Radar calibration system and method based on GNSS

Abstract

The invention belongs to the technical field of radar calibration, and discloses a GNSS-based radar calibration system and method. According to the invention, the unmanned aerial vehicle carries GNSS equipment to dynamically fly, the three-dimensional space is segmented in combination with rays, and automatic obstacle avoidance and calibration point lifting are realized, so that an electromagnetic transmission channel is ensured to be barrier-free and cover the full range of radar beams, the integrity and adaptability of the calibration space are improved, and manual intervention is reduced. By integrating temperature, humidity, electromagnetic interference intensity and channel length, through finite difference conjoint analysis and a historical data mapping model, multivariable environmental influence compensation is realized, the problem of single environmental parameter compensation is solved, and systematic errors in a complex environment are remarkably reduced. Through cooperation of the environmental influence calibration module and the fixed-point test module, environmental errors are compensated first, then calibration results are verified, a closed-loop calibration process is formed, the number of times of repeated calibration is reduced, and the real-time performance of the system is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar calibration, and relates to a radar calibration system and method based on GNSS. Background Art

[0002] With the rapid development of modern technology, radar plays a crucial role in many fields such as meteorological monitoring, aerospace, traffic control, and national defense. The accuracy of radar directly affects the effective development of related operations and the accuracy of decision-making in these fields. During the operation of radar, it will be affected by various factors, making it difficult to effectively guarantee its accuracy. Therefore, radar calibration operations are required.

[0003] GNSS, namely the Global Navigation Satellite System, in terms of data acquisition and processing, the existing technology has a low accuracy in obtaining the position information of calibration points, making it difficult to meet the calibration requirements of modern radars, resulting in poor calibration effects. Therefore, the research on radar calibration technology based on GNSS is of great significance.

[0004] There are also technical researches on radar calibration in the existing technical solutions, but there are still many defects: on the one hand, traditional radar calibration relies on fixed calibration points or static trajectories set manually, and cannot dynamically adapt to terrain obstacles and changes in radar beam coverage, resulting in calibration blind spots or redundancy. On the other hand, the existing technology mostly uses single environmental parameters for compensation and lacks the ability of joint analysis of multiple variables, resulting in the accumulation of calibration errors. Summary of the Invention

[0005] In view of this, to solve the problems raised in the above background art, a radar calibration system and method based on GNSS are proposed.

[0006] The object of the present invention can be achieved by the following technical solutions: In the first aspect of the present invention, a radar calibration system based on GNSS is provided, including: a regional calibration and positioning module that divides a monitoring area based on the geographical coordinates of the target radar device and locates the corresponding calibration points, generates a dynamic calibration trajectory according to the radar beam coverage range and terrain obstacle data, and flies a UAV carrying a GNSS signal receiving device along the dynamic calibration trajectory to obtain the monitoring position coordinates of the UAV in the radar coordinate system and the absolute position coordinates in the geographical position coordinate system in real time.

[0007] An environmental impact calibration module that integrates an environmental sensor network to obtain the environmental information of each monitoring area, and performs environmental impact compensation by combining the monitoring position coordinates and absolute position coordinates of each calibration point to perform environmental impact calibration.

[0008] The fixed-point test and calibration module performs fixed-point accuracy tests on the calibration points of the radar device after environmental impact calibration to obtain the radar echo attenuation values and coordinate offsets of each calibration point, generates fixed-point test and calibration requirements, and performs fixed-point test and calibration accordingly.

[0009] The second aspect of the present invention provides a GNSS-based radar calibration method, including: dividing a monitoring area based on the geographical coordinates of the target radar device and positioning corresponding calibration points, and generating a dynamic calibration trajectory based on the radar beam coverage range and terrain obstacle data.

[0010] The unmanned aerial vehicle (UAV) carrying the GNSS signal receiving device flies along the dynamic calibration trajectory to obtain the monitored position coordinates of the UAV in the radar coordinate system and the absolute position coordinates in the geographical position coordinate system in real time.

[0011] The integrated environmental sensor network obtains the environmental information of each monitoring area, and performs environmental impact compensation by combining the monitored position coordinates and absolute position coordinates of each calibration point to perform environmental impact calibration.

