A measuring system and method for real-time muzzle velocity and barrel attitude of a cannonball

Abstract

A measurement system for real-time muzzle velocity and barrel attitude of artillery shells includes an industrial control computer; a muzzle acquisition unit that communicates with the industrial control computer via their respective wireless communication modules; an RTK (Rapid-Release Kinematic) drone equipped with a positioning module and a wireless communication module. The RTK drone, combined with positioning data sent from a compatible positioning base station, can accurately locate itself and transmit its positioning data to the industrial control computer in real time via its wireless communication module; and a checkerboard calibration board, which, together with the RTK drone, is used to calibrate and convert coordinate relationships between the high-speed camera and the lidar. This invention solves the problem in existing technologies where the barrel attitude and firing angle / direction shift after firing, requiring remeasurement and resulting in time consumption. This invention allows for real-time recording and calculation of barrel attitude, firing angle, and direction, providing convenience and speed.

Description

Technical Field

[0001] This invention belongs to the field of measurement technology for projectile initial velocity, firing angle, and firing direction, and specifically relates to a measurement system and method for real-time projectile exit velocity and gun barrel attitude. Background Technology

[0002] Non-contact measurement is currently the mainstream trend in measuring the static or dynamic parameters of objects. The muzzle velocity of a projectile, as well as the attitude, angle, and trajectory of the gun barrel, are crucial parameters in military equipment for determining the success of a mission. The current mainstream method for measuring muzzle velocity involves deploying sensors inside the gun barrel, using optical and pressure sensors for detection and calculation. However, this method is complex to deploy and difficult to maintain, and it fails to measure and calculate the gun barrel attitude, angle, and trajectory. The current mainstream method for measuring angle and trajectory involves measuring the platform and attitude of the gun barrel before firing. After this initial measurement, it is difficult to remeasure the angle and trajectory during continuous firing missions, making real-time, dynamic, and continuous data acquisition impossible.

[0003] Therefore, in order to address the above problems, there is an urgent need for a system that can measure the muzzle velocity, firing angle, and firing direction of the projectile in real time. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a measurement system and method for real-time muzzle velocity of projectiles and barrel attitude. The specific technical solution is as follows:

[0005] A measurement system for real-time muzzle velocity of projectiles and barrel attitude, the measurement system comprising:

[0006] Industrial control computers;

[0007] The muzzle acquisition unit communicates with the industrial control computer via their respective wireless communication modules; the muzzle acquisition unit consists of a high-speed camera and a lidar, and the high-speed camera and lidar are synchronized through a timing module to ensure that their times are synchronized.

[0008] The gun barrel is located within the field of view of the high-speed camera and lidar to measure its own attitude in real time.

[0009] The RTK drone is equipped with a positioning module and a wireless communication module. The RTK drone can accurately locate itself by combining the positioning data sent by the positioning base station that is compatible with it, and can send its own positioning data to the industrial control computer in real time through its wireless communication module.

[0010] The checkerboard calibration board, together with the RTK UAV, is used to calibrate and transform the coordinate relationship of the high-speed camera and the lidar. During the calibration process, both are located within the field of view of the high-speed camera and the lidar.

[0011] The industrial control computer and the muzzle acquisition unit are both powered by the UPS module.

[0012] A method for measuring the real-time muzzle velocity of a projectile and the attitude of a gun barrel, the method comprising the following steps:

[0013] Step S1: System Setup

[0014] Set up and fix the industrial control computer, and connect and fix the wireless communication module and UPS module that work with it; set up and fix the muzzle acquisition unit, and connect and fix the wireless communication module, UPS module and timing module that work with it; set up and fix the positioning base station, and put it into base station mode;

[0015] Step S2: Calculate camera intrinsic parameters and camera extrinsic parameter calibration files.

[0016] The checkerboard calibration board is moved back and forth and left and right within the field of view of the high-speed camera and the lidar. The high-speed camera and lidar collect and record each fixed point, and save the image and point cloud data of the corresponding point. The algorithm identifies the position of the checkerboard calibration board in real time, and manually identifies the checkerboard point cloud data. There are more than 20 pairs. The camera intrinsic parameters of the high-speed camera and the camera extrinsic parameters of the conversion relationship between the high-speed camera and the lidar are calculated.

[0017] Step S3: Calculate the calibration file for the camera coordinate system and the northeast-sky coordinate system.

[0018] The RTK drone is moved forward, backward, left, and right within the field of view of the high-speed camera. The industrial control computer receives the positioning information of the RTK drone in real time. The industrial control computer matches the image and positioning data according to the timestamp information. The RTK drone flies near the center of the image for 5 minutes, then ends the flight and calculates the transformation relationship between the camera coordinate system and the northeast-sky coordinate system.

[0019] Step S4: Calculate the firing direction and angle of the gun barrel.

