WO2023116316A1 - Method and system for measuring large-scale radar antenna array surface precision - Google Patents

Abstract

A method and a system for measuring large-scale radar antenna array surface precision, relating to the technical field of antenna array surface precision measurement, and comprising steps including scenario construction, task planning, measurement implementation, quality evaluation, and processing display. The present method uses an unmanned aerial vehicle-mounted photographic measurement system to carry out automatic measurement of large-scale radar antenna array surface precision, and a resulting three-dimensional model result can be displayed. Thus, staff of a radar assembly site can more intuitively and efficiently measure assembly precision of a large-scale radar antenna array surface, thereby solving the technical problems in the prior art of low efficiency in measurement of radar antenna array surface precision, and poor display effects in visualization of a result, and further achieving the technical effects of reducing on-site measurement workload and improving measurement efficiency.

Description

A method and system for measuring the accuracy of a large radar antenna array technical field

The invention relates to the technical field of antenna front precision measurement, in particular to a large-scale radar antenna front precision measurement method and system.

Background technique

The flatness accuracy of the antenna array has a crucial influence on the electrical performance index of the antenna. From the actual process of large-scale antenna array assembly and adjustment, digital photogrammetry detection plays an indispensable key role in the entire assembly and adjustment process. Through the actual measurement and precision adjustment analysis of the antenna array, the gravity deformation curve can be calculated, and the optimal surface accuracy and adjusted pitch angle of the array can be obtained, so as to provide the designer with a simulation analysis of the load deformation. Reliable data, as well as full control over the completion of design, production assembly, installation and measurement. Photogrammetry can meet the flatness measurement of large-scale arrays under various attitudes, and has small environmental requirements and high precision. Therefore, it is especially suitable for online detection during installation and adjustment of large-scale, high-precision antenna structure systems, and effectively guides the array Accuracy adjustment and deformation monitoring of the antenna array, etc., in terms of data processing, photogrammetry is all completed by computer, which breaks away from the uncertain factors of traditional precision optical instruments, and is the future development direction of this detection field.

In the prior art, the method of measuring the accuracy of large-scale radar antenna arrays is usually manual on-site measurement, and offline measurement is often used, which cannot achieve real-time measurement of flatness and real-time correction of errors. The real-time monitoring of flatness error can be used as the input of electrical signal phase compensation, which can improve the radar accuracy and is a key part of radar intelligent perception. The combination of phase photoelectric position sensor and dynamic displacement sensor or acceleration sensor can measure the deformation of the antenna front in real time, or use visual measurement methods and image processing methods to collect the front flatness of each attitude radar in real time. The development of similar online real-time high-precision measurement methods will be the trend of large-scale phased array radar flatness measurement in the future. Summarizing the existing technology has the following shortcomings: First, there are many researches on antenna array photogrammetry methods, but there are few researches on how to quickly generate measurement task planning based on the UAV-based antenna array precision measurement method, and no patents or other methods have been formed. The results of intellectual property rights cannot be widely used; the second is that there is no corresponding method for measuring the accuracy of antenna arrays based on drones, which makes the efficiency of measuring the accuracy of large radar antenna arrays not high, and it is impossible to directly use drones to measure the accuracy of antenna arrays. Measurement, resulting in a waste of personnel and time.

Aiming at the technical problems of low measurement efficiency and poor visual display effect of large-scale radar antenna array accuracy in the prior art, no effective solution has been proposed so far. Therefore, a method and system for large-scale radar antenna array accuracy measurement is proposed.

technical problem

The technical problem to be solved by the present invention is: how to solve the technical problems of low measurement efficiency and poor visual display effect of large-scale radar antenna front in the prior art, and provides a large-scale radar antenna front precision measurement method.

technical solution

The present invention solves the above-mentioned technical problems through the following technical solutions, and the present invention comprises the following steps:

S1: Set the measurement mark points on the real antenna array, initialize the measurement through UAV photography, obtain and match the key feature points of the antenna array real object and the 3D model, and obtain the antenna array aperture size, the coordinate information of the measurement marker points, etc. , and map it to the 3D model to build a 3D measurement scene;

S2: According to the aperture size of the antenna array, equipment parameters, the number of intersections of adjacent measurement marker points, the number of measurement marker points, and the accuracy requirement information, the measurement task is planned and simulated in the three-dimensional measurement scene, and after the iterative optimization of the measurement marker points is set, Obtain UAV track and waypoint data that meet the requirements of antenna array measurement tasks;

S3: Send the UAV track and waypoint data that meet the requirements of the antenna array measurement task to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetric images;

S4: Transmit the photogrammetry image and make a quality compliance judgment, operate the photogrammetry image that is judged to be unsatisfactory and retake the measurement;

S5: Store the photogrammetry image and perform image processing to obtain the coordinate value of the antenna front measurement mark point, form the antenna front accuracy value through data fitting processing, reconstruct the 3D model and display the antenna front measurement accuracy information.