[0012] Perform fixed-point accuracy tests on the calibration points of the radar device after environmental impact calibration to obtain the radar echo attenuation values and coordinate offsets of each calibration point, generate fixed-point test and calibration requirements, and perform fixed-point test and calibration accordingly.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention uses a UAV carrying a GNSS device to fly dynamically, combines ray segmentation of the three-dimensional space and automatically avoids obstacles to lift the calibration points, ensuring that the electromagnetic transmission channel is unobstructed, covering the entire range of the radar beam, improving the integrity and adaptability of the calibration space, and reducing manual intervention.

[0014] (2) The present invention realizes multi-variable environmental impact compensation by integrating temperature, humidity, electromagnetic interference intensity and channel length through finite difference joint analysis and historical data mapping models, solves the problem of single environmental parameter compensation, and significantly reduces the systematic error in complex environments.

[0015] (3) The present invention coordinates the environmental impact calibration module and the fixed-point test module, compensates the environmental error first and then verifies the calibration result, forms a closed-loop calibration process, reduces the number of repeated calibrations, and improves the real-time performance of the system. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 This is a schematic diagram of the connection of each module of the system of the present invention.

[0018] Figure 2 This is a schematic diagram of the implementation steps of the method of the present invention.

[0019] Figure 3 This is a cross-sectional view of the monitoring space area corresponding to an embodiment provided by the present invention.

[0020] Figure 4 This is a schematic diagram of the fixed-point movement operation corresponding to an embodiment provided by the present invention.

[0021] Reference numerals: 1—the position coordinates of the target radar device, 2—the monitoring space area, 3—the calibration point, 4—the direction of the fixed-point movement operation, 5—the position points corresponding to the interval movement distance. Detailed implementation manners

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0023] Please refer to Figure 1 As shown, the first aspect of the present invention provides a GNSS-based radar calibration system, including a regional calibration and positioning module, an environmental impact calibration module, and a fixed-point test calibration module, wherein the regional calibration and positioning module is connected to the environmental impact calibration module, and the environmental impact calibration module is connected to the fixed-point test calibration module.

[0024] The regional calibration and positioning module is used to divide the monitoring area based on the geographical coordinates of the target radar device and locate the corresponding calibration points, generate a dynamic calibration trajectory according to the radar beam coverage range and terrain obstacle data, fly along the dynamic calibration trajectory by a drone carrying a GNSS signal receiving device, and obtain the monitoring position coordinates of the drone in the radar coordinate system and the absolute position coordinates in the geographical position coordinate system in real time.

[0025] In a preferred embodiment of the present invention, the specific method for generating the dynamic calibration trajectory is as follows: a monitoring space area is constructed based on the position coordinates of the target radar device and the radar beam coverage range, and the position coordinates of the target radar device are located at the center point of the projection area of the monitoring space area on the horizontal plane.

[0026] In one embodiment, as Figure 3As shown in the figure, the monitoring space area is constructed as follows: taking the position coordinates of the target radar device as the center point, a semi-circular area is constructed with the maximum value of the radar beam coverage range as the radius, and this area is denoted as the monitoring space area.

[0027] Based on equally spaced angles, several rays are emitted from the position coordinates of the target radar device in all directions. Taking the rays as dividing lines, several dividing planes are formed perpendicular to the horizontal plane where the rays are located. Then, the monitoring space area is divided into several monitoring areas, and the three-dimensional space center points of each monitoring area are denoted as calibration points.

[0028] Connect the position coordinates of each calibration point with the position coordinates of the target radar device to obtain several electromagnetic transmission channels. Use a three-dimensional scanning device to obtain the three-dimensional distribution data of each channel, and identify whether there are obstacles in each electromagnetic transmission channel. If there are obstacles, raise the calibration point of the corresponding monitoring area by a preset adjustment height value in the vertical direction, reconstruct the electromagnetic transmission channel and perform obstacle identification until there are no obstacles in the electromagnetic transmission channels corresponding to each calibration point, and then determine each calibration point.