[0020] The checkerboard calibration board and RTK UAV are removed, the lidar scans the point cloud data of the gun barrel, and the firing direction and firing angle representing the gun barrel attitude are calculated according to the conversion relationship in steps S2 and S3.

[0021] Step S5: Calculate the real-time muzzle velocity of the projectile.

[0022] The high-speed camera is put into high-speed acquisition mode. At this time, the shell is launched and the high-speed camera acquires and records image data at high speed. According to the barrel attitude in step S4, the image perspective is transformed to a plane perpendicular to the optical center of the high-speed camera. The real-time muzzle velocity of the shell is calculated by using the distance and time between multiple frames.

[0023] Step S6: Continuously calculate the barrel attitude and the real-time muzzle velocity of the next projectile.

[0024] After the current shell is fired, the lidar collects the point cloud data of the barrel in real time, updates the barrel's attitude in real time, recalculates the barrel's firing direction and firing angle, and repeats step S5 to calculate the real-time muzzle velocity of the next shell.

[0025] Step S7: End the data collection and retrieve the equipment.

[0026] Furthermore, in steps S2 and S3, the output information of the high-speed camera and the lidar contains absolute timestamp information assigned by the GPS timing module, and the positioning data based on the GNGGA protocol transmitted back by the RTK UAV also contains absolute timestamp information. The industrial control computer retrieves the same timestamp as a pair of data for pairing and parsing among the high-speed camera, lidar, and RTK UAV, for use in the inversion calculation during calibration.

[0027] Furthermore, after receiving B-code timing from the timing module, the high-speed camera adopts the BeiDou satellite reference time and receives the 1PPS signal from the BeiDou satellite. When the high-speed camera receives the trigger signal, it starts high-speed image acquisition from the next whole second. At the same time, the positioning module in the RTK UAV also receives the 1PPS signal from the BeiDou satellite and outputs the differential positioning data of the RTK UAV based on the GNGGA protocol every 100ms starting from the whole second.

[0028] Furthermore, in step S3, the extraction of pixel coordinates from the RTK drone needs to go through three stages: discovery, tracking, and filtering. The specific steps are as follows:

[0029] Step S3.1: Process the first 10 frames of the image sequence using the frame difference method to segment the moving targets in the video;

[0030] Step S3.2: Using the RTK UAV target extracted in step S3.1 as a template, the optical flow method is used to continuously track the UAV target to obtain the target's coordinate sequence p. l and p r Confidence sequence C l and C r ;

[0031] Step S3.3: Set the confidence threshold C T Filter coordinate sequences p where both left and right confidence scores are greater than the threshold.l ′ and p r ′.

[0032] Furthermore, in step S3, the latitude and longitude of the RTK UAV need to be converted to the northeast-northeast coordinate system, the distance from the RTK UAV to the reference ellipsoid is h, and the following relationship is satisfied:

[0033] h = H + N

[0034] Where H is altitude and N is geoid difference; both H and N can be obtained from RTK UAV data; then, the latitude and longitude are converted to the northeast-northeast coordinate system according to the following formula:

[0035]

[0036] Here, Δ refers to the offset relative to the reference origin.

[0037] Furthermore, in step S2, the calibration formulas for calculating the camera intrinsic parameters and the camera extrinsic parameters that determine the conversion relationship between the high-speed camera and the lidar are as follows:

[0038]

[0039]

[0040] In the above formula, R = [R x R y R z ], T = [t x t y t z ] T , respectively, are the rotation matrix R and translation matrix T of the extrinsic parameters, and matrix K is the intrinsic parameter; f x =f / dx, f y = f / dy, where f is the focal length of the high-speed camera, and dx*dy is the physical size of each pixel in the sensor of the high-speed camera, (X w ,Y w Z w Z is the world coordinate system, (u,v) is the pixel coordinate system for interpreting the RTK UAV in the image, and Z is the world coordinate system. C For the camera coordinate system (X) c ,Y c Z c In the equation, s represents the distance component of the object along the direction of the optical center, and s is the tilt between the camera target and the lens.

[0041] Furthermore, in step S3, the derivation formula for calculating the transformation relationship between the camera coordinate system and the northeast-sky coordinate system is as follows:

[0042]

[0043] In the above formula, the real-time latitude and longitude output by the RTK drone is converted into (X... w ,Y w Z w );

[0044] Once the RTK drone is detected as being located at the center of the image, its latitude, longitude, and coordinates (X1, Y1, Z1) are recorded. C The value is There are 9 unknowns in R, and 8 unknowns considering rotation consistency. There are 3 unknowns in T. One coordinate point can provide 2 equations. That is, by finding 6 points at different depths located at the center of the image, the R and T matrices can be solved, which can be used as the transformation matrix from the camera coordinate system to the northeast-sky coordinate system.

[0045] Further, in step S4, the firing angle is the angle between the barrel vector and the northeast plane in the northeast-northeast coordinate system, denoted as α, and the firing direction is the angle between the projection vector of the barrel vector onto the northeast plane in the northeast-northeast coordinate system and the due north direction, denoted as β.

