A surface-to-surface intersection measurement method for terminal trajectory parameters based on linear motion constraints

Abstract

The present invention provides a surface-to-surface intersection measurement method for terminal trajectory parameters based on linear motion constraints, comprising: using a gaze measurement method to capture and record terminal flight images of a flying target flying toward a target from different angles using at least two high-frame cameras; retrieving images of the flying target and the target in the same frame based on the terminal flight images, and replaying and outputting the encounter segment images as a real-time SDI video stream; reading multiple playback SDI video streams and performing real-time image interpretation using a target detection algorithm to obtain target interpretation data; filtering the interpretation data using a three-point random resampling method and performing angle synthesis to obtain target interpretation point data; and calculating the target interpretation point data using a surface-to-surface intersection algorithm based on linear motion constraints to obtain the terminal flight trajectory parameters of the flying target. The present invention can achieve rapid and accurate measurement of terminal trajectory parameters without the need for equipment time synchronization, and has a wide range of applications.

Description

Technical Field

[0001] The present invention relates to the field of optical measurement technology, and in particular to a surface-to-surface intersection measurement method for terminal trajectory parameters based on linear motion constraints. Background Art

[0002] Existing techniques for measuring target trajectory parameters employ post-processing high-precision optical intersection processing. Using two or more photoelectric theodolites to record target flight images and calculate the target's flight trajectory using angle intersection measurement is a typical optical measurement method, offering advantages such as high measurement accuracy and non-contact measurement. For measuring the terminal trajectory parameters, due to the target's high relative velocity and poor image quality near the ground due to atmospheric jitter, two high-speed cameras are typically deployed in a close-range, staring measurement setup to record high-frame-rate images of the target encounter segment. High-speed cameras typically use flash memory to store images. After stopping recording, key segment images are downloaded from the camera cache, and manual target interpretation is performed. The interpretation results include both the image miss distance of the target's feature points and the absolute time at which the frame was recorded. The intersection processing algorithm first pairs the interpretation points based on the absolute time. Then, a point-by-point least-squares intersection algorithm is used to calculate the target's spatial coordinates at each moment. Finally, the target space is fitted to obtain the terminal trajectory parameters.

[0003] However, the need to download images from the camera and manually interpret and intersect them afterwards results in slow data processing. Furthermore, traditional point-by-point intersection positioning methods require both cameras to have a common time base, placing high demands on camera time synchronization. These limitations place high demands on the image acquisition and recording hardware used in existing technologies, making it difficult to meet the demands for rapid measurement and evaluation.

[0004] Therefore, there is an urgent need for a terminal trajectory parameter measurement method that can reduce hardware requirements and meet the needs of rapid measurement and evaluation. Summary of the Invention

[0005] Based on this, it is necessary to provide a surface-to-surface intersection measurement method for the terminal trajectory parameters based on linear motion constraints to address the above technical problems.

[0006] A surface-to-surface intersection measurement method for terminal trajectory parameters based on linear motion constraints comprises the following steps: adopting a gaze measurement method, using at least two high-frame cameras to capture and record terminal flight images of a flying target flying toward a target from different angles; retrieving images of the flying target and the target in the same frame based on the terminal flight images, and replaying and outputting encounter segment images in the form of a real-time SDI video stream; reading multiple playback SDI video streams, and using a target detection algorithm to perform real-time image interpretation to obtain interpretation data of the flying target; using a three-point random resampling method to filter the interpretation data, and performing angle synthesis on the filtered interpretation data to obtain target interpretation point data; based on the linear motion constraint, using a surface-to-surface intersection algorithm to calculate the target interpretation point data to obtain terminal flight trajectory parameters of the flying target.

[0007] In one embodiment, the gaze measurement method is used to use at least two high-frame cameras to capture and record the final flight images of the flying target flying toward the target from different angles, including: when using two high-frame cameras, defining the layout points and target points of the first camera and the second camera, completing the station layout, and using the characteristic points and coordinates of the target to calibrate the parameters of the camera optical axis direction and dimension; using the gaze measurement method, based on the first camera and the second camera, using a high frame rate to record the encounter process images of the flying target and the target, and obtaining the final flight images of the flying target flying toward the target.

