown in Table 1.

[0024] Table 1. Comparison of the optimized ground radar detection range index simulation test verification method with other methods. As can be seen from Table 1, the optimized ground radar detection range index simulation flight verification method has significant advantages over the other two methods in terms of test target, test duration, test data sample size, test cost, and test risk.

[0025] The above embodiments only illustrate preferred implementation methods, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of this invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this invention, and these all fall within the protection scope of this invention.

Claims

1. An optimized method for simulating and verifying the detection range index of ground radar, characterized in that: Includes the following steps: S1. Based on the radar's factory parameters, obtain the power curve at the time of manufacture, thereby determining the farthest distance at which the detection probability can be satisfied at the time of manufacture for each altitude level. S2. Conduct flight measurements; S21. Select a height layer and determine the farthest horizontal distance that can satisfy the detection probability when the height layer is manufactured; use the height layer as the vertical axis and the corresponding farthest horizontal distance that can satisfy the detection probability when the height layer is manufactured as the horizontal axis to find the starting point. S22. Construct the first flight segment and calculate the first elevation angle; Starting from the starting point, the X-distance of flight close to the radar at the altitude level is the first segment of the flight path. Taking the starting point as the initial position, the point where the aircraft is located after flying X / 2 distances close to the radar at the altitude layer is the first auxiliary point. The elevation angle from the first auxiliary point to the radar is calculated, which is referred to as the first elevation angle. S23, The simulation system rises to a certain height; There is an airborne platform at a certain distance from the radar. The airborne platform includes a drone, which is equipped with a simulation system. The drone lifts the simulation system up and hovers together. After lifting and hovering, the elevation angle of the drone relative to the radar is the same as the first elevation angle. S24. In the simulation system, set the simulated target RCS, target heading, and flight speed; Based on the first elevation angle and the horizontal distance of the first auxiliary point relative to the radar, the simulated target RCS, target heading, and flight speed are set in the simulation system. The size of the simulated target RCS is manually set according to the horizontal distance from the first auxiliary point to the radar. The target heading is radial or rearward flight at the altitude layer with the first auxiliary point as the starting point. The flight speed is manually set according to the first elevation angle and the horizontal distance of the first auxiliary point relative to the radar. S25: The radar generates transmit and receive signals, and the simulation system generates multiple simulated target signals; In the first segment of the flight path, there are multiple observation points at different locations. Multiple simulated target signals are generated by the simulation system. The simulated target signals are the signals of the simulated aircraft flying to the corresponding observation points. The radar detects whether these signals can be detected. The number of detected signals / the number of observation points = the detection probability of the first segment of the flight path. S26. Construct the second segment of the flight path, and then complete the detection. The first auxiliary point is defined as the first auxiliary point flying X distances closer to the radar along the altitude layer, and the segment corresponding to this X distance is defined as the second flight path segment; the point where the first auxiliary point is located after flying X / 2 distances closer to the radar along the altitude layer is defined as the second auxiliary point, and the elevation angle of the second auxiliary point relative to the radar is calculated, i.e., the second elevation angle. There is an overlapping area between the second segment of the route and the first segment of the route; Using the second elevation angle as the standard for the UAV's ascent altitude, and setting the corresponding simulated target RCS, target heading, and flight speed based on the second elevation angle and the horizontal distance of the second auxiliary point relative to the radar, the detection of the second flight path section is completed in accordance with the method of S23~S25. S27. Following the method in S26, complete the detection of multiple flight path sections until the elevation angle of the corresponding auxiliary point reaches the required value of 35°. S28. After all flight path intervals corresponding to the altitude layer have been detected, plot the relationship between the detection probability and the horizontal distance with the horizontal distance of each auxiliary point relative to the radar as the abscissa and the detection probability of the corresponding flight path interval as the ordinate. Based on the plot, find the detection probability that meets the technical requirements and find the maximum detection range of the radar at this altitude layer. S29. Select another new altitude layer and, following the steps in S21 to S28, complete the detection of the corresponding flight path section to find the maximum detection range of the radar at that altitude layer. This allows us to obtain the maximum detection range of the radar at various altitude levels; S3. Based on the maximum detection range of the radar at each altitude level obtained in S2, redraw the radar's power curve to complete the verification and calibration of the radar's power curve at the time of manufacture.

2. The optimized ground radar detection range index simulation flight verification method according to claim 1, characterized in that: In S2, during a single ascent and hovering period, the UAV can detect one or more observation points within a flight path section.

3. The optimized ground radar detection range index simulation flight verification method according to claim 1, characterized in that: The simulation system simulates the echo characteristics of simulated targets at various observation points, including the distance from the simulated target to the radar, the echo intensity from the simulated target to the radar, and the echo velocity from the simulated target to the radar.

4. The optimized ground radar detection range index simulation flight verification method according to claim 3, characterized in that: The distance from the simulated target to the radar is achieved by adjusting the delay of the simulation system. The formula for calculating the delay is as follows: Where R is the distance from the simulated target to the radar, r is the distance from the simulation system to the radar, tm is the processing and forwarding time of the target simulation system after receiving the radar signal, c is the speed of light in a vacuum, Δt target is the time difference from the transmission of the radar wave signal to the receipt of the simulated target feedback signal, Δt simulation is the time difference from the transmission of the radar wave signal to the receipt of the feedback signal from the UAV carried by the simulation system, and Δt is the delay time of the simulation system.

5. The optimized ground radar detection range index simulation flight verification method according to claim 3, characterized in that: The simulated target's echo intensity to the radar is achieved by adjusting the output power Ptsim of the simulation system. The formula for calculating the adjusted output power Ptsim is as follows: In the formula, Pt is the radar transmit power, Gt is the main lobe antenna gain, r is the distance from the simulation system to the radar, R is the distance from the simulated target to the radar, Gtsim is the antenna gain of the target simulation system, L1 is the distance-related attenuation from the target to the radar, and L2 is the distance-related attenuation from the simulator to the radar.

6. The optimized ground radar detection range index simulation flight verification method according to claim 3, characterized in that: The simulated target's echo velocity to the radar is achieved by adjusting the frequency offset of the simulation system. The formula for calculating the frequency offset is as follows: In the formula, V is the simulated speed of the aircraft target; λ is the radar signal wavelength; and β is the angle between the simulated target's direction of motion and the radial direction of the target and the radar.

7. The optimized ground radar detection range index simulation flight verification method according to claim 3, characterized in that: The echo characteristic information also includes energy changes caused by the radar target's cross-sectional area and distance, which are achieved by adjusting the power of the target simulation system; wherein, the radar target's cross-sectional area is represented by RCS.

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