[0046] To calculate the firing angle and direction, the gun barrel's attitude must first be transformed to the northeast-sky coordinate system. The transformation relationship from the radar coordinate system to the camera [R1, T1] and from the camera to the northeast-sky coordinate system [R2, T2] can be obtained. Using a lidar, the gun barrel's axis vector in the radar coordinate system can be obtained as S1, and the axis vector in the northeast-sky coordinate system is S2 = [R1, T1] · S1[R2, T2]. From this, the firing angle and direction can be calculated. Assuming S2 calculates the gun barrel's vector as (x... p ,y p ,z p If the angle and direction of the shot are given, then the formulas for calculating them are as follows:

[0047]

[0048]

[0049] Further, in step S5, before firing the shell, the number of pixels C occupied by a fixed length L in the front view is measured; after perspective change, at a certain moment, the image pixel of the shell in the front view is located at (x1, y1), after time T0 it is located at image pixel (x2, y2), and after time T1 it is located at image pixel (x3, y3). Then the initial velocity of the shell leaving the barrel is:

[0050]

[0051] The beneficial effects of this invention are:

[0052] (1) This invention provides a system for measuring the muzzle velocity of a cannon combined with the firing angle and direction of the cannon barrel. It also solves the problem in the prior art that the attitude and firing angle and direction of the cannon barrel will deviate after the firing action, and the personnel need to remeasure, which is time-consuming. This invention can record and calculate the attitude, firing angle and direction of the cannon barrel in real time, which is convenient and fast. In this way, when the firing angle and direction exceed the limit value, the operator can be reminded in time.

[0053] (2) This invention abandons the traditional binocular image intersection measurement method and adopts a single station to quickly measure parameters such as the direction angle, attitude angle and shooting speed based on the northeast-northeast coordinate system in real time. The single station includes a point cloud and image acquisition module. The RTK calibration method is introduced, which can establish a mutual conversion relationship between the coordinate system where the point cloud is located, the camera coordinate system and the northeast-northeast coordinate system. Attached Figure Description

[0054] Figure 1 A schematic diagram of the measurement system of the present invention is shown;

[0055] Figure 2 A flowchart illustrating the measurement method of the present invention is shown;

[0056] Figure 3 A schematic diagram of industrial control computer pairing and parsing in this invention is shown;

[0057] Figure 4 A schematic diagram illustrating the synchronization between image timestamps and location information timestamps in this invention is shown.

[0058] Figure 5 A schematic diagram of the northeast-sky coordinate system in this invention is shown;

[0059] Figure 6 This invention illustrates the relationship between the altitude of the RTK UAV, the geoid difference, and the distance to the reference ellipsoid.

[0060] Figure 7 A schematic diagram of the camera coordinate system and the solid geometric coordinate system in this invention is shown;

[0061] Figure 8 This diagram illustrates the angle between the firing angle and the firing direction of the gun barrel in the northeast-northeast coordinate system of this invention. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0063] like Figure 1As shown, a measurement system for real-time muzzle velocity of projectiles and barrel attitude is provided. The measurement system includes:

[0064] Industrial control computers;

[0065] The muzzle acquisition unit communicates with the industrial control computer via their respective wireless communication modules; the muzzle acquisition unit consists of a high-speed camera and a lidar, and the high-speed camera and lidar are synchronized through a timing module to ensure that their times are synchronized.

[0066] The gun barrel is located within the field of view of the high-speed camera and lidar to measure its own attitude in real time.

[0067] The RTK drone is equipped with a positioning module and a wireless communication module. The RTK drone can accurately locate itself by combining the positioning data sent by the positioning base station that is compatible with it, and can send its own positioning data to the industrial control computer in real time through its wireless communication module.

[0068] The checkerboard calibration board, together with the RTK UAV, is used to calibrate and transform the coordinate relationship of the high-speed camera and the lidar. During the calibration process, both are located within the field of view of the high-speed camera and the lidar.

[0069] The industrial control computer and the muzzle acquisition unit are both powered by the UPS module.

[0070] By adopting the above technical solution, a system for measuring the muzzle velocity of a cannonball combined with the firing angle and direction of the cannon is provided. At the same time, it solves the problem in the prior art that the attitude and firing angle and direction of the cannon barrel will deviate after the firing action, and the personnel need to remeasure, which is time-consuming. The present invention can record and calculate the attitude, firing angle and direction of the cannon barrel in real time, which is convenient and fast. In this way, when the firing angle and direction exceed the limit value, the operator can be promptly reminded.

[0071] The high-speed camera is a monocular camera, and the lateral distance between the high-speed camera and the lidar is fixed. The high-speed camera is located on the left and the lidar is located on the right, which facilitates the observation of the barrel attitude and the muzzle velocity.