Further, the step S1 includes the following steps:

S11: Set the measurement mark points for the real antenna array. The measurement marker points are set according to the key feature points of the antenna array. The key feature points are important guarantee accuracy such as the aperture profile of the antenna array, the flatness of the antenna array, and the accuracy of the assembly distance. , The characteristic elements of the interface position between the antenna array and other mechanical components, and the antenna array aperture size and the coordinate information of the measurement mark points are obtained through the initial measurement of the UAV photography;

S12: Match the coordinate information of the obtained front aperture size and measurement marker points with the 3D model. Matching with the 3D model is to move, align, and overlap the dominant feature points so that they coincide and match with the feature points corresponding to the 3D model. , and the coordinate information of other measurement marker points are mapped and reflected to the 3D model.

Furthermore, in the step S1, the three-dimensional measurement scene is a fusion information set of the UAV and the photogrammetry equipment mounted on it, the real object of the antenna array and its three-dimensional model, and the coordinates of the measurement marker points that can be visualized on the computer.

Furthermore, in the step S2, planning and simulating the measurement task in the three-dimensional measurement scene, that is, by setting the aperture size value, the position and quantity of the measurement mark points, the number of intersections of adjacent measurement mark points, equipment parameters, and The value required by the measurement accuracy. After iteratively optimizing the measurement mark points, the antenna array measurement mark point coordinates, measurement mark point numbers, measurement times, and measurement angle information that meet the antenna array measurement task requirements are obtained.

Furthermore, in the step S2, for the obtained coordinates of the antenna front measurement mark point, the number of the measurement mark point, the number of measurements, and the measurement angle information, through data conversion, a flight path and a track that can be recognized by the UAV are formed. Waypoint data; among them, data conversion includes data extraction, mapping coding, and unified operation of format specifications, and UAV track and waypoint data include UAV coordinates, waypoint numbers, measurement angles, and measurement times information; The coordinates, waypoint numbers, measurement angles, and measurement times information of the UAV are consistent with the measurement mark point coordinates, measurement mark point numbers, measurement times, and measurement angle information of the antenna array. The measurement mark points of the antenna array The coordinates and the coordinates of the UAV are a global coordinate system including the antenna array, photogrammetry system, measurement markers, and measurement references, which can be displayed visually in a three-dimensional measurement scene.

Further, the step S3 includes the following process: segmentally define the measurement task, divide the UAV track and waypoint data from the measurement task, and display the completion of the measurement task in real time in the three-dimensional measurement scene situation, then the measurement task is connected with the UAV track and waypoint data and the photogrammetry image obtained by photogrammetry, and finally the UAV track and The waypoint data is transmitted to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetry images.

Furthermore, in the step S4, a reverse search is performed on the photogrammetry images that do not meet the requirements, and the tasks that need to be re-photographed and measured are obtained in batches, the positions of the measurement markers, and the corresponding UAV tracks and waypoints data, re-plan the shooting and measurement path, and form a re-shooting and measurement plan; eliminate the photogrammetry images that are determined not to meet the requirements, and replace and supplement the re-shooting and measurement images.

Furthermore, in the step S4, the quality compliance determination elements include the number of intersections of adjacent measurement mark points, clarity, brightness, color shift, and similarity.

Further, the step S5 includes the following steps:

S51: storing the photogrammetry image in the three-dimensional measurement scene database, and storing it in association with the measurement task, the position of the measurement mark point, and the UAV track and waypoint data;

S52: Perform image processing on the photogrammetry image to obtain coordinate values of antenna array measurement marker points, and form antenna array accuracy values through data fitting processing;

S53: Reconstruct the 3D model according to the precision value of the antenna front and display the measurement accuracy information of the antenna front. The reconstruction of the 3D model is to perform [x, y, z, Rx, Ry, Rz] coordinate six-dimensional value transformation, relocate, assemble, and update the pose of the front component parts on the three-dimensional model by the coordinate value;

S54: After the reconstruction of the 3D model is completed, the detailed coordinate values of the measurement coordinate points and the overall flatness error value of the measurement accuracy of the antenna front are visually and interactively displayed on the 3D model.