[0008] In one embodiment, the method comprises retrieving a same-frame image of the flying target and the target based on the last segment flight image, and replaying and outputting the encounter segment image in the form of a real-time SDI video stream, including: after the flying target and the target meet, the high-frame camera stops recording, and the image segment from the flying target entering the frame to the explosion is retrieved using storage recording software to obtain a same-frame image of the flying target and the target, performing slow playback at least three times, and outputting the playback video stream to the outside in the form of a real-time SDI video stream.

[0009] In one embodiment, the read data includes a device number, a frame number, a data valid flag, a target horizontal pixel miss amount, a target vertical pixel miss amount, a video stream image width, and a video stream image height.

[0010] In one embodiment, the three-point random resampling method is used to filter the judgment data, including: defining the number of resampling times n, the straight line fitting error threshold tol and the number of sampling points each time nc; expressing all the judgment data of the first camera as [dx1, dy1], and randomly selecting nc groups of judgment data therein , 1…nc represents the first to nc groups of interpretation data, As the independent variable, As the dependent variable, perform one-dimensional straight line fitting to obtain the fitted straight line t0; calculate the absolute distance di of each judgment point (dx1, dy1) in [dx1, dy1] relative to the straight line t0, and form a new judgment point set with di < tol , s represents the sth interpretation point, and the number of interpretation points contained in the interpretation point set is defined as T1; the step of randomly selecting nc groups of interpretation data to obtain a new interpretation point set is repeated n times to obtain n new interpretation point sets , where the number of reading points contained in each set of reading points constitutes an array [T1, T2, T3,…Tn]; find the maximum value in [T1, T2, T3,…Tn], defined as T ns , the corresponding judgment point set is , That is, the judgment point data obtained by filtering the judgment data of the first camera; the judgment data of the second camera is processed in the same way to obtain the judgment point data obtained by filtering the judgment data of the second camera.

[0011] In one embodiment, the angle synthesis of the filtered interpretation data to obtain target interpretation point data includes: defining the image resolution of the SDI video stream as [H sdi ,W sdi ], the original image resolution is [H bmp ,W bmp ] and the camera dimension calculated based on the original image is [LGx bmp ,LGy bmp ]; define the corrected interpretation data of the first camera as [dx s1 ,dy s1 ], then:

[0012] ;

[0013] ;

[0014] Convert the pixel miss amount into the target pointing angle for angle synthesis, and define the optical axis direction of the first camera as [A 1axis ,E 1axis ], the miss angle corrections for azimuth and elevation are dA1 and dE1 respectively, then:

[0015] ;

[0016] The target pitch angle after angle integration is:

[0017] ;

[0018] The azimuth miss correction is:

[0019] ;

[0020] The target azimuth after angle integration is:

[0021] ;

[0022] Based on the same method, the target pointing angle measured by the second camera is obtained [A 20 ,E 20 ]; According to the target pointing angles of the first camera and the second camera, the corresponding target judgment point data are obtained respectively.

[0023] In one embodiment, the target interpretation point data is calculated based on the linear motion constraint using a surface intersection algorithm to obtain the terminal flight trajectory parameters of the flying target, including: establishing a local rectangular coordinate system with the center of the target as the coordinate origin, the station coordinates of the first camera and the second camera in the local rectangular coordinate system are [x1, y1, z1] and [x2, y2, z2] respectively, and the corresponding target pointing angles are [A 10 ,E 10 ] and [A 20 ,E 20 ];definition , construct the point coordinate data set located on the plane formed by the target linear motion trajectory and the first camera station coordinates, which is:

[0024] ;

[0025] According to the intercept equation of the plane, the points in the point coordinate data set satisfy:

[0026] ;

[0027] Where a1, b1, and c1 are the intercepts of the plane formed by the target linear motion trajectory and the coordinates of the first camera station on the three axes of the local rectangular coordinate system:

[0028] ;

[0029] Where B is a vector with the same number of rows as xyz01, 1 column, and all elements are 1. T is the transpose of matrix xyz01;