[0029] It should be noted that in the present invention, the UAV is equipped with a GNSS device to fly dynamically, combines ray segmentation of the three-dimensional space and automatically avoids obstacles and raises the calibration points to ensure that the electromagnetic transmission channels are obstacle-free, cover the full range of the radar beam, improve the integrity and adaptability of the calibration space, and reduce manual intervention.

[0030] Connect each calibration point in sequence to generate a dynamic calibration trajectory.

[0031] It should be added that it is crucial to reasonably set the preset adjustment height value. If the value is too small, it may not be able to completely avoid obstacles, resulting in the radar wave propagation still being affected and causing deviations in the calibration results. If the value is too large, the position of the calibration point will deviate from the ideal state, which will also affect the calibration accuracy, and may increase the calibration cost and complexity. This value needs to comprehensively consider factors such as the radar beam characteristics, the distribution characteristics of terrain obstacles, and the actual calibration accuracy requirements to ensure the effectiveness and accuracy of the calibration work.

[0032] In an embodiment, the connection method of the calibration points corresponding to the dynamic calibration trajectory is: taking the calibration point closest to the target radar device as the starting point, connecting each calibration point counterclockwise to form a dynamic calibration trajectory.

[0033] The environmental impact calibration module is used to integrate the environmental sensor network to obtain the environmental information of each monitoring area, and perform environmental impact compensation in combination with the monitoring position coordinates and absolute position coordinates of each calibration point to perform environmental impact calibration.

[0034] In a preferred embodiment of the present invention, the specific steps for obtaining the environmental information of each monitoring area are as follows: Calculate the attenuation gradient of each electromagnetic transmission channel based on the electromagnetic propagation model, and dynamically set environmental monitoring points.

[0035] In a preferred embodiment, the entire monitoring area is partitioned according to the attenuation gradients of each electromagnetic transmission channel calculated based on the electromagnetic propagation model, and the areas with the attenuation gradient change rate within a certain specific interval are classified into one category. Specifically, the areas where the attenuation gradient changes by 0.1 - 0.3 dB per kilometer are divided into one partition. The center point of each partition is used as an environmental monitoring point.

[0036] It should be explained that the advantage of dynamically setting environmental monitoring points is that it can obtain the environmental information of each monitoring area more accurately. Since the attenuation gradients of electromagnetic transmission channels in different areas are different, setting monitoring points fixedly may not comprehensively and accurately reflect the impact of environmental changes on the radar. By dynamically setting, monitoring points can be increased in key areas or areas with large changes according to the differences in attenuation gradients, and appropriately reduced in stable areas, improving the pertinence and effectiveness of environmental information collection, and thus providing more accurate data support for subsequent implementation of environmental impact compensation and calibration, and enhancing the accuracy of radar calibration.

[0037] The integrated environmental sensor network obtains the temperature, humidity, and electromagnetic interference intensity of each environmental monitoring point, and simultaneously obtains the length of each electromagnetic transmission channel and the distance between adjacent environmental monitoring points.

[0038] The temperature, humidity, and electromagnetic interference intensity of adjacent environmental monitoring points are combined with the corresponding distances for multivariate finite difference joint analysis to obtain the temperature gradient, humidity gradient, and monitored electromagnetic interference intensity of each electromagnetic transmission channel.

[0039] It should be noted that the reasons for selecting temperature, humidity, and electromagnetic interference intensity for analysis are as follows: 1. Affect the propagation of radar waves: Temperature and humidity will change the atmospheric refractive index and affect the propagation path of radar waves. The changes in temperature gradient and humidity gradient will cause different refractive indices in different regions of the atmosphere, making the radar waves bend during propagation, and thus affecting the accurate measurement of the target position by the radar. For example, in the case of uneven vertical distribution of temperature and humidity, an atmospheric duct phenomenon may be formed, resulting in abnormal propagation of radar waves and detection errors.