The present invention also discloses a large-scale radar antenna front precision measurement system that uses the above measurement method to measure the large-scale radar antenna front precision, including:

The scene construction unit is used to obtain and match the key feature points of the real object of the antenna array and the 3D model, obtain the coordinate information of the aperture size of the antenna array and the measurement mark point, and map and reflect it to the 3D model to construct a 3D measurement scene;

The task planning unit is used to plan and simulate the measurement task in the three-dimensional measurement scene according to the size of the antenna array aperture, equipment parameters, the number of intersections of adjacent measurement marker points, the number of measurement marker points, and the accuracy requirements, and iterate the measurement marker points After optimizing the settings, the UAV track and waypoint data that meet the requirements of the antenna array measurement task are obtained;

The measurement implementation unit is used to transmit the UAV track and waypoint data that meet the requirements of the antenna front measurement task to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetric images;

The quality evaluation unit is used to transmit the photogrammetric image and determine the quality compliance, operate the photogrammetric image that is determined not to meet the requirements and re-take the measurement;

The processing and display unit is used to store photogrammetric images and perform image processing to obtain the coordinate values of the antenna front measurement mark points, form the antenna front accuracy value through data fitting processing, reconstruct the 3D model and display the antenna front measurement accuracy information.

Beneficial effect

Compared with the prior art, the present invention has the following advantages: UAV-mounted photogrammetry system is used to automatically measure the accuracy of large-scale radar antenna fronts and visualize the results of the three-dimensional model, so the staff on the radar assembly site can be more intuitive and efficient. The measurement of assembly accuracy of large radar antenna arrays solves the technical problems of low measurement efficiency of radar antenna array accuracy and poor visual display of results in the prior art, and further achieves the technical effect of reducing on-site measurement workload and improving measurement efficiency , it is worth promoting and using.

Description of drawings

Fig. 1 is the flow chart of the large-scale radar antenna front precision measurement method in the embodiment of the present invention;

Fig. 2 is a schematic structural diagram of a large-scale radar antenna front precision measurement system in an embodiment of the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION

The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

The technical terms involved in the embodiments of the present invention are explained as follows:

Three-dimensional measurement scene: refers to the collection of fusion information such as unmanned aerial vehicle and its equipped photogrammetry equipment, antenna array object and its three-dimensional model, coordinates of measurement markers, etc., which are visualized in the computer.

3D model: refers to a collection of reconfigurable models that inherit from the antenna array design model and carry the necessary measurement elements.

According to an embodiment of the present invention, an embodiment of a method for measuring the accuracy of a large-scale radar antenna front is provided. It should be noted that the steps shown in the flow chart of the accompanying drawings can be implemented in a computer system such as a set of computer-executable instructions and, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

Fig. 1 is a flowchart of a method for measuring the accuracy of a large-scale radar antenna front according to an embodiment of the present invention. As shown in Fig. 1, the method includes steps S1 to S5, wherein:

Step S1: According to the measurement mark points set on the real antenna array, the measurement is initialized by UAV photography, and the key feature points of the real antenna array and the 3D model are obtained and matched, and the aperture size of the antenna array and the distance between the measurement marker points are obtained. Coordinate information, etc., and map and reflect to the 3D model to construct a 3D measurement scene.

More specifically, the measurement mark points are set on the real object of the antenna array, and the measurement marker points are set according to the key feature points of the real antenna array, the key feature points are the aperture profile of the antenna array, the flatness of the antenna array, and the accuracy of the assembly distance The important elements to ensure the accuracy, such as the interface between the antenna array and other mechanical parts, etc., obtain the antenna array aperture size and the coordinate information of the measurement mark points through the initial measurement of the UAV photography; the antenna array aperture size, measurement The coordinate information of the marked points is matched with the 3D model. The 3D model is the design model of the antenna array, and the matching with the 3D model is to move, align, and coincide with the dominant feature points such as the outline of the antenna array and the interface with other mechanical components. Operation, so that it coincides with the feature points corresponding to the 3D model, and the coordinate information of other measurement marker points is mapped to the 3D model; the 3D measurement scene is a UAV that can be visualized on the computer, and the photogrammetry equipment and antenna it carries A collection of fused information such as front objects and their 3D models, coordinates of measurement markers, etc.