[0030] Construct two vectors lying on the xyz01 plane and , by cross-producting the two vectors, we can obtain the normal vector direction ABC1 of the plane formed by the target linear motion trajectory and the coordinates of the first camera station. The formula is:

[0031] ;

[0032] Define ABC1=[A1,B1,C1], the equation of the plane is:

[0033] ;

[0034] Where, ;

[0035] The same method is used to obtain the normal vector direction number ABC2=[A1, B1, C1] of the plane formed by the target linear motion trajectory and the second camera station coordinates, and the equation of the corresponding plane is obtained as follows:

[0036] ;

[0037] Where D2=-ABC2∙[x2,y2,z2]; by combining the equations of the two planes, we get the intersection equation of the linear motion trajectory L, and the direction number W=[p,q,r] of the linear motion trajectory is obtained as follows:

[0038] ;

[0039] According to the direction number of the linear motion trajectory L, the terminal flight trajectory parameters of the flying target are obtained.

[0040] Compared with the prior art, the advantages and beneficial effects of the present invention are as follows: by adopting a gaze measurement method, based on at least two high-frame cameras, recording the final flight images of a flying target flying toward a target from different angles, and retrieving the frame images of the flying target and the target in the same frame, and replaying and outputting the encounter segment images in the form of a real-time SDI video stream; reading multiple playback SDI video streams, and adopting a target detection algorithm to perform real-time image interpretation to obtain the interpretation data of the flying target, adopting a three-point random resampling method to filter the interpretation data, and performing dimension correction and angle synthesis on the filtered interpretation data to obtain target interpretation point data, based on the linear motion constraint, adopting a face-to-face intersection algorithm to calculate the target interpretation point data to obtain the final flight trajectory parameters of the flying target, thereby avoiding the time synchronization requirements of the traditional algorithm for the camera, and realizing fast and accurate measurement of the final trajectory parameters, having strong operability, and being widely applicable to a variety of high-frame-rate gaze intersection measurement systems, and having a wide range of applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 1 is a flow chart of a method for measuring terminal trajectory parameters by surface-to-surface intersection based on linear motion constraints in one embodiment;

[0042] Figure 2 The present invention is a flowchart of a surface-to-surface intersection measurement method for terminal trajectory parameters based on linear motion constraints in one embodiment. DETAILED DESCRIPTION

[0043] Before describing the specific embodiments of the present invention, the overall concept of the present invention is described as follows:

[0044] The present invention is mainly developed based on the target trajectory parameter measurement process. The current measurement method of the terminal trajectory parameters has high requirements on the image acquisition and recording hardware, and it is difficult to meet the needs of rapid measurement and evaluation.

[0045] Therefore, the present invention proposes a surface intersection measurement method for terminal trajectory parameters based on linear motion constraints. By adopting a gaze measurement method, at least two high-frame cameras are used to shoot and record the terminal flight images of a flying target flying toward a target from different angles, and the frame images of the flying target and the target in the same frame are retrieved, and the encounter segment images are played back and output in the form of real-time SDI video stream. The key segment video stream output by the automatic interpretation camera playback is adopted, which greatly compresses the time consumption of high-frame rate image downloading and manual interpretation and improves the data processing speed; reads the multi-channel playback SDI video stream, and adopts the target detection algorithm to perform real-time image interpretation to obtain the interpretation data of the flying target, and adopts the target detection algorithm to perform real-time image interpretation. The three-point random resampling method is used to filter the interpretation data, filtering out the abnormal interpretation point data and reducing the impact of the automatic interpretation outlier error on the intersection result; the filtered interpretation data is dimensionally corrected and angle integrated to obtain the target interpretation point data, ensuring the accuracy of the pointing angle of the automatic image interpretation result based on the video stream; based on the linear motion constraint, the surface-to-surface intersection algorithm is used to calculate the target interpretation point data to obtain the terminal flight trajectory parameters of the flying target, thereby avoiding the traditional algorithm's requirement for camera time synchronization and achieving rapid and accurate measurement of the terminal trajectory parameters. It has strong operability and can be widely applied to a variety of high-frame-rate staring intersection measurement systems, with a wide range of applications.