[0040] 2. Cause signal attenuation and interference: An increase in humidity will increase the water vapor content in the atmosphere. Water vapor has an absorption and scattering effect on radar waves, resulting in radar signal attenuation and affecting the radar's ability to detect targets. When the electromagnetic interference intensity is too high, it will interfere with the echo signal received by the radar, submerge the signal in noise, reduce the signal-to-noise ratio of the radar, and cause the radar to be unable to accurately detect the target echo or misidentify information such as the distance, speed, and angle of the target.

[0041] 3. Impact on radar equipment performance: These factors can also affect the performance of the radar equipment itself. For example, humidity may cause water vapor to condense on the surface of the radar equipment, affecting the electrical performance of the equipment and accelerating the corrosion and aging of electronic components; electromagnetic interference may penetrate into the control system and data processing system of the radar, resulting in problems such as malfunction, data error, or system crash, seriously affecting the accuracy and reliability of the radar.

[0042] Preferably, the specific analysis methods for the temperature gradient, humidity gradient, and monitored electromagnetic interference intensity are as follows: Calculate the ratio of the temperature and humidity of adjacent environmental monitoring points to the corresponding spacing to obtain the temperature gradient and humidity gradient of each adjacent environmental monitoring point, and then calculate the average value respectively to obtain the temperature gradient and humidity gradient of each electromagnetic transmission channel.

[0043] Calculate the average value of the electromagnetic interference intensity of each environmental monitoring point to obtain the monitored electromagnetic interference intensity of the electromagnetic transmission channel.

[0044] In a preferred embodiment of the present invention, the specific analysis method for performing environmental impact compensation is as follows: Construct a mapping relationship model between environmental parameters and radar position coordinate deviation based on historical data records.

[0045] Match the temperature gradient, humidity gradient, and monitored electromagnetic interference intensity with the above mapping relationship model respectively to obtain the temperature parameter impact deviation, humidity parameter impact deviation, and electromagnetic interference intensity impact deviation corresponding to each electromagnetic transmission channel. Then, fuse the contribution weights of the temperature gradient, humidity gradient, and electromagnetic interference intensity through the weighted least squares method to calculate the environmental impact compensation amount of each electromagnetic transmission channel.

[0046] It should be noted that in the GNSS-based radar calibration system, the contribution weights of the temperature gradient, humidity gradient, and electromagnetic interference intensity are used to measure the proportion of these three environmental factors in the process of affecting radar performance. Usually, the weights are determined based on a large amount of historical data and experimental results. First, analyze the relationship between each environmental factor and the radar position coordinate deviation in the historical data to judge the magnitude of the influence of each factor. Control variable experiments can also be carried out in the laboratory or actual scenarios, respectively changing the temperature gradient, humidity gradient, and electromagnetic interference intensity, observing the changes in radar performance, and determining the weights based on the degree of change. For example, multiple experiments show that in a certain frequency band, the change in electromagnetic interference intensity has a great impact on the radar ranging deviation, and its weight will be relatively high.

[0047] In a preferred embodiment, the calculation method of the environmental impact compensation amount is as follows: Sum the temperature parameter impact deviation, humidity parameter impact deviation, and electromagnetic interference intensity impact deviation according to the weights to obtain the environmental impact compensation amount.

[0048] Calculate the position deviation between the monitoring position coordinates and the absolute position coordinates of each calibration point to obtain the actual monitoring deviation of each calibration point, and then compare it with the environmental impact compensation amount of the corresponding electromagnetic transmission channel to obtain the deviation after environmental impact compensation in the corresponding monitoring area.

[0049] Preferably, calculate the difference between the actual monitoring deviation of each calibration point and the environmental impact compensation amount to obtain the deviation after environmental impact compensation in the corresponding monitoring area.

[0050] Perform environmental impact calibration based on the deviation after environmental impact compensation in each monitoring area and the length of each electromagnetic transmission channel.

[0051] In a preferred embodiment of the present invention, the specific method for constructing the mapping relationship model between environmental parameters and radar position coordinate deviations based on historical data records is as follows: Extract historical data records, obtain the radar monitoring distance and absolute geographical distance corresponding to each record, and at the same time obtain the corresponding environmental data. Calculate the average value of the radar position coordinate deviations corresponding to the same environmental parameters as the radar coordinate position deviation mapped by this environmental parameter, and then construct the mapping relationship model between environmental parameters and radar position coordinate deviations based on this. In the model, each environmental data type corresponds one-to-one to each environmental parameter and radar position coordinate deviation.