Step S2: According to the antenna array size, equipment parameters, the number of intersections of adjacent measurement markers, the number of measurement markers, accuracy requirements and other information, the number of intersections of adjacent measurement markers is the number of overlapping points between adjacent photos, indicating the intersection area Size; in the three-dimensional measurement scene, the measurement task is planned and simulated, and the measurement mark points are iteratively optimized and set to obtain the UAV track and waypoint data that meet the requirements of the antenna array measurement task.

More specifically, the planning and simulation of the measurement task in the three-dimensional measurement scene is to set the parameter values of the aperture size, the location and quantity of the measurement mark points, the number of intersections of adjacent measurement mark points, equipment parameters, and measurement accuracy requirements. After the iterative optimization setting of the points, the coordinates of the antenna array measurement mark point, the number of the measurement mark point, the number of measurements, the measurement angle and other information that meet the requirements of the antenna array measurement task are obtained; the evaluation indicators that meet the measurement task requirements include measurement accuracy requirements, measurement Time, measurement coverage and other elements, for different measurement task requirements, planning and simulation can form different measurement task planning and measurement point setting schemes; for the obtained antenna array measurement point coordinates, measurement point numbers, and measurement times , measurement angle and other information, through data conversion, form the track and waypoint data that the UAV can recognize; Track and waypoint data; UAV track and waypoint data include UAV coordinates, waypoint numbers, measurement angles, measurement times, etc.; UAV coordinates, waypoint numbers, measurement angles, measurement times, etc. The obtained measurement mark point coordinates, measurement mark point numbers, measurement times, measurement angles and other information correspond to each other; The global coordinate system including , etc., can be visualized in the 3D measurement scene.

Step S3: The UAV track and waypoint data that meet the requirements of the antenna array measurement task are transmitted to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain a photogrammetric image.

More specifically, the measurement task is defined in segments, the UAV track and waypoint data are divided into tasks, and the completion of the measurement task is displayed in real time in the three-dimensional measurement scene to prevent the UAV from being damaged due to battery life problems. The measurement task is interrupted, the data is lost, and the measurement cannot continue; the measurement task, the UAV track, the waypoint data, and the photogrammetry image obtained by photogrammetry are connected and associated with information, and the "measurement task" is used as the first For the first-level node, the "UAV track" that realizes the measurement task is used as the second-level node, which is connected to the first-level node "measurement task", and "waypoint data" is used as the third-level node, which is connected to the second-level node. The second-level node "UAV track" and "photogrammetry image" as the fourth-level node are connected to the third-level node "waypoint data"; the UAV track and The waypoint data is transmitted to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetry images.

Step S4: Transmit the photogrammetric image and make a quality compliance judgment, operate on the photogrammetric image that is judged to be unsatisfactory and retake the measurement; the quality compliance judgment elements include the number of intersections of adjacent measurement mark points, clarity, brightness, color Bias, similarity, etc.

More specifically, perform a reverse search on the photogrammetry images that do not meet the requirements, obtain the tasks that need to be re-photographed and measured in batches, measure the position of the marker points and the corresponding UAV track and waypoint data, and re-plan the shooting and measurement path , to form a re-shooting measurement plan; the photogrammetry images determined not to meet the requirements are eliminated, and the re-shooting measurement images are replaced and supplemented.

Step S5: Store the photogrammetric image and perform image processing to obtain the coordinate values of the antenna front measurement mark points, form the antenna front accuracy value through data fitting processing, reconstruct the 3D model and display the antenna front measurement accuracy information.