[0072] Compared to existing technologies, CN111059961A, "A Real-time Detection Method for Artillery Attitude Parameters Using a Total Station," requires marking on the gun barrel and setting fixed measurement targets on the top and side of the barrel; CN116399167A, "A Method for Artillery Accuracy Verification," requires attaching a first and second marker point to the breech and muzzle of the gun barrel respectively; and setting up a first and second total station on the rear and front sides of the gun barrel respectively. This system can measure attitude angles using point cloud processing from a lidar system, eliminating the need for target marking. Furthermore, secondary measurements after gun barrel displacement during firing are simple and efficient, saving the step of manual point measurement with a total station.

[0073] The paper "Target Attitude Interpretation Processing Based on Optical Images," published in the journal Applied Optics, employs a binocular intersection method for data acquisition, followed by three interpretation processing methods: two-point-based, line-based, and model-based. This system uses single-site measurement, with the site including image acquisition and point cloud data acquisition. RTK measurement is incorporated for calibration, allowing parameters such as target attitude angles and firing angles to be imported into a three-dimensional plane (northeast-southeast), facilitating range verification. It also eliminates the need for dual-site deployment and communication connections required in binocular measurement. Furthermore, point cloud acquisition provides more efficient and accurate extraction of the target's centerline than image-based interpretation.

[0074] In her doctoral dissertation, "Research on LiDAR Range Image Target Recognition Algorithm Based on Point Normal Vector Attitude Estimation," Lü Dan only used point cloud multi-angle acquisition for attitude measurement. This system uses point cloud and image fusion for measurement, and incorporates RTK equipment for calibration. The point cloud coordinate system and the northeast-sky coordinate system are mutually converted using image calibration, which can introduce the target's attitude angle, firing angle and other parameters into the northeast-sky three-dimensional plane, facilitating the verification of the target range.

[0075] In summary, this system abandons the traditional binocular image intersection measurement method and adopts a single station to quickly measure parameters such as the firing angle, attitude angle and firing velocity based on the northeast-northeast coordinate system in real time. The single station includes point cloud and image acquisition modules, and introduces the RTK calibration method to establish mutual conversion relationships between the coordinate system of the point cloud, the camera coordinate system and the northeast-northeast coordinate system.

[0076] like Figure 2 As shown, a method for measuring the real-time muzzle velocity of a projectile and the attitude of a gun barrel includes the following steps:

[0077] Step S1: System Setup

[0078] Set up and fix the industrial control computer, and connect and fix the wireless communication module and UPS module that work with it; set up and fix the muzzle acquisition unit, and connect and fix the wireless communication module, UPS module and timing module that work with it; set up and fix the positioning base station, and put it into base station mode;

[0079] Step S2: Calculate camera intrinsic parameters and camera extrinsic parameter calibration files.

[0080] The checkerboard calibration board is moved back and forth and left and right within the field of view of the high-speed camera and the lidar. The high-speed camera and lidar collect and record each fixed point, and save the image and point cloud data of the corresponding point. The algorithm identifies the position of the checkerboard calibration board in real time, and manually identifies the checkerboard point cloud data. There are more than 20 pairs. The camera intrinsic parameters of the high-speed camera and the camera extrinsic parameters of the conversion relationship between the high-speed camera and the lidar are calculated.

[0081] Step S3: Calculate the calibration file for the camera coordinate system and the northeast-sky coordinate system.

[0082] The RTK drone is moved forward, backward, left, and right within the field of view of the high-speed camera. The industrial control computer receives the positioning information of the RTK drone in real time. The industrial control computer matches the image and positioning data according to the timestamp information. The RTK drone flies near the center of the image for 5 minutes, then ends the flight and calculates the transformation relationship between the camera coordinate system and the northeast-sky coordinate system.

[0083] Step S4: Calculate the firing direction and angle of the gun barrel.

[0084] The checkerboard calibration board and RTK UAV are removed, the lidar scans the point cloud data of the gun barrel, and the firing direction and firing angle representing the gun barrel attitude are calculated according to the conversion relationship in steps S2 and S3.

[0085] Step S5: Calculate the real-time muzzle velocity of the projectile.

[0086] The high-speed camera is put into high-speed acquisition mode. At this time, the shell is launched and the high-speed camera acquires and records image data at high speed. According to the barrel attitude in step S4, the image perspective is transformed to a plane perpendicular to the optical center of the high-speed camera. The real-time muzzle velocity of the shell is calculated by using the distance and time between multiple frames.

[0087] Step S6: Continuously calculate the barrel attitude and the real-time muzzle velocity of the next projectile.

[0088] After the current shell is fired, the lidar collects the point cloud data of the barrel in real time, updates the barrel's attitude in real time, recalculates the barrel's firing direction and firing angle, and repeats step S5 to calculate the real-time muzzle velocity of the next shell.

[0089] Step S7: End the data collection and retrieve the equipment.