[0052] In a preferred embodiment of the present invention, the specific method for performing environmental impact calibration is as follows: Based on the deviation after environmental impact compensation in each monitoring area and the length of the corresponding electromagnetic transmission channels, perform normalized deviation coefficient analysis to obtain the radar distance monitoring deviation coefficient of each monitoring area, and then input it into the radar system to perform environmental impact calibration.

[0053] Preferably, calculate the ratio of the deviation after environmental impact compensation in each monitoring area to the length of the corresponding electromagnetic transmission channels to obtain the radar distance monitoring deviation coefficient of each monitoring area.

[0054] Preferably, the significance of the radar distance monitoring deviation coefficient is as follows: 1. Evaluate the accuracy of radar ranging: This coefficient intuitively reflects the deviation degree of radar distance monitoring in different monitoring areas after considering environmental impact compensation. The closer the coefficient is to 0, the higher the accuracy of radar distance monitoring; the farther the coefficient deviates from 0, the greater the error of radar distance monitoring, which can be used to quickly evaluate the ranging performance of the radar in different areas.

[0055] 2. Calibration basis: As a calibration parameter, it is input into the radar system to correct the radar distance monitoring data. By adjusting the algorithm or parameters inside the radar system, the measured distance data is compensated according to the deviation coefficient, improving the accuracy of radar distance monitoring and ensuring that the radar can measure the target distance more accurately in different environments.

[0056] It should be noted that the present invention realizes multi-variable environmental impact compensation by integrating temperature, humidity, electromagnetic interference intensity and channel length through finite difference joint analysis and historical data mapping model, solves the problem of single environmental parameter compensation, and significantly reduces the systematic error in complex environments.

[0057] The fixed-point test calibration module is used to perform fixed-point accuracy tests on the radar device after environmental impact calibration to obtain the radar echo attenuation values and coordinate offsets of each calibration point, and generate fixed-point test calibration requirements, and perform fixed-point test calibration accordingly.

[0058] In a preferred embodiment of the present invention, the specific steps for performing the fixed-point accuracy test of the calibration points are as follows: Please refer to Figure 4 As shown, based on the preset moving distance and direction, the UAV is equipped with a GNSS signal receiving device to perform a number of fixed-point moving operations at each calibration point.

[0059] Based on the GNSS signal receiving device, obtain the actual moving distance of each fixed-point moving operation, and at the same time use the radar device to obtain the monitored moving distance of each fixed-point moving operation.

[0060] Compare and fuse the actual moving distances and monitored moving distances of each fixed-point moving operation at each calibration point to obtain the coordinate offsets of each calibration point.

[0061] Preferably, calculate the average value of the actual moving distances and monitored moving distances of each fixed-point moving operation at each calibration point to obtain the coordinate offsets of each calibration point.

[0062] Obtain the measured signal attenuation values of each fixed-point moving operation at each calibration point, and then perform data fusion analysis to obtain the measured signal attenuation values of each calibration point.

[0063] Preferably, calculate the average value of the measured signal attenuation values of each fixed-point moving operation at each calibration point to obtain the measured signal attenuation values of each calibration point.

[0064] In a preferred embodiment of the present invention, the specific method for generating the fixed-point test calibration requirements is as follows: Compare the coordinate offsets and measured signal attenuation values of each calibration point with the corresponding reference coordinate offset thresholds and reference signal attenuation value thresholds of each monitoring area to obtain the judgment results on whether fixed-point test calibration is required for each monitoring area.

[0065] Specifically, if the coordinate offset of a certain calibration point is greater than the reference coordinate offset threshold or the measured signal attenuation value is greater than the reference signal attenuation value threshold, it is judged that the corresponding monitoring area needs to perform fixed-point test calibration; otherwise, it is judged that fixed-point test calibration is not required.