[0046] After introducing the overall concept of the present invention, in order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below through specific embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0047] In one embodiment, Figure 1 As shown, a surface-to-surface intersection measurement method for terminal trajectory parameters based on linear motion constraints is provided, comprising the following steps:

[0048] Step S110 , using a gaze measurement method, using at least two high-frame cameras to capture the final flight image of the flying object flying towards the target from different angles.

[0049] Specifically, in order to better measure the target flight trajectory, a staring measurement method is adopted, using at least two high-frame cameras to capture the final flight image of the flying target flying towards the target from different angles to obtain a high-frame rate final flight image.

[0050] Among them, step S110 includes: when using two high-frame cameras, defining the layout points and target points of the first camera and the second camera, completing the station layout, and using the characteristic points and coordinates of the target to calibrate the parameters of the camera optical axis direction and dimension; using the gaze measurement method, based on the first camera and the second camera, using a high frame rate to record the encounter process image of the flying target and the target, and obtain the final flight image of the flying target flying towards the target.

[0051] Specifically, the first camera layout point is defined as , the second camera is set at , the target point is After the station is deployed, the target's characteristic points and their coordinates are used to calibrate the camera's optical axis direction and dimension parameters. Using a gaze measurement method, the first and second cameras record the encounter process between the flying target and the target at a high frame rate, obtaining images of the final stage of the flight as the target flies toward the target, achieving fast, high-frame-rate imaging.

[0052] Step S120 , searching for images of the flight target and the target in the same frame based on the final flight image, and playing back and outputting the encounter segment images in the form of real-time SDI video stream.

[0053] Specifically, the final flight image obtained by the high-frame camera is retrieved to obtain a frame image of the flying target and the target in the same frame, and the encounter segment image of the flying target and the target is played back and output in real time in the form of an SDI video stream, realizing efficient, stable and high-quality video transmission. This enables the automatic interpretation of the key segment video stream output by the camera playback, greatly compressing the time consumption of high-frame rate image downloading and manual interpretation, and improving the data processing speed.

[0054] Among them, step S120 includes: after the flying target meets the target, the high-frame camera stops recording, and the image segment from the flying target entering the frame to the explosion is retrieved using storage recording software to obtain a frame image of the flying target and the target in the same frame, and slow playback is performed at least three times, and the playback video stream is output to the outside in the form of a real-time SDI video stream.

[0055] Specifically, after the flying target encounters the target, the high-frame camera stops recording, and the storage recording software is used to retrieve the image segment from the target entering the frame to the explosion for slow playback, and the playback video stream is output to the outside in the form of an SDI video stream. During playback, at least three slow playbacks are performed to ensure that sufficient target judgment point data is collected, and the playback video stream is output to the outside in the form of a real-time SDI video stream, thereby improving measurement efficiency.

[0056] Step S130 , reading the multi-channel playback SDI video streams, and using the target detection algorithm to perform real-time image interpretation to obtain the interpretation data of the flying target.

[0057] Specifically, the SDI video streams output by multiple high-frame cameras are read, and target detection algorithms, such as background modeling and Yolo algorithm, are used to perform real-time image interpretation to obtain the interpretation data of the flying target for subsequent trajectory parameter calculation.

[0058] The read data includes device number, frame number, data valid flag, target horizontal pixel miss amount, target vertical pixel miss amount, video stream image width and video stream image height.

[0059] In step S140, the three-point random resampling method is used to filter the interpretation data, and the filtered interpretation data is angle-integrated to obtain target interpretation point data. Based on the linear motion constraint, the surface-to-surface intersection algorithm is used to calculate the target interpretation point data to obtain the terminal flight trajectory parameters of the flying target.

[0060] Specifically, after receiving the interpretation data and finishing playback of the SDI video stream, data reception is stopped. In order to reduce the influence of the automatic interpretation abnormal numerical error on the intersection result, the multi-channel data is filtered separately based on the straight line trajectory fitting of three-point random resampling to eliminate the interpretation noise and realize the filtering of the abnormal interpretation point data; and the interpretation data after multi-channel filtering are angle-integrated to ensure the accuracy of the flight trajectory data; based on the constraint of linear motion, the interpretation data after multi-channel filtering are integrated, and the surface-to-surface intersection algorithm is used to calculate the terminal flight trajectory parameters of the flying target, thereby eliminating the time synchronization requirement of multiple cameras required by traditional algorithms, having strong operability, and being widely applicable to various existing high-frame-rate optical staring intersection measurement systems, with wide applicability.

