High-precision off-target quantity fast measurement method for multiple targets

Abstract

The present application belongs to the field of optical measurement technology, and particularly relates to a high-precision off-target amount fast measurement method for multiple targets. The method is as follows: firstly, the two-dimensional angle trajectory of multiple targets in a single station is identified, the two-dimensional angle trajectory of multiple targets of any two selected stations is calculated for inter-station trajectory matching, the three-dimensional space trajectory of multiple targets is obtained, that is, the two-dimensional trajectory between stations is taken as input, combined with the angle measurement accuracy of each station, the intersection and matching of the same point are processed, and finally the three-dimensional space trajectory of multiple targets is obtained, according to the four-dimensional space-time trajectory data of the main target and each target, the minimum space off-target amount and the corresponding time are calculated. The four-dimensional space-time discrete data of multiple targets is fitted with time as the independent variable, according to the partial derivative result of the fitting equation, the minimum distance of each target and the main target at the same time is calculated, and the high-precision calculation of the off-target amount of multiple targets is realized.

Description

Technical Field

[0001] This invention belongs to the field of optical measurement technology, and in particular relates to a high-precision, rapid method for measuring miss distances of multiple targets. Background Technology

[0002] Optical measurement equipment boasts advantages such as high measurement accuracy, fast response speed, and strong anti-interference capabilities, making it widely used in dynamic target tracking measurement. When using optical measurement equipment to measure the miss distance of multiple airborne moving targets, high-precision multi-target intersection measurement is required. How to quickly eliminate "false targets" generated during the intersection process and obtain accurate calculation results in the shortest possible time places extremely high demands on multi-target intersection algorithms. Addressing the specific needs of airborne moving multi-target miss distance measurement, developing a multi-target intersection measurement method adapted to optical measurement equipment, capable of rapidly eliminating false targets, and possessing both accuracy and real-time performance has become a pressing technical challenge in the field of optical measurement. Summary of the Invention

[0003] In view of this, the present invention aims to provide a high-precision method for rapid measurement of miss distances of multiple targets, so as to improve the data processing performance and measurement accuracy of optical measurement equipment in the scenario of tracking and measuring miss distances of multiple targets in the air. The present invention fits the spatial trajectory of the four-dimensional spatiotemporal discrete data of multiple targets with time as the independent variable, and calculates the minimum distance between each target and the main target at the same time based on the partial derivative of the fitting equation, thereby realizing high-precision calculation of miss distances of multiple targets.

[0004] To achieve the above objectives, the technical solution created by this invention is implemented as follows:

[0005] A high-precision, rapid method for measuring miss distances from multiple targets includes the following steps:

[0006] S1: Deploy no fewer than two optical measurement devices to enable the two optical measurement devices to simultaneously track the main target. When the secondary target enters the field of view of each optical measurement device, each optical measurement device acquires a continuous frame at the same observation time to obtain the time-series image sequence acquired by each optical measurement device.

[0007] S2: In the time-series image sequences acquired by each optical measurement device, obtain the pixel offset of the center position of each target in each time-series image relative to the center position of the corresponding time-series image, and obtain the two-dimensional angle value of each time-series image acquired by each optical measurement device.

[0008] S3: Perform data preprocessing operations on the pixel offset of each target in each time series image and the two-dimensional angle values ​​of each time series image collected by each optical measurement device. Then, perform matching and intersection operations on the same trajectory data points of each target between different stations to obtain the spatial three-dimensional coordinates of all targets at different observation times.

[0009] S4: Perform linear curve fitting on the spatial three-dimensional coordinates of the main target and each secondary target at different observation times, and construct the trajectory distance function based on the fitting results. By iteratively solving the trajectory distance function, obtain the minimum spatial miss distance and corresponding time between the main target and each secondary target.

[0010] Furthermore, step S2 specifically includes the following steps:

[0011] S21: Obtain the coordinates of the center position of the kth time series image in the image coordinate system in the time series image sequence acquired by the i-th optical measurement device, and the two-dimensional angle value of the kth time series image acquired by the i-th optical measurement device.

[0012] The image coordinate system is constructed with the lower left corner of the corresponding time series image as the origin. The direction from the origin to the right is taken as the positive x-axis, and the direction from the origin to the top is taken as the positive y-axis.

[0013] S22: Obtain the coordinates of the center position of each target in the k-th time series image in the image coordinate system of the time series image sequence acquired by the i-th optical measurement device;

[0014] S23: In the k-th time-series image of the time-series image sequence acquired by the i-th optical measurement device, obtain the pixel offset between the center position of each target and the center position of the time-series image;

[0015] S24: Replace the kth time-series image with the (k+1)th time-series image in the time-series image sequence acquired by the i-th optical measurement device. Repeat steps S21-S23 until the pixel offset of each target relative to the center position of the corresponding time-series image is obtained in all time-series images in the time-series image sequence acquired by the i-th optical measurement device.