[0066] It should be noted that the reference coordinate offset threshold refers to a boundary value of the coordinate offset preset during the radar calibration process. When conducting a fixed-point accuracy test on the calibration points, the coordinate offsets of each obtained calibration point are compared with it. If the actual coordinate offset exceeds this threshold, it indicates that there may be a large error in the coordinate measurement of the radar at this calibration point, and fixed-point test calibration is required to correct the coordinate deviation. This threshold is not fixed, but is obtained through weighted correction and fusion calculation by combining the distances between the calibration points corresponding to each monitoring area and the radar device with the preset basic coordinate offset threshold. Due to factors such as different distances from the radar in different monitoring areas, their reference coordinate offset thresholds will also vary.

[0067] It should be noted that the reference signal attenuation value threshold is a reference boundary set for the attenuation degree of the radar echo signal. In the fixed-point accuracy test, when the measured signal attenuation values of each calibration point are compared with this threshold, if the measured signal attenuation value exceeds the threshold range, it means that the attenuation of the radar echo signal may affect the accurate detection of the target by the radar, and fixed-point test calibration is required. Similar to the reference coordinate offset threshold, it is also obtained through weighted correction and fusion calculation by combining the threshold influence distance, the preset basic signal attenuation value threshold, and adding the influence analysis of the environmental attenuation coefficient. Considering the environmental attenuation coefficient is because environmental factors will affect the attenuation of radar signals, which can more accurately reflect the reasonable range of radar signal attenuation in different environments.

[0068] If it is determined that fixed-point test calibration needs to be performed, then further identify whether the specific test calibration requirement is signal strength compensation or distance identification correction.

[0069] Specifically, if the coordinate offset is greater than the reference coordinate offset threshold, identify that the specific test calibration requirement is distance identification correction; if the measured signal attenuation value is greater than the reference signal attenuation value threshold, identify that the specific test calibration requirement is signal strength compensation.

[0070] It should be noted that the specific test calibration requirement can be one or both of signal strength compensation and distance identification correction.

[0071] It should be noted that the purpose of identifying the specific test calibration requirement: on the one hand, it can make the calibration work more targeted and improve the calibration efficiency. There are different problems such as signal strength and distance identification in radar calibration. If calibrated generally, it will waste resources and it is difficult to solve the fundamental problem. After clarifying whether it is a signal strength compensation or distance identification correction requirement, calibration can be directly targeted at the problem, saving time and effort.

[0072] On the other hand, it can improve the accuracy of radar calibration. Different calibration requirements are processed differently. By accurately positioning the requirements and taking corresponding measures, the radar measurement error can be effectively reduced. For example, if it is accurately identified as a distance identification and correction requirement, by optimizing the radar distance measurement algorithm, calibrating the distance measurement reference, etc., the radar can measure the target distance more accurately.

[0073] In a preferred embodiment of the present invention, the specific analysis method for the reference coordinate offset threshold and the reference signal attenuation value threshold corresponding to each monitoring area is as follows: Denote the distance between the calibration points corresponding to each monitoring area and the radar device as the threshold influence distance, and then perform weighted correction and fusion calculation in combination with the preset coordinate offset threshold and signal attenuation value threshold to obtain the reference coordinate offset threshold and the reference signal attenuation value threshold corresponding to each monitoring area.

[0074] It should be noted that the present invention forms a closed-loop calibration process through the cooperation of the environmental impact calibration module and the fixed-point test module, compensates for environmental errors first and then verifies the calibration results, reduces the number of repeated calibrations, and improves the real-time performance of the system.

[0075] Please refer to Figure 2 As shown, the second aspect of the present invention provides a GNSS-based radar calibration method, including: dividing monitoring areas based on the geographical coordinates of the target radar device and positioning the corresponding calibration points, and generating a dynamic calibration trajectory based on the radar beam coverage range and terrain obstacle data.

[0076] The drone is equipped with a GNSS signal receiving device and flies along the dynamic calibration trajectory to obtain the monitoring position coordinates of the drone in the radar coordinate system and the absolute position coordinates in the geographical position coordinate system in real time.

[0077] Integrate the environmental sensor network to obtain the environmental information of each monitoring area, and perform environmental impact compensation in combination with the monitoring position coordinates and absolute position coordinates of each calibration point to perform environmental impact calibration.