More specifically, photogrammetry images are stored in the 3D measurement scene database, and stored in association with measurement tasks, measurement marker positions, and UAV track and waypoint data; image color uniformity and distortion correction are performed on photogrammetry images Image processing such as image processing, hierarchical adjustment calculation, etc., to obtain the coordinate value of the antenna front measurement mark point, and form the antenna front precision value through data fitting processing; reconstruct the 3D model according to the antenna front precision value and display the antenna front measurement Accuracy information, the three-dimensional model is reconstructed according to the coordinate value of the antenna front measurement mark point, and the [x, y, z, Rx, Ry, Rz] coordinate six-dimensional value conversion is performed, wherein each measurement mark point is fitted into a multi- A detail plane group, and then integrate multiple detail plane groups to form an overall surface, collect the coordinates of the center points of multiple detail plane groups to form the coordinate values [x, y, z, Rx, Ry, Rz] of the center point of the overall surface; (x, y, z) represents the coordinate value of the measurement mark point in the OXYZ coordinate system, and (Rx, Ry, Rz) represents the angle of rotation of the measurement mark point around the x, y, and z axes, that is, the Euler angle (eular) . Relocate, assemble, and update the pose of the array components on the 3D model according to the coordinate values of the measurement marker points; the displayed antenna array measurement accuracy information includes visual and interactive display on the 3D model after the reconstruction of the 3D model is completed The detailed coordinate values of the measurement coordinate points, and the error values such as the overall flatness of the antenna front measurement accuracy.

In the embodiment of the present invention, by acquiring and matching the key feature points of the real object of the antenna array and the 3D model, the aperture size of the antenna array, the coordinate information of the measurement marker points, etc. are obtained, and mapped to the 3D model to construct a 3D measurement scene; According to the antenna array size, equipment parameters, the number of intersections of adjacent measurement markers, the number of measurement markers, accuracy requirements and other information, the measurement task is planned and simulated in the 3D measurement scene, and after the iterative optimization of the measurement markers is set, the obtained The UAV track and waypoint data that meet the requirements of the antenna front measurement task; the UAV track and waypoint data that meet the antenna front measurement task requirements are transmitted to the UAV system, and the UAV follows the measurement task prediction Set up a path for photogrammetry to obtain a photogrammetry image; transmit the photogrammetry image and perform quality compliance judgment, operate the photogrammetry image that does not meet the requirements and re-take the measurement; the quality compliance judgment elements include adjacent measurement marks The number of point intersections, clarity, brightness, color shift, similarity, etc.; store the photogrammetry image and perform image processing to obtain the coordinate values of the antenna array measurement mark points, and form the antenna array accuracy value through data fitting processing. The three-dimensional model Reconstruct and display the measurement accuracy information of the antenna front to achieve the purpose of large-scale radar antenna front precision measurement and result visualization. Since the UAV is equipped with a photogrammetry system to automatically measure the large-scale radar antenna front precision and the three-dimensional model The results are visualized, so the staff at the radar assembly site can measure the assembly accuracy of the large-scale radar antenna array more intuitively and efficiently, which solves the problems of low measurement efficiency of the radar antenna array accuracy and poor visual display of the results in the prior art problems, and then achieved the technical effect of reducing the workload of on-site measurement and improving measurement efficiency.

Fig. 2 is a schematic structural diagram of a large-scale radar antenna front precision measurement system according to an embodiment of the present invention. The large-scale radar antenna front precision measurement system includes: a scene construction unit 1, a task planning unit 2, a measurement implementation unit 3, a quality evaluation unit 4, and a processing and display unit 5, wherein:

The scene construction unit 1 is used to obtain and match the key feature points of the antenna array object and the 3D model, obtain the antenna array aperture size, the coordinate information of the measurement mark points, etc., and map and reflect it to the 3D model to construct a 3D measurement scene. In this embodiment, the scene construction unit 1 includes a marker setting module, an initial measurement module and a feature matching module.

The marker setting module is used to set the measurement mark points on the real antenna array. The measurement marker points are set according to the key feature points of the antenna array. The key feature points are the aperture profile of the antenna array, the flatness of the antenna array, the accuracy of the assembly distance, etc. It is important to ensure the accuracy, the characteristic elements of the position of the interface between the antenna array and other mechanical components.

The initial measurement module is used to measure and obtain the aperture size of the antenna array, the coordinate information of the measurement mark points, etc., to form a three-dimensional measurement scene, specifically the unmanned aerial vehicle and the photogrammetry equipment that can be visualized in the computer, the actual object of the antenna array and It is a collection of fused information such as 3D models, coordinates of measurement markers, etc.

The feature matching module is used to match the obtained antenna array aperture size, coordinate information of measurement marker points, etc. with the 3D model, specifically to move, align, and coincide with the dominant feature points such as the antenna array outline and the interface with other mechanical components Operation, so that it coincides and matches with the corresponding feature points of the 3D model, and the coordinate information of other measurement marker points is mapped and reflected to the 3D model.