[0016] S25: Replace the (i+1)th optical measurement device with the ith optical measurement device and repeat steps S21-S24. In the time-series image sequence obtained by each optical measurement device, obtain the pixel offset of the center position of each target in each time-series image relative to the center position of the corresponding time-series image, as well as the two-dimensional angle value of each time-series image acquired by each optical measurement device.

[0017] Furthermore, in step S3, the data preprocessing operations include optical system distortion correction and target synthetic angle light wave refraction correction.

[0018] Furthermore, the imaging field of view of each optical measurement device is divided into zones. Optical system distortion correction employs a bivariate quadratic polynomial model to solve for the pixel offset correction coefficients in the X and Y directions for each region. Based on these coefficients, the pixel offset of the target within the corresponding region is corrected. The bivariate quadratic polynomial model is as follows:

[0019] ;

[0020] in,( , The target surface correction pixel offset of the j-th target in the k-th frame time sequence image acquired by the i-th optical measurement device. for Pixel offset correction factor in direction. for Pixel offset correction factor in direction, ( , ) represents the actual pixel offset of the j-th target in the k-th frame of the time sequence image acquired by the i-th optical measurement device.

[0021] Furthermore, the calculation formula used for the systematic error correction of the target composite angle is as follows:

[0022] ;

[0023] in,( , The target surface correction pixel offset is the amount of the target surface when the i-th optical measurement device acquires the j-th target in the k-th frame of the time-series image. L is the zero position difference, C is the aiming difference, H is the horizontal axis difference, and g is the orientation difference. The composite azimuth angle of the target when the i-th optical measuring device acquires the j-th target in the k-th time-series image. The composite elevation angle of the target when the i-th optical measuring device acquires the j-th target in the k-th frame of the time sequence image:

[0024]

[0025] in, The azimuth encoder angle value is used when the i-th optical measurement device acquires the main target in the k-th frame of the time sequence image. For the i-th optical measurement device acquiring the pitch encoder angle value of the main target in the k-th frame of the time sequence image, ( , The target surface correction pixel offset is the value used when the i-th optical measurement device acquires the j-th target in the k-th frame of the time-series image. Let be the focal length value of the i-th optical measuring device.

[0026] Furthermore, in step S3, the matching and intersection operation of corresponding points for each target between different stations is specifically as follows:

[0027] S31: Select any two optical measuring devices from all deployed optical measuring devices. Based on the positions of the two stations corresponding to the two selected optical measuring devices in the geodetic coordinate system, measure the k-th frame of the time series image observed by station one. The k-th frame of the time-series image observed from the target and station 2. The coplanar difference between the current target pairs is calculated using the following formula: (The formula is not provided in the original text.)

[0028] ;

[0029] in, For the k-th frame of the time series image observed at station one The azimuth angle of the target location For the k-th frame of the time series image observed at station one The pitch angle of the target location For the k-th frame of the time series image observed at station 2, the first... The azimuth angle of the target location For the k-th frame of the time series image observed at station two, the first... The pitch angle of the target location , , , , , These are all intermediate calculations. The k-th time series image observed at station one The k-th frame of the time sequence image observed by the target and station 2. The coplanar difference between the two targets is given by (X1, Y1, Z1), which represents the coordinates of station 1 in the geodetic coordinate system, and (X2, Y2, Z2), which represents the coordinates of station 2 in the geodetic coordinate system.

[0030] S32: If the coplanar difference of the current target pair to be matched If the value is less than the corresponding set measurement accuracy threshold, then the first... The first goal and the first The target is designated as the s-th point target with the same name in the k-th frame of the temporal image;

[0031] S33: The position coordinates of the s-th corresponding point target in the k-th time series image are obtained by performing intersection calculation on the s-th corresponding point target in the k-th time series image using the following formula ( , , ):

[0032] ;

[0033] in, These are weighting coefficients;

[0034] S34: Replace the current target pair with the next target pair to be matched in the k-th frame time sequence image. Repeat steps S31-S33 until the matching of all the same-name point targets measured by the two stations in the k-th frame time sequence image is completed, and obtain the position coordinates of all targets in three-dimensional space at the measurement time corresponding to the k-th frame time sequence image.

[0035] S35: Replace the k-th frame time series image with the (k+1)-th frame time series image, and repeat steps S31-S34 until the spatial three-dimensional coordinates of all targets at all observation times are obtained.