[0061] The steps of filtering the interpreted data are as follows: define the number of resampling times n, the straight line fitting error threshold tol and the number of sampling points nc each time; express all interpreted data of the first camera as [dx1,dy1], and randomly select nc groups of interpreted data. , 1…nc represents the first to nc groups of interpretation data, As the independent variable, As the dependent variable, perform one-dimensional straight line fitting to obtain the fitted straight line t0; calculate the absolute distance di of each judgment point (dx1, dy1) in [dx1, dy1] relative to the straight line t0, and form a new judgment point set with di < tol , s represents the sth interpretation point, and the number of interpretation points contained in the interpretation point set is defined as T1; the step of randomly selecting nc groups of interpretation data to obtain a new interpretation point set is repeated n times to obtain n new interpretation point sets , where the number of reading points contained in each set of reading points constitutes an array [T1, T2, T3,…Tn]; find the maximum value in [T1, T2, T3,…Tn], defined as T ns , the corresponding judgment point set is , That is, the judgment point data obtained by filtering the judgment data of the first camera; the judgment data of the second camera is processed in the same way to obtain the judgment point data obtained by filtering the judgment data of the second camera.

[0062] Specifically, define the number of resampling times n=1000 times, define the straight line fitting error threshold tol=1, and define the number of sampling points each time nc=3. The following is an explanation based on one-way judgment data:

[0063] Step 1: Randomly select nc groups of interpretation result data from all the interpretation data [dx1,dy1] of the first camera , 1…nc represents the first to nc groups of interpretation data;

[0064] Step 2: As the independent variable, As the dependent variable, perform one-dimensional straight line fitting to obtain the fitting line t0;

[0065] Step 3: Calculate the absolute distance di from each judgment point (dx1, dy1) in [dx1, dy1] to the line t0, and filter out all judgment points that satisfy di<tol , s represents the sth judgment point, and a new judgment point set is constructed , the number of judgment points contained in this set is defined as T1;

[0066] Step 4: Repeat steps 1 to 3 n times to obtain n new sets of judgment points, defined as , where the number of reading points contained in each set of reading points constitutes an array [T1, T2, T3,…Tn]; find the maximum value in [T1, T2, T3,…Tn], defined as T ns , and its corresponding judgment point set is , That is, the judgment point data obtained by filtering based on the judgment result of the first camera.

[0067] The second camera's interpretation data is processed in the same way as above, and we get That is, the judgment point data obtained by filtering based on the judgment result of the second camera.

[0068] The step of performing angle synthesis on the filtered interpretation data to obtain target interpretation point data includes: defining the image resolution of the SDI video stream as [H sdi ,W sdi ], the original image resolution is [H bmp ,W bmp ] and the camera dimension calculated based on the original image is [LGx bmp ,LGy bmp ]; define the corrected interpretation data of the first camera as [dx s1 ,dy s1 ], then:

[0069] ;

[0070] ;

[0071] Convert the pixel miss amount into the target pointing angle for angle synthesis, and define the optical axis direction of the first camera as [A 1axis ,E 1axis ], the miss angle corrections for azimuth and elevation are dA1 and dE1 respectively, then:

[0072] ;

[0073] The target pitch angle after angle integration is:

[0074] ;

[0075] The azimuth miss correction is:

[0076] ;

[0077] The target azimuth after angle integration is:

[0078] ;

[0079] Based on the same method, the target pointing angle measured by the second camera is obtained [A 20 ,E 20 ]; According to the target pointing angles of the first camera and the second camera, the corresponding target judgment point data are obtained respectively.

[0080] Specifically, since the original image resolution recorded by the camera is inconsistent with the image resolution of the SDI video stream output by the camera, and the camera's dimensional parameters are usually obtained based on the original image interpretation, it is necessary to perform dimensional correction and angle synthesis on the obtained interpretation data. The video stream interpretation data and the original dimensional ratio correction method are used to perform angle synthesis on the interpretation results based on the video stream, so as to obtain the corresponding target interpretation point data and ensure the accuracy of the pointing angle of the automatic image interpretation results based on the video stream.