[0090] By adopting the above technical solution, since the measured gun barrel direction and angle, and the real-time muzzle velocity of the projectile are all established in the Northeast-Eastern Sky coordinate system, the camera intrinsic parameters of the high-speed camera and the camera extrinsic parameters of the conversion relationship between the high-speed camera and the lidar, as well as the conversion relationship between the camera coordinate system and the Northeast-Eastern Sky coordinate system, can be calculated first. In this way, the lidar coordinate system, the camera coordinate system of the high-speed camera, and the Northeast-Eastern Sky coordinate system can be linked together, and the observed and recorded data can be uniformly transferred to the Northeast-Eastern Sky coordinate system to calculate the gun barrel direction and angle, and the real-time muzzle velocity of the projectile.

[0091] like Figure 3 As shown, in steps S2 and S3, the output information of the high-speed camera and the lidar contains absolute timestamp information assigned by the GPS timing module. At the same time, the positioning data based on the GNGGA protocol transmitted back by the RTK UAV also contains absolute timestamp information. The industrial control computer retrieves the same timestamp as a pair of data for pairing and parsing among the high-speed camera, lidar and RTK UAV, for use in the inversion calculation during calibration.

[0092] By adopting the above technical solution, the timestamps of the high-speed camera image, the lidar point cloud timestamp, and the RTK drone satellite (GNGGA) protocol can be matched and aligned. In this way, as long as the same timestamp is found, the data at the same moment can be known, which facilitates pairing and parsing by the industrial control computer.

[0093] like Figure 4 As shown, after receiving B-code time synchronization from the timing module, the high-speed camera adopts the BeiDou satellite reference time and receives the 1PPS signal from the BeiDou satellite. When the high-speed camera receives the trigger signal, it starts high-speed image acquisition from the next whole second. At the same time, the positioning module in the RTK UAV also receives the 1PPS signal from the BeiDou satellite and outputs the differential positioning data of the RTK UAV based on the GNGGA protocol every 100ms starting from the whole second.

[0094] By adopting the above technical solutions, such as setting the frame rate of the high-speed camera to 100fps, the high-speed camera will always have timestamp images of 100ms, 200ms, 300ms... in the acquired images. The above method can realize the synchronization of the image timestamp and the positioning information timestamp. In this way, once the actual RTK drone's location information is determined, the corresponding image in the high-speed camera can be found, and the location of the corresponding RTK drone can be found through image analysis.

[0095] like Figure 1 and 2 As shown, in step S3, the extraction of pixel coordinates of the RTK drone needs to go through three stages: discovery, tracking, and filtering. The specific steps are as follows:

[0096] Step S3.1: Process the first 10 frames of the image sequence using the frame difference method to segment the moving targets in the video;

[0097] Step S3.2: Using the RTK UAV target extracted in step S3.1 as a template, the optical flow method is used to continuously track the UAV target to obtain the target's coordinate sequence p. l and p r Confidence sequence C l and C r ;

[0098] Step S3.3: Set the confidence threshold C T Filter coordinate sequences p where both left and right confidence scores are greater than the threshold. l ′ and p r ′.

[0099] By adopting the above technical solution, in step S3.1, due to the presence of interference factors such as birds and image noise, there is more than one moving target obtained by segmentation. However, these interference sources differ from the real RTK drone target in dimensions such as target size, motion pattern, and brightness level. The real RTK drone target can be extracted by utilizing this difference.

[0100] The above describes the extraction method under normal circumstances. When the number of pixels occupied by the RTK drone in the image is small, generally not exceeding 30 pixels, it is difficult to extract feature corner points for stable tracking. The method added in this invention is to add a color dimension and extract the color histogram of the RTK drone to extract pixel coordinates and achieve stable tracking. The color histogram is calculated by statistically analyzing the values ​​of the three color channels BGR of the RTK drone region and their occurrences to form a histogram of the three colors BGR. The coordinates that match the histogram are then found in the image captured by the high-speed camera.

[0101] like Figure 5 and 6 As shown, in step S3, the latitude and longitude of the RTK UAV need to be converted to the northeast-northeast coordinate system. The distance from the RTK UAV to the reference ellipsoid is h, and the following relationship must be satisfied:

[0102] h = H + N

[0103] Where H is altitude and N is geoid difference; both H and N can be obtained from RTK UAV data; then, the latitude and longitude are converted to the northeast-northeast coordinate system according to the following formula:

[0104]

[0105] Here, Δ refers to the offset relative to the reference origin.

[0106] By adopting the above technical solution, the data obtained from the RTK UAV includes timestamp, longitude, latitude, altitude (H), and geoid difference (N). The above coordinate data is based on the WGS84 coordinate system. Since longitude and latitude belong to the polar coordinate system, while the camera coordinate system belongs to the rectangular coordinate system, the longitude and latitude need to be converted to the NAU coordinate system (rectangular coordinate system) before they can be used for calibration. Before converting the longitude and latitude to the NAU coordinate system, the distance h from the RTK UAV to the reference ellipsoid needs to be known.