[0036] Furthermore, step S4 specifically includes the following steps:

[0037] S41: By performing linear curve fitting on the spatial three-dimensional coordinates of the main target and each secondary target at different observation times using the following formula, the fitting curve of the main target can be expressed as:

[0038] ;

[0039] in, The spatial three-dimensional trajectory fitted to the main target, where t is the observation time. , , , , and All are fitting coefficients;

[0040] No. The fitted curve for each objective can be represented as:

[0041] ;

[0042] in, For the first The spatial three-dimensional trajectory fitted to the target in each iteration, where t is the observation time. , , , , and All are fitting coefficients;

[0043] The first is constructed using the following formula. Distance function between the trajectories of the individual and the main target:

[0044] ;

[0045] in, The three-dimensional trajectory of the main target in space. For the first The three-dimensional spatial trajectory of each target For the first The distance function between the trajectories of each secondary target and the primary target;

[0046] S42: Solve for the partial derivative of the distance function between trajectories using the following formula:

[0047] ;

[0048] in, The value at time 0 of the linear curve in the x-direction of the main target. The value at time 0 of the linear curve in the y-direction of the main target. The value at time 0 of the linear curve in the z-direction of the main target. For the first The value at time 0 of the linear curve of the x-direction of each sub-target. For the first The value at time 0 of the linear curve of the y-direction of each sub-target. For the first The value at time 0 of the linear curve of the z-direction of each sub-target. , , , , , , , , , , and These are all intermediate parameters and have no physical meaning.

[0049] S43: Solve for the main objective and the... using the following formula Spatial miss distance and corresponding time between individual targets:

[0050] ;

[0051] ;

[0052] ;

[0053] in, For the first Spatial miss distance between secondary targets and primary target In order to be with the first The time corresponding to the spatial miss distance between each secondary target and the primary target. , and This is an intermediate parameter with no physical meaning.

[0054] S44: Replace the r-th sub-target with the (r+1)-th sub-target and repeat steps S41-S43 until the minimum spatial miss distance and corresponding time between the main target and each sub-target are obtained: R is the total number of sub-targets.

[0055] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0056] This invention presents a high-precision, rapid method for measuring miss distances from multiple targets. It fits the spatial trajectories of four-dimensional spatiotemporal discrete data of multiple targets with time as the independent variable. The method then calculates the minimum distance between each target and the main target at the same time by differentiating the fitted equation, achieving high-precision calculation of miss distances. Since multiple targets are within the same imaging frame, systematic errors can be effectively eliminated, improving the accuracy of miss distance measurement using optical measurement equipment. Furthermore, the method utilizes target pixel offset data from real-time image processing to obtain the two-dimensional trajectories of multiple targets, saving time required for multi-target interpretation. The use of an automatic calculation method for the identification parameters of each trajectory further improves the efficiency of miss distance calculation. Attached Figure Description

[0057] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0058] Figure 1 This is a flowchart illustrating the high-precision, rapid measurement method for multi-target miss distances described in an embodiment of the present invention. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not constitute a limitation thereof.

[0060] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0061] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0062] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0063] The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0064] like Figure 1 As shown, this invention proposes a high-precision, rapid measurement method for multi-target miss distance, specifically including the following steps:

[0065] S1: Deploy no fewer than two optical measurement devices to enable the two optical measurement devices to simultaneously track the main target. When the secondary target enters the field of view of each optical measurement device, each optical measurement device acquires a continuous frame at the same observation time to obtain the time-series image sequence acquired by each optical measurement device.

[0066] S2: In the time-series image sequences acquired by each optical measurement device, obtain the pixel offset of the center position of each target in each time-series image relative to the center position of the corresponding time-series image, and obtain the two-dimensional angle value of each time-series image acquired by each optical measurement device.

[0067] S3: Perform data preprocessing operations on the pixel offset of each target in each time series image and the two-dimensional angle values ​​of each time series image collected by each optical measurement device. Then, perform matching and intersection operations on the same trajectory data points of each target between different stations to obtain the spatial three-dimensional coordinates of all targets at different observation times.

[0068] S4: Perform linear curve fitting on the spatial three-dimensional coordinates of the main target and each secondary target at different observation times, and construct the trajectory distance function based on the fitting results. By iteratively solving the trajectory distance function, obtain the minimum spatial miss distance and corresponding time between the main target and each secondary target.