[0081] The steps for obtaining the final flight trajectory parameters of the flight target specifically include: establishing a local rectangular coordinate system with the center of the target as the origin, the station coordinates of the first camera and the second camera in the local rectangular coordinate system are [x1, y1, z1] and [x2, y2, z2] respectively, and the corresponding target pointing angles are [A 10 ,E 10 ] and [A 20 ,E 20 ];definition , construct the point coordinate data set located on the plane formed by the target linear motion trajectory and the first camera station coordinates, which is:

[0082] ;

[0083] According to the intercept equation of the plane, the points in the point coordinate data set satisfy:

[0084] ;

[0085] Where a1, b1, and c1 are the intercepts of the plane formed by the target linear motion trajectory and the coordinates of the first camera station on the three axes of the local rectangular coordinate system:

[0086] ;

[0087] Where B is a vector with the same number of rows as xyz01, 1 column, and all elements are 1. T is the transpose of matrix xyz01; construct two vectors located on the xyz01 plane and , by cross-producting the two vectors, we can obtain the normal vector direction ABC1 of the plane formed by the target linear motion trajectory and the coordinates of the first camera station. The formula is:

[0088] ;

[0089] Define ABC1=[A1,B1,C1], the equation of the plane is:

[0090] ;

[0091] Where, ;

[0092] The same method is used to obtain the normal vector direction number ABC2=[A2, B2, C2] of the plane formed by the target linear motion trajectory and the second camera station coordinates, and the equation of the corresponding plane is obtained as follows:

[0093] ;

[0094] Where D2=-ABC2∙[x2,y2,z2]; by combining the equations of the two planes, we get the intersection equation of the linear motion trajectory L, and the direction number W=[p,q,r] of the linear motion trajectory is obtained as follows:

[0095] ;

[0096] According to the direction number of the linear motion trajectory L, the terminal flight trajectory parameters of the flying target are obtained.

[0097] Specifically, based on the target linear motion constraint, the planes formed by the target linear motion trajectory and the coordinates of the two cameras are constructed respectively, and the normal vectors of the two planes are solved respectively to construct the intersection equation of the target linear motion trajectory, thereby obtaining the direction vector of the target motion straight line, and then obtaining the terminal trajectory parameters such as trajectory inclination angle and miss distance. This avoids the time synchronization requirement of the equipment and can realize the rapid measurement and processing of the terminal trajectory parameters. It has strong operability and wide applicability.

[0098] According to the number of directions of the linear motion trajectory L, the parameters such as the target terminal flight trajectory inclination and miss distance can be obtained. For example, the trajectory inclination is defined as the angle [jx, jy, jz] between the straight line L and the three axes of the local rectangular coordinate system, then:

[0099] .

[0100] In this embodiment, by adopting a gaze measurement method, at least two high-frame cameras are used to shoot and record the final flight images of the flying target flying towards the target from different angles, and the frame images of the flying target and the target in the same frame are retrieved, and the encounter segment images are played back and output in the form of a real-time SDI video stream; the multi-channel replayed SDI video streams are read, and the target detection algorithm is used to perform real-time image interpretation to obtain the interpretation data of the flying target, the interpretation data is filtered by a three-point random resampling method, and the filtered interpretation data is dimensionally corrected and angle-integrated to obtain the target interpretation point data, and based on the linear motion constraint, the surface-to-surface intersection algorithm is used to calculate the target interpretation point data to obtain the final flight trajectory parameters of the flying target, thereby avoiding the time synchronization requirements of the traditional algorithm for the camera, and realizing fast and accurate measurement of the final trajectory parameters, having strong operability and being widely applicable to a variety of high-frame-rate gaze intersection measurement systems, and having a wide range of applications.