[0078] After the environmental impact calibration of the radar device, perform a fixed-point accuracy test on the calibration points to obtain the radar echo attenuation value and coordinate offset of each calibration point, and generate a fixed-point test calibration requirement, and perform fixed-point test calibration accordingly.

[0079] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A GNSS-based radar calibration system, characterized in that: include: The regional calibration and positioning module divides the monitoring area and locates the corresponding calibration points based on the geographic coordinates of the target radar device, generates a dynamic calibration trajectory based on the radar beam coverage and terrain obstacle data, and uses the drone equipped with a GNSS signal receiving device to fly along the dynamic calibration trajectory to obtain the monitoring position coordinates of the drone in the radar coordinate system and the absolute position coordinates in the geographic coordinate system in real time; The environmental impact calibration module integrates the environmental sensor network to obtain the environmental information of each monitoring area, and performs environmental impact compensation based on the monitoring position coordinates and absolute position coordinates of each calibration point to perform environmental impact calibration; The fixed-point test calibration module performs a calibration point accuracy test on the radar equipment after environmental impact calibration to obtain the radar echo attenuation value and coordinate offset of each calibration point, and generates a fixed-point test calibration requirement, based on which the fixed-point test calibration is performed.

2. The GNSS-based radar calibration system according to claim 1, characterized in that: The specific method of generating the dynamic calibration trajectory is as follows: Constructing a monitoring space region based on the position coordinates of the target radar device and the radar beam coverage, wherein the position coordinates of the target radar device are located at the center point of the projection area of ​​the monitoring space region onto the horizontal plane; Based on the equally spaced angles, a number of rays are emitted from the coordinates of the target radar device to the surrounding areas, and a number of dividing planes are formed perpendicular to the horizontal plane where the rays are located, thereby dividing the monitoring space area into a number of monitoring areas, and the three-dimensional space center point of each monitoring area is recorded as a calibration point; Connect each calibration point with the coordinates of the position of the target radar device to obtain a number of electromagnetic transmission channels, use a three-dimensional scanning device to obtain the three-dimensional distribution data of each channel, identify whether there are obstacles in each electromagnetic transmission channel, and if so, lift the calibration point of the corresponding monitoring area in the vertical direction by a preset adjustment height value, reconstruct the electromagnetic transmission channel and identify obstacles, until there are no obstacles in the electromagnetic transmission channel corresponding to each calibration point, and then determine each calibration point; Connect the calibration points in sequence to generate a dynamic calibration trajectory.

3. The GNSS-based radar calibration system according to claim 1, characterized in that: The specific steps of obtaining the environmental information of each monitoring area are as follows: Calculate the attenuation gradient of each electromagnetic transmission channel based on the electromagnetic propagation model and dynamically set the environmental monitoring points; The integrated environmental sensor network obtains the temperature, humidity and electromagnetic interference intensity of each environmental monitoring point, and also obtains the length of each electromagnetic transmission channel and the distance between adjacent environmental monitoring points; The temperature, humidity and electromagnetic interference intensity of adjacent environmental monitoring points are combined with the corresponding spacing to perform a multivariate finite difference joint analysis to obtain the temperature gradient, humidity gradient and monitoring electromagnetic interference intensity of each electromagnetic transmission channel.

4. The GNSS-based radar calibration system according to claim 3, characterized in that: The specific analysis method of the execution environment impact compensation is as follows: Construct a mapping relationship model between environmental parameters and radar position coordinate deviations based on historical data records; The temperature gradient, humidity gradient and monitored electromagnetic interference intensity are matched with the above-mentioned mapping relationship model to obtain the temperature parameter influence deviation, humidity parameter influence deviation and electromagnetic interference intensity influence deviation corresponding to each electromagnetic transmission channel. The contribution weights of the temperature gradient, humidity gradient and electromagnetic interference intensity are integrated by weighted least squares method to calculate the environmental impact compensation amount of each electromagnetic transmission channel; The monitoring position coordinates and the absolute position coordinates of each calibration point are calculated for position deviation to obtain the actual monitoring deviation of each calibration point, and then compared with the environmental impact compensation amount of the corresponding electromagnetic transmission channel to obtain the environmental impact compensation deviation of the corresponding monitoring area; Environmental impact calibration is performed based on the deviation after environmental impact compensation in each monitoring area and the length of each electromagnetic transmission channel.