[0107] like Figure 7 As shown, in step S2, the calibration formula for calculating the camera intrinsic parameters and the camera extrinsic parameters that determine the conversion relationship between the high-speed camera and the lidar is as follows:

[0108]

[0109]

[0110] In the above formula, R = [R x R y R z ], T = [t x t y t z ] T , respectively, are the rotation matrix R and translation matrix T of the extrinsic parameters, and matrix K is the intrinsic parameter; f x =f / dx, f y = f / dy, where f is the focal length of the high-speed camera, and dx*dy is the physical size of each pixel in the sensor of the high-speed camera, (X w ,Y w Z w Z is the world coordinate system, (u,v) is the pixel coordinate system for interpreting the RTK UAV in the image, and Z is the world coordinate system. C For the camera coordinate system (X) c ,Y c Z c In the equation, s represents the distance component of the object along the direction of the optical center, and s is the tilt between the camera target and the lens.

[0111] like Figure 1 As shown, the derivation formula for calculating the transformation relationship between the camera coordinate system and the northeast-sky coordinate system in step S3 is as follows:

[0112]

[0113] In the above formula, the real-time latitude and longitude output by the RTK drone is converted into (X... w ,Y w Z w );

[0114] Once the RTK drone is detected as being located at the center of the image, its latitude, longitude, and coordinates (X1, Y1, Z1) are recorded. C The value is There are 9 unknowns in R, and 8 unknowns considering rotation consistency. There are 3 unknowns in T. One coordinate point can provide 2 equations. That is, by finding 6 points at different depths located at the center of the image, the R and T matrices can be solved, which can be used as the transformation matrix from the camera coordinate system to the northeast-sky coordinate system.

[0115] By adopting the above technical solution, the coordinate transformation relationship between the high-speed camera and the lidar can be obtained through a checkerboard calibration board. The transformation relationship between the camera coordinate system and the northeast-sky coordinate system needs to be calculated using an RTK drone. The system of this invention uses only one high-speed camera and one lidar; the RTK drone can provide latitude, longitude, and altitude, which, after being converted to the northeast-sky coordinate system, serves as the world coordinate system (X). w ,Y w Z w This involves determining the transformation relationship between the specific single-camera coordinate system and the northeast-sky coordinate system, i.e., solving for the extrinsic parameters of the high-speed camera relative to the northeast-sky coordinate system. A similar derivation can be performed using the coordinate transformation relationship between the high-speed camera and the lidar.

[0116] In the above formula, the camera intrinsic parameters have already been calculated in the previous step when solving for the coordinate transformation between the high-speed camera and the lidar. The camera extrinsic parameters are the transformation relationship between the camera coordinate system and the northeast-sky coordinate system to be calculated, involving rotation and translation. c Let u and v be the distance components of the object along the optical center in the camera coordinate system. u and v are the pixel coordinates of the RTK drone in the image, and the drone's real-time output latitude and longitude are converted to (X...) coordinates. w ,Y w Z w Therefore, the key to solving the rotation matrix R and translation T lies in Z. c Data Acquisition. In actual drone flights, personnel first bring the RTK drone close to the camera and record its latitude, longitude, and coordinates (X0, Y0, Z0) in the northeast sky. After the drone takes off, personnel preview the acquired images in real time, and the drone flies at different depths around the center of the image.

[0117] like Figure 8 As shown, in step S4, the firing angle is the angle between the gun barrel vector and the northeast plane in the northeast-northeast coordinate system, denoted as α; the firing direction is the angle between the projection vector of the gun barrel vector onto the northeast plane in the northeast-northeast coordinate system and the due north direction, denoted as β.

[0118] To calculate the firing angle and direction, the gun barrel's attitude must first be transformed to the northeast-central coordinate system. The transformation relationship from the radar coordinate system to the camera [R1, T1] and from the camera to the northeast-central coordinate system [R2, T2] can be obtained. Using a lidar, the gun barrel's axis vector in the radar coordinate system can be obtained as S1, and the axis vector in the northeast-central coordinate system is S2 = [R1, Y1].S1[R2, Y2]. From this, the firing angle and direction can be calculated. Assuming S2 calculates the gun barrel's vector (X... p ,Y p Z p If the angle and direction of the shot are given, then the formulas for calculating them are as follows:

[0119]

[0120]

[0121] like Figure 1 As shown, in step S5, before firing the shell, the number of pixels C occupied by a fixed length L in the front view is measured; after perspective change, at a certain moment, the image pixel of the shell in the front view is located at (x1, y1), after time T0 it is located at image pixel (x2, y2), and after time T1 it is located at image pixel (x3, y3). Then the initial velocity of the shell leaving the barrel is:

[0122]

[0123] By employing the above technical solution, a checkerboard pattern or other markers are placed parallel to the gun barrel. In the image near the gun barrel, the four vertices of the checkerboard pattern or markers are recorded as (x1, x2, x3, x4). The checkerboard pattern is then moved to the front of the camera, and the corresponding four vertices in the acquired image are (y1, y2, y3, y4). The perspective transformation matrix H is then calculated.