[0101] In one embodiment, Figure 2 As shown, the present invention adopts a gaze measurement method, using two high-frame-rate cameras to capture and record the final flight images of a high-speed moving target flying towards a target from two different angles; after the target encounters the target, the target and target images recorded by the camera are quickly retrieved, and the encounter segment images are played back and output in the form of a real-time SDI video stream; the real-time interpretation module reads the two-way playback SDI video stream, performs real-time image interpretation to obtain the target image miss amount, and uses UDP communication to send the image miss amount in real time to the intersection processing module; the intersection processing module receives the two-way target interpretation result data in real time, uses a three-point random resampling method to filter the interpretation data, and uses a surface-to-surface intersection algorithm based on the target straight-line flight assumption to calculate the target final flight trajectory parameters.

[0102] Through the above steps, the method of automatically interpreting the key segment video stream of the camera playback output reduces the time consumed by downloading high-frame-rate images and manual interpretation. Dimensional correction and three-point resampling data filtering are used to ensure the quality of the automatically interpreted data. Based on the target's linear motion constraints, a surface-to-surface intersection algorithm is employed, eliminating the traditional requirement for time synchronization between the two cameras. Ultimately, this method achieves rapid measurement and processing of terminal trajectory parameters. This method is highly operational and widely applicable, and can be widely applied to various existing high-frame-rate optical staring intersection measurement systems. For example, it can be used in the field to rapidly process the terminal trajectory parameters of high-speed flying projectiles.

[0103] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0104] Obviously, those skilled in the art will appreciate that the various modules or steps of the present invention described above can be implemented using a general-purpose computing device. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they can be implemented using program code executable by the computing device, which can then be stored in a computer storage medium (ROM / RAM, magnetic disk, optical disk) and executed by the computing device. In some cases, the steps shown or described herein can be performed in a different order than that shown, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Therefore, the present invention is not limited to any particular combination of hardware and software.

[0105] The above content is a further detailed description of the present invention in conjunction with specific embodiments, and the specific implementation of the present invention cannot be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A surface-to-surface intersection measurement method for terminal trajectory parameters based on linear motion constraints, characterized in that: The following steps are involved: Using the staring measurement method, at least two high-frame cameras are used to capture and record the final flight images of the flying target from different angles. Retrieving the same-frame image of the flight target and the target according to the final flight image, and replaying and outputting the encounter segment image in the form of a real-time SDI video stream; Read multiple playback SDI video streams and use target detection algorithms to perform real-time image interpretation to obtain flight target interpretation data; The three-point random resampling method is used to filter the judgment data, and the filtered judgment data is angle-integrated to obtain target judgment point data. Based on the linear motion constraint, the surface-to-surface intersection algorithm is used to calculate the target judgment point data to obtain the terminal flight trajectory parameters of the flying target.

2. The surface intersection measurement method for terminal trajectory parameters based on linear motion constraints according to claim 1 is characterized in that: The gaze measurement method is used to use at least two high-frame cameras to capture and record the final flight images of the flying target flying towards the target from different angles, including: When using two high-frame cameras, define the layout points and target points of the first and second cameras, complete the station layout, and use the target's feature points and coordinates to calibrate the camera optical axis direction and dimension parameters; A gaze measurement method is adopted, based on the first camera and the second camera, and images of the encounter process between the flying target and the target are recorded at a high frame rate to obtain a final flight image of the flying target flying towards the target.

3. The surface intersection measurement method for terminal trajectory parameters based on linear motion constraints according to claim 1 is characterized in that: The method of retrieving the same-frame image of the flight target and the target according to the final flight image, and replaying and outputting the encounter segment image in a real-time SDI video stream, includes: After the flying target encounters the target, the high-frame camera stops recording, and the storage recording software is used to retrieve the image segment from the flying target entering the frame to the explosion, obtaining a frame image of the flying target and the target in the same frame. The slow playback is performed at least three times, and the playback video stream is output to the outside in the form of a real-time SDI video stream.

4. The method for measuring terminal trajectory parameters by surface intersection based on linear motion constraints according to claim 1, characterized in that: The read data includes a device number, a frame number, a data valid flag, a target horizontal pixel miss amount, a target vertical pixel miss amount, a video stream image width, and a video stream image height.