The task planning unit 2 is used to plan and simulate the measurement task in the three-dimensional measurement scene according to the size of the antenna array, equipment parameters, the number of intersections of adjacent measurement marker points, the number of measurement marker points, and accuracy requirements, and to plan and simulate the measurement marker points. After the iterative optimization settings, the UAV track and waypoint data that meet the requirements of the antenna front measurement task are obtained. In this embodiment, the task planning unit 2 includes a scheme generation module and a data conversion module.

The scheme generation module is used to plan and simulate the measurement task in the three-dimensional measurement scene. By setting the value of the aperture size, the position and quantity of the measurement mark points, the number of intersections of adjacent measurement mark points, the equipment parameters, and the measurement accuracy requirements, etc., the After the measurement mark points are set iteratively and optimally, the antenna array measurement mark point coordinates, measurement mark point numbers, measurement times, measurement angles and other information that meet the antenna array measurement task requirements are obtained; the evaluation indicators that meet the measurement task requirements include measurement accuracy requirements , measurement time, measurement coverage and other elements, for different measurement task requirements, planning and simulation can form different measurement task planning and measurement mark point setting schemes;

The data conversion module is used to obtain information such as the coordinates of the antenna array measurement markers, the number of the measurement markers, the number of measurements, and the angle of measurement, through operations such as data extraction, mapping encoding, and format standardization, to form a UAV flight control system that can Recognized track and waypoint data; UAV track and waypoint data include drone coordinates, waypoint number, measurement angle, measurement times, etc.; UAV coordinates, waypoint number, measurement angle, measurement times The information such as the coordinates of the measurement mark point, the number of the measurement mark point, the number of times of measurement, the measurement angle and other information are respectively corresponding and consistent; The global coordinate system including , measurement datum, etc. can be visualized in the 3D measurement scene.

The measurement implementation unit 3 is used to transmit the UAV track and waypoint data that meet the requirements of the antenna front measurement task to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetric images. In this embodiment, the measurement implementation unit 3 includes a division module, an association module and an execution module.

The division module is used to segmentally define the measurement task, divide the UAV track and waypoint data and tasks into data, and display the completion of the measurement task in real time in the three-dimensional measurement scene, so as to prevent the unmanned aerial vehicle due to battery life problems. The measurement task is interrupted, the data is lost, and the measurement cannot continue.

The associating module is used to connect and associate the measurement task with the UAV track and waypoint data, and the photogrammetry images obtained by photogrammetry.

The execution module is used to transmit the UAV track and waypoint data that meet the requirements of the antenna front measurement task to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetric images.

The quality evaluation unit 4 is used to transmit the photogrammetry image and perform quality compliance judgment, operate the photogrammetry image that is determined not to meet the requirements and retake the measurement; the quality compliance judgment elements include the number of intersections of adjacent measurement marker points, Clarity, brightness, color cast, similarity, etc. Perform a reverse search on the photogrammetry images that do not meet the requirements, obtain the tasks that need to be re-photographed and measured in batches, the positions of the measurement points, and the corresponding UAV track and waypoint data, re-plan the shooting and measurement path, and form a new The photogrammetric plan; the photogrammetric images determined not to meet the requirements are eliminated, and the photogrammetric images are re-photographed for replacement and supplementation.

The processing and display unit 5 is used to store photogrammetric images and perform image processing to obtain the coordinate values of the antenna front measurement mark points, form the antenna front accuracy value through data fitting processing, reconstruct the three-dimensional model and display the antenna front measurement Accuracy information. In this embodiment, the processing and display unit 5 includes a processing module, a reconstruction module and a display module.

The processing module is used to store the photogrammetry image, which is associated with the measurement task, the position of the measurement mark point, and the UAV track and waypoint data; image processing is performed on the photogrammetry image to obtain the coordinate value of the antenna array measurement mark point, through The data fitting process forms the antenna front precision value; according to the antenna front precision value, the three-dimensional model is reconstructed and the antenna front measurement precision information is displayed.

The reconstruction module is used to convert the six-dimensional values of [x, y, z, Rx, Ry, Rz] coordinates according to the coordinate values of the marked points measured on the antenna front, and reconstruct the coordinate values on the front component parts on the three-dimensional model Locate, assemble, update pose.

The display module is used to visually and interactively display the detailed coordinate values of the measurement coordinate points on the 3D model after the reconstruction of the 3D model is completed, as well as error values such as the overall flatness of the measurement accuracy of the antenna front.