[0124]

[0125] u and v represent the left side of the original image, corresponding to the coordinates x and y of the transformed image, where x = x′ / w′ and y = y′ / w′.

[0126] Transformation matrix It can be divided into 4 parts. It represents linear transformations, such as scaling, shearing, and rotation.

[0127] [a 31 a 32 [a] is used for translation. 13 a 23 ] TThis results in perspective transformation. Therefore, affine transformations can be understood as special forms of perspective transformation. Images transformed by perspective are usually not parallelograms (unless the mapped view plane is parallel to the original plane).

[0128] When acquiring actual gun barrel images, applying the H matrix to the actual gun barrel images can transform the gun barrel in the images to a frontal view plane. Then, the firing rate is calculated using a single-camera pixel size calibration method.

[0129] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A measurement system for real-time muzzle velocity of projectiles and barrel attitude, characterized in that, The measurement system includes: Industrial control computers; The muzzle acquisition unit communicates with the industrial control computer via their respective wireless communication modules; the muzzle acquisition unit consists of a high-speed camera and a lidar, and the high-speed camera and lidar are synchronized through a timing module to ensure that their times are synchronized. The gun barrel is located within the field of view of the high-speed camera and lidar to measure its own attitude in real time. The RTK drone is equipped with a positioning module and a wireless communication module. The RTK drone can accurately locate itself by combining the positioning data sent by the positioning base station that is compatible with it, and can send its own positioning data to the industrial control computer in real time through its wireless communication module. The checkerboard calibration board, together with the RTK UAV, is used to calibrate and transform the coordinate relationship of the high-speed camera and the lidar. During the calibration process, both are located within the field of view of the high-speed camera and the lidar. The industrial computer and the muzzle acquisition unit are both powered by the UPS module. A method for measuring the real-time muzzle velocity and barrel attitude of a projectile using the aforementioned measurement system, the method comprising the following steps: Step S1: System Setup Set up and fix the industrial control computer, and connect and fix the wireless communication module and UPS module that work with it; set up and fix the muzzle acquisition unit, and connect and fix the wireless communication module, UPS module and timing module that work with it; set up and fix the positioning base station, and put it into base station mode; Step S2: Calculate camera intrinsic parameters and camera extrinsic parameter calibration files. The checkerboard calibration board is moved back and forth and left and right within the field of view of the high-speed camera and the lidar. The high-speed camera and lidar collect and record each fixed point, and save the image and point cloud data of the corresponding point. The algorithm identifies the position of the checkerboard calibration board in real time, and manually identifies the checkerboard point cloud data. There are more than 20 pairs. The camera intrinsic parameters of the high-speed camera and the camera extrinsic parameters of the conversion relationship between the high-speed camera and the lidar are calculated. Step S3: Calculate the calibration file for the camera coordinate system and the northeast-sky coordinate system. The RTK drone is moved forward, backward, left, and right within the field of view of the high-speed camera. The industrial control computer receives the positioning information of the RTK drone in real time. The industrial control computer matches the image and positioning data according to the timestamp information. The RTK drone flies near the center of the image for 5 minutes, then ends the flight and calculates the transformation relationship between the camera coordinate system and the northeast-sky coordinate system. Step S4: Calculate the firing direction and angle of the gun barrel. The checkerboard calibration board and RTK UAV are removed, the lidar scans the point cloud data of the gun barrel, and the firing direction and firing angle representing the gun barrel attitude are calculated according to the conversion relationship in steps S2 and S3. Step S5: Calculate the real-time muzzle velocity of the projectile. The high-speed camera is put into high-speed acquisition mode. At this time, the shell is launched and the high-speed camera acquires and records image data at high speed. According to the barrel attitude in step S4, the image perspective is transformed to a plane perpendicular to the optical center of the high-speed camera. The real-time muzzle velocity of the shell is calculated by using the distance and time between multiple frames. Step S6: Continuously calculate the barrel attitude and the real-time muzzle velocity of the next projectile. After the current shell is fired, the lidar collects the point cloud data of the barrel in real time, updates the barrel's attitude in real time, recalculates the barrel's firing direction and firing angle, and repeats step S5 to calculate the real-time muzzle velocity of the next shell. Step S7: End the data collection and retrieve the equipment.

2. The measurement system for real-time muzzle velocity of projectiles and barrel attitude according to claim 1, characterized in that: In steps S2 and S3, the output information of the high-speed camera and the lidar contains absolute timestamp information assigned by the GPS timing module. At the same time, the positioning data based on the GNGGA protocol transmitted back by the RTK UAV also contains absolute timestamp information. The industrial control computer retrieves the same timestamp as a pair of data for pairing and parsing among the high-speed camera, lidar and RTK UAV, for use in the inversion calculation during calibration.