5. The surface intersection measurement method for terminal trajectory parameters based on linear motion constraints according to claim 2 is characterized in that: The filtering of the interpretation data by using a three-point random resampling method includes: Define the number of resampling times n, the straight line fitting error threshold tol and the number of sampling points each time nc; All the interpretation data of the first camera are expressed as [dx1,dy1], and nc groups of interpretation data are randomly selected , 1…nc represents the first to nc groups of interpretation data; by As the independent variable, As the dependent variable, perform one-dimensional straight line fitting to obtain the fitting line t0; Calculate the absolute distance di of each reading point (dx1, dy1) relative to the straight line t0 in [dx1, dy1], and form a new reading point set with di < tol , s represents the sth judgment point, and the number of judgment points contained in the judgment point set is defined as T1; The steps of randomly selecting nc groups of interpretation data to obtain a new interpretation point set are repeated n times to obtain n new interpretation point sets. , where the number of reading points contained in each set of reading points constitutes an array [T1, T2, T3,…Tn]; Find the maximum value in [T1, T2, T3,…Tn], defined as T ns , the corresponding judgment point set is , That is, the judgment point data obtained by filtering the judgment data of the first camera; The same processing is performed on the interpretation data of the second camera to obtain interpretation point data obtained by filtering based on the interpretation data of the second camera.

6. The method for measuring terminal trajectory parameters by surface intersection based on linear motion constraint according to claim 5, characterized in that: The step of performing angle synthesis on the filtered interpretation data to obtain target interpretation point data includes: Define the image resolution of SDI video stream as [H sdi ,W sdi ], the original image resolution is [H bmp ,W bmp ] and the camera dimension calculated based on the original image is [LGx bmp ,LGy bmp ]; Define the first camera’s corrected interpretation data as [dx s1 ,dy s1 ], then: ； ； Convert the pixel miss amount into the target pointing angle for angle synthesis, and define the optical axis direction of the first camera as [A 1axis ,E 1axis ], the miss angle corrections for azimuth and elevation are dA1 and dE1 respectively, then: ； The target pitch angle after angle integration is: ； The azimuth miss correction is: ； The target azimuth after angle integration is: ； Based on the same method, the target pointing angle measured by the second camera is obtained [A 20 ,E 20 ]; According to the target pointing angles of the first camera and the second camera, corresponding target judgment point data are obtained respectively.

7. The surface intersection measurement method for terminal trajectory parameters based on linear motion constraints according to claim 6 is characterized in that: The target interpretation point data is calculated based on the linear motion constraint using a surface-to-surface intersection algorithm to obtain the terminal flight trajectory parameters of the flying target, including: Establish a local rectangular coordinate system with the center of the target as the origin. The station coordinates of the first camera and the second camera in the local rectangular coordinate system are [x1, y1, z1] and [x2, y2, z2] respectively. The corresponding target pointing angles are [A 10 ,E 10 ] and [A 20 ,E 20 ]; definition , construct the point coordinate data set located on the plane formed by the target linear motion trajectory and the first camera station coordinates, which is: ； According to the intercept equation of the plane, the points in the point coordinate data set satisfy: ； Where a1, b1, and c1 are the intercepts of the plane formed by the target linear motion trajectory and the coordinates of the first camera station on the three axes of the local rectangular coordinate system: ； Where B is a vector with the same number of rows as xyz01, 1 column, and all elements are 1. T is the transpose of matrix xyz01; Construct two vectors lying on the xyz01 plane and , by cross-producting the two vectors, we can obtain the normal vector direction ABC1 of the plane formed by the target linear motion trajectory and the coordinates of the first camera station. The formula is: ； Define ABC1=[A1,B1,C1], the equation of the plane is: ； Where, ; The same method is used to obtain the normal vector direction number ABC2=[A2, B2, C2] of the plane formed by the target linear motion trajectory and the second camera station coordinates, and the equation of the corresponding plane is obtained as follows: ； Where D2=-ABC2∙[x2,y2,z2]; by combining the equations of the two planes, we get the intersection equation of the linear motion trajectory L, and the direction number W=[p,q,r] of the linear motion trajectory is obtained as follows: ； According to the direction number of the linear motion trajectory L, the terminal flight trajectory parameters of the flying target are obtained.

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