Each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may physically exist separately, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

To sum up, the method for measuring the accuracy of large radar antenna arrays in the above-mentioned embodiments uses the photogrammetry system carried by the drone to automatically measure the accuracy of the array of large radar antennas and visualize the results of the 3D model, so the work on the radar assembly site Personnel can measure the assembly accuracy of large-scale radar antenna arrays more intuitively and efficiently, which solves the technical problems of low measurement efficiency of radar antenna array accuracy and poor visual display of results in the prior art, thereby reducing the workload of on-site measurement And the technical effect of improving measurement efficiency is worthy of promotion and use.

Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention, those skilled in the art can make the above-mentioned The embodiments are subject to changes, modifications, substitutions and variations.

Claims (10)

1. A method for measuring the accuracy of a large-scale radar antenna front is characterized in that it comprises the following steps:

   S1: Set the measurement mark points on the real antenna array, initialize the measurement through UAV photography, obtain and match the key feature points of the antenna array real object and the 3D model, and obtain the antenna array aperture size, the coordinate information of the measurement marker points, etc. , and map it to the 3D model to build a 3D measurement scene;

   S2: According to the aperture size of the antenna array, equipment parameters, the number of intersections of adjacent measurement marker points, the number of measurement marker points, and the accuracy requirement information, the measurement task is planned and simulated in the three-dimensional measurement scene, and after the iterative optimization of the measurement marker points is set, Obtain UAV track and waypoint data that meet the requirements of antenna array measurement tasks;

   S3: Send the UAV track and waypoint data that meet the requirements of the antenna array measurement task to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetric images;

   S4: Transmit the photogrammetry image and make a quality compliance judgment, operate the photogrammetry image that is judged to be unsatisfactory and retake the measurement;

   S5: Store the photogrammetry image and perform image processing to obtain the coordinate value of the antenna front measurement mark point, form the antenna front accuracy value through data fitting processing, reconstruct the 3D model and display the antenna front measurement accuracy information.
2. A method for measuring the accuracy of a large radar antenna front according to claim 1, wherein said step S1 comprises the following steps:

   S11: Set the measurement mark points for the real antenna array. The measurement marker points are set according to the key feature points of the antenna array. The key feature points are the antenna array aperture profile, antenna array flatness, assembly distance accuracy, antenna array For the characteristic elements of the interface position with other mechanical components, the aperture size of the antenna array and the coordinate information of the measurement mark points are obtained through the initial measurement of the UAV photography;

   S12: Match the coordinate information of the obtained front aperture size and measurement marker points with the 3D model. Matching with the 3D model is to move, align, and overlap the dominant feature points so that they coincide and match with the feature points corresponding to the 3D model. , and the coordinate information of other measurement marker points are mapped and reflected to the 3D model.
3. A method for measuring the accuracy of a large-scale radar antenna front according to claim 2, characterized in that: in the step S1, the three-dimensional measurement scene is an unmanned aerial vehicle capable of visual display in a computer and a photogrammetry equipment mounted on it, The fusion information collection of the real object of the antenna array and its three-dimensional model, and the coordinates of the measurement mark points.
4. A method for measuring the accuracy of a large radar antenna front according to claim 1, characterized in that: in the step S2, in the three-dimensional measurement scene, the measurement task is planned and simulated by setting the aperture value, measuring The location and number of marker points, the number of intersections of adjacent measurement marker points, equipment parameters, and the value required for measurement accuracy. After iteratively optimizing the measurement marker points, the coordinates of the antenna array measurement marker points that meet the requirements of the antenna array measurement task are obtained. , measurement mark point number, measurement times, measurement angle information.
5. A method for measuring the accuracy of a large radar antenna front according to claim 1, wherein in the step S2, the obtained coordinates of the antenna front measurement mark point, the number of the measurement mark point, the number of measurements, Measuring angle information, through data conversion, forms track and waypoint data that can be recognized by UAVs; among them, data conversion includes data extraction, mapping coding, format specification and unified operation, UAV track and waypoint data include Human-machine coordinates, waypoint numbers, measurement angles, and measurement times information; the UAV’s coordinates, waypoint numbers, measurement angles, and measurement times information, as well as the coordinates of the measurement mark points on the antenna array, the measurement mark point numbers, and the measurement times The number of times and the measurement angle information are correspondingly consistent, and the coordinates of the measurement mark points of the antenna array and the coordinates of the unmanned aerial vehicle are the global coordinate system including the antenna array, the photogrammetry system, the measurement marker points, and the measurement reference. It can be visualized in the 3D measurement scene.
6. A method for measuring the accuracy of a large radar antenna front according to claim 1, wherein said step S3 includes the following process: defining the measurement task in sections, and combining the UAV track and waypoint data Carry out data division with the measurement task, display the completion of the measurement task in real time in the three-dimensional measurement scene, and then carry out information socketing of the measurement task with the UAV track and waypoint data and the photogrammetry image obtained by photogrammetry Finally, the UAV track and waypoint data that meet the requirements of the antenna array measurement task are transmitted to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetric images.
7. A method for measuring the accuracy of a large-scale radar antenna front according to claim 1, characterized in that: in the step S4, a reverse search is performed on the photogrammetric images that are determined not to meet the requirements, and batch acquisition needs to be re-photographed for measurement The task of measuring the position of the marker point and the corresponding UAV track and waypoint data, re-planning the shooting measurement path, forming a re-shooting measurement plan; eliminating the photogrammetry images that do not meet the requirements, and re-shooting and measuring The image is replaced and supplemented.
8. A method for measuring the accuracy of a large-scale radar antenna front according to claim 7, wherein in said step S4, the quality compliance determination elements include the number of intersections of adjacent measurement mark points, clarity, brightness, and color shift , similarity.
9. A method for measuring the accuracy of a large radar antenna front according to claim 1, wherein said step S5 comprises the following steps:

   S51: storing the photogrammetry image in the three-dimensional measurement scene database, and storing it in association with the measurement task, the position of the measurement mark point, and the UAV track and waypoint data;

   S52: Perform image processing on the photogrammetry image to obtain coordinate values of antenna array measurement marker points, and form antenna array accuracy values through data fitting processing;

   S53: Reconstruct the 3D model according to the precision value of the antenna front and display the measurement accuracy information of the antenna front. The reconstruction of the 3D model is to perform [x, y, z, Rx, Ry, Rz] coordinate six-dimensional value transformation, in which, each measurement mark point is fitted into multiple detail plane groups, and then multiple detail plane groups are integrated to form an overall surface, and the coordinates of the center points of multiple detail plane groups are collected to form The coordinate value of the center point of the overall surface [x, y, z, Rx, Ry, Rz]; (x, y, z) represents the coordinate value of the measurement mark point in the OXYZ coordinate system, and (Rx, Ry, Rz) represents Measure the rotation angle of the marked point around the x, y, and z axes, that is, the Euler angle; reposition, assemble, and update the pose of the array components on the 3D model according to the coordinate value of the measured mark point;

   S54: After the reconstruction of the 3D model is completed, the detailed coordinate values of the measurement mark points and the overall flatness error value of the measurement accuracy of the antenna front are visually and interactively displayed on the 3D model.
10. A large-scale radar antenna front precision measurement system, characterized in that the measurement method according to any one of claims 1 to 9 is used to measure the large-scale radar antenna front precision, including:

    The scene construction unit is used to obtain and match the key feature points of the real object of the antenna array and the 3D model, obtain the coordinate information of the aperture size of the antenna array and the measurement mark point, and map and reflect it to the 3D model to construct a 3D measurement scene;

    The task planning unit is used to plan and simulate the measurement task in the three-dimensional measurement scene according to the size of the antenna array aperture, equipment parameters, the number of intersections of adjacent measurement marker points, the number of measurement marker points, and the accuracy requirements, and iterate the measurement marker points After optimizing the settings, the UAV track and waypoint data that meet the requirements of the antenna array measurement task are obtained;

    The measurement implementation unit is used to transmit the UAV track and waypoint data that meet the requirements of the antenna front measurement task to the UAV system, and the UAV performs photogrammetry according to the preset path of the measurement task to obtain photogrammetric images;

    The quality evaluation unit is used to transmit the photogrammetric image and determine the quality compliance, operate the photogrammetric image that is determined not to meet the requirements and re-take the measurement;

    The processing and display unit is used to store photogrammetric images and perform image processing to obtain the coordinate values of the antenna front measurement mark points, form the antenna front accuracy value through data fitting processing, reconstruct the 3D model and display the antenna front measurement accuracy information.