3. The measurement system for real-time muzzle velocity of projectiles and barrel attitude according to claim 2, characterized in that: After receiving B-code time synchronization from the timing module, the high-speed camera adopts the BeiDou satellite reference time and receives the 1PPS signal from the BeiDou satellite. When the high-speed camera receives the trigger signal, it starts high-speed image acquisition from the next whole second. At the same time, the positioning module in the RTK UAV also receives the 1PPS signal from the BeiDou satellite and outputs the differential positioning data of the RTK UAV based on the GNGGA protocol every 100ms starting from the whole second.

4. The measurement system for real-time muzzle velocity of projectiles and barrel attitude according to claim 3, characterized in that: In step S3, the extraction of pixel coordinates from the RTK drone involves three stages: discovery, tracking, and filtering. The specific steps are as follows: Step S3.1: Process the first 10 frames of the image sequence using the frame difference method to segment the moving targets in the video; Step S3.2: Using the RTK UAV target extracted in step S3.1 as a template, the optical flow method is used to continuously track the UAV target to obtain the target's coordinate sequence. and Confidence sequence and ; Step S3.3: Set the confidence threshold Filter coordinate sequences where both left and right confidence scores are greater than the threshold. and .

5. The measurement system for real-time muzzle velocity of projectiles and barrel attitude according to claim 4, characterized in that: In step S3, the latitude and longitude of the RTK UAV need to be converted to the northeast-northeast coordinate system. The distance from the RTK UAV to the reference ellipsoid is h, and the following relationship must be satisfied: ； Where H is altitude and N is geoid difference; both H and N can be obtained from RTK UAV data; then, the latitude and longitude are converted to the northeast-northeast coordinate system according to the following formula: ； in, This refers to the offset relative to the reference origin.

6. The measurement system for real-time muzzle velocity of projectiles and barrel attitude according to claim 5, characterized in that: In step S2, the calibration formula for calculating the camera intrinsic parameters and the camera extrinsic parameters that determine the conversion relationship between the high-speed camera and the lidar is as follows: ； ； In the above formula, , , respectively, are the rotation matrix R and the translation matrix T of the extrinsic parameters, and the matrix It's an internal reference; , , It is the focal length of a high-speed camera. It refers to the physical size of each pixel in the image sensor of a high-speed camera. It is a world coordinate system. The image shows the pixel coordinate system for interpreting the RTK drone. Camera coordinate system The distance component of the object along the direction of the optical center. It refers to the tilt between the camera target surface and the lens.

7. The measurement system for real-time muzzle velocity of projectiles and barrel attitude according to claim 6, characterized in that: In step S3, the derivation formula for calculating the transformation relationship between the camera coordinate system and the northeast-sky coordinate system is as follows: ； In the above formula, the latitude and longitude output by the RTK drone are converted into... ; Once the RTK drone is detected as being in the center of the image, its latitude, longitude, and coordinates are recorded. ,but The value is There are 9 unknowns in R, and 8 unknowns considering rotation consistency. There are 3 unknowns in T. One coordinate point can provide 2 equations. That is, by finding 6 points at different depths located at the center of the image, the R and T matrices can be solved, which can be used as the transformation matrix from the camera coordinate system to the northeast-sky coordinate system.

8. The measurement system for real-time muzzle velocity of projectiles and barrel attitude according to claim 7, characterized in that: In step S4, the firing angle is the angle between the gun barrel vector and the northeast plane in the northeast-northeast coordinate system, denoted as α; the firing direction is the angle between the projection vector of the gun barrel vector onto the northeast plane in the northeast-northeast coordinate system and the due north direction, denoted as β. To calculate the firing angle and firing direction, the gun barrel attitude must first be converted to the northeast-central coordinate system to obtain the transformation relationship from the radar coordinate system to the camera. , Obtain the transformation relationship from the camera to the northeast celestial coordinate system. Using lidar, the axis vector of the gun barrel in the radar coordinate system can be obtained. The axis vector in the northeast-northeast coordinate system Therefore, its angle of attack and direction of attack can be calculated, assuming... The calculated vector of the gun barrel is as follows The formulas for calculating its angle of attack and direction of attack are as follows: ； 。 9. A measurement system for real-time muzzle velocity of projectiles and barrel attitude according to claim 8, characterized in that: In step S5, before firing the shell, the number of pixels C occupied by a fixed length L in the front view is measured; after perspective transformation, at a certain moment, the image pixel of the shell in the front view is located at (x1, y1), after time T0 it is located at image pixel (x2, y2), and after time T1 it is located at image pixel (x3, y3). The corresponding initial velocity of the shell leaving the barrel is: ( + ) / 2。

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