5. The GNSS-based radar calibration system according to claim 4, characterized in that: The specific method of constructing the mapping relationship model between environmental parameters and radar position coordinate deviations based on historical data records is as follows: Extract historical data records, obtain the radar monitoring distance and absolute geographical distance corresponding to each record, and obtain the corresponding environmental data at the same time. Calculate the average of the radar position coordinate deviations corresponding to the same environmental parameters as the radar coordinate position deviation mapped by the environmental parameters, and then build a mapping relationship model between environmental parameters and radar position coordinate deviations based on this. In the model, each environmental data type corresponds to each environmental parameter and radar position coordinate deviation one by one.

6. The GNSS-based radar calibration system according to claim 5, characterized in that: The specific method of performing environmental impact calibration is as follows: The normalized deviation coefficient analysis is performed based on the deviation after environmental impact compensation of each monitoring area and the length of each corresponding electromagnetic transmission channel to obtain the radar distance monitoring deviation coefficient of each monitoring area, which is then input into the radar system to perform environmental impact calibration.

7. The GNSS-based radar calibration system according to claim 1, characterized in that: The specific steps of performing the calibration point fixed-point accuracy test are as follows: Based on the preset moving distance and direction, the drone is equipped with a GNSS signal receiving device to perform several fixed-point moving operations at each calibration point; The actual moving distance of each fixed-point moving operation is obtained based on the GNSS signal receiving device, and the monitoring moving distance of each fixed-point moving operation is obtained by using the radar device; The actual moving distance and the monitored moving distance of each calibration point are compared and fused for deviation analysis to obtain the coordinate offset of each calibration point; The measured signal attenuation value of each fixed-point moving operation at each calibration point is obtained, and then the measured signal attenuation value of each calibration point is obtained by performing data fusion analysis.

8. The GNSS-based radar calibration system according to claim 7, characterized in that: The specific method of generating the fixed-point test calibration requirement is as follows: The coordinate offset and measured signal attenuation value of each calibration point are compared with the reference coordinate offset threshold and reference signal attenuation threshold corresponding to each monitoring area to obtain a judgment result on whether each monitoring area needs to be calibrated at a fixed point; If it is determined that a fixed-point test calibration needs to be performed, it is further identified whether the specific test calibration requirement is signal strength compensation or distance recognition correction.

9. The GNSS-based radar calibration system according to claim 8, characterized in that: The specific analysis method of the reference coordinate offset threshold and the reference signal attenuation threshold corresponding to each monitoring area is as follows: The distance between the calibration point corresponding to each monitoring area and the radar equipment is recorded as the threshold influence distance, and then combined with the pre-set coordinate offset threshold and signal attenuation value threshold to perform weight correction fusion calculation to obtain the reference coordinate offset threshold and reference signal attenuation value threshold corresponding to each monitoring area.

10. A radar calibration method based on GNSS, characterized in that: include: Divide the monitoring area based on the geographic coordinates of the target radar device and locate the corresponding calibration points, and generate dynamic calibration tracks based on the radar beam coverage and terrain obstacle data; The drone is equipped with a GNSS signal receiving device and flies along a dynamic calibration trajectory to obtain the monitoring position coordinates of the drone in the radar coordinate system and the absolute position coordinates in the geographic location coordinate system in real time; The integrated environmental sensor network acquires the environmental information of each monitoring area, and performs environmental impact compensation by combining the monitoring position coordinates and absolute position coordinates of each calibration point to perform environmental impact calibration; After the environmental impact calibration, the radar equipment is subjected to a calibration point fixed-point accuracy test to obtain the radar echo attenuation value and coordinate offset of each calibration point, and a fixed-point test calibration requirement is generated, and a fixed-point test calibration is performed accordingly.

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