[0069] It should be noted that during the measurement experiment, the optical measurement equipment can quickly measure the miss distance by tracking the main target and obtaining the continuous frame images of one or more secondary targets and the main target in key encounter segments. To achieve rapid multi-target miss distance measurement, a three-step processing method is adopted: The first step is multi-target tracking, which first identifies the two-dimensional angular trajectories of multiple targets in a single measurement station. To improve processing speed, the pixel offset of multiple targets calculated by real-time image processing is directly used as the input for this step, saving the time required for multi-target interpretation. The second step is multi-target same-name trajectory data point matching and intersection, which performs inter-station trajectory matching calculation on the two-dimensional angular trajectories of multiple targets at any two selected measurement stations to obtain the three-dimensional spatial trajectory of multiple targets. That is, using the two-dimensional trajectory between stations as input, combined with the angular measurement accuracy of each measurement station, the intersection and matching of points at the same time are performed to finally obtain the three-dimensional spatial trajectory of multiple targets. The third step is miss distance fitting and calculation, which calculates the minimum spatial miss distance and the corresponding time based on the four-dimensional spatiotemporal trajectory data of the main target and each target.

[0070] Preferably, the multi-target tracking process has multiple methods such as detection before tracking, tracking before detection, and detection while tracking. At the same time, image preprocessing, feature matching, data association and other methods can be used to achieve stable tracking of multiple targets.

[0071] Furthermore, step S2 specifically includes the following steps:

[0072] S21: Obtain the coordinates of the center position of the kth time series image in the image coordinate system in the time series image sequence acquired by the i-th optical measurement device, and the two-dimensional angle value of the kth time series image acquired by the i-th optical measurement device.

[0073] The image coordinate system is constructed with the lower left corner of the corresponding time series image as the origin. The direction from the origin to the right is taken as the positive x-axis, and the direction from the origin to the top is taken as the positive y-axis.

[0074] S22: Obtain the coordinates of the center position of each target in the k-th time series image in the image coordinate system of the time series image sequence acquired by the i-th optical measurement device;

[0075] S23: In the k-th time-series image of the time-series image sequence acquired by the i-th optical measurement device, obtain the pixel offset between the center position of each target and the center position of the time-series image;

[0076] S24: Replace the kth time-series image with the (k+1)th time-series image in the time-series image sequence acquired by the i-th optical measurement device. Repeat steps S21-S23 until the pixel offset of each target relative to the center position of the corresponding time-series image is obtained in all time-series images in the time-series image sequence acquired by the i-th optical measurement device.

[0077] S25: Replace the (i+1)th optical measurement device with the ith optical measurement device and repeat steps S21-S24. In the time-series image sequence obtained by each optical measurement device, obtain the pixel offset of the center position of each target in each time-series image relative to the center position of the corresponding time-series image, as well as the two-dimensional angle value of each time-series image acquired by each optical measurement device.

[0078] Furthermore, in step S3, the data preprocessing operations include optical system distortion correction and target synthetic angle light wave refraction correction.

[0079] Furthermore, the imaging field of view of each optical measurement device is divided into zones. Optical system distortion correction employs a bivariate quadratic polynomial model to solve for the pixel offset correction coefficients in the X and Y directions for each region. Based on these coefficients, the pixel offset of the target within the corresponding region is corrected. The bivariate quadratic polynomial model is as follows:

[0080] ;

[0081] in,( , The target surface correction pixel offset of the j-th target in the k-th frame time sequence image acquired by the i-th optical measurement device. for Pixel offset correction factor in direction. for Pixel offset correction factor in direction, ( , ) represents the actual pixel offset of the j-th target in the k-th frame of the time sequence image acquired by the i-th optical measurement device.

[0082] It should be noted that optical system distortion is categorized into radial distortion, eccentric distortion, and thin prism distortion. To achieve high angular measurement accuracy across the entire field of view in a wide-field optical measurement system, a method is proposed to divide the field of view of the measurement system into multiple regions for camera distortion correction. For each region, the least squares multivariate regression method is used to calculate the correction coefficients, which are then used for measurement calculations. Simulation analysis led to the selection of a bivariate quadratic correction model, which is characterized by its simplicity, intuitiveness, fast computation speed, and ease of implementation.

[0083] The target surface was divided into sections after partitioning. Each region is a small region of a certain size. To minimize the error for all imaging points within a region, the least squares method is used to process each region, calculating the correction coefficient for each region. Based on the bivariate quadratic polynomial least squares regression method, each small region is selected... One sampling point, Direction correction factor and Direction correction factor The calculation formula is as follows:

[0084] ;

[0085] ;

[0086] In the formula, This indicates the number of sample points that need to be calculated within the small area. , Indicates the first The actual pixel offset of each sample point Indicates the first Each sample point in Theoretical pixel offset in direction, To indicate the first The theoretical pixel offset of a sample point in the y-direction.

[0087] Solving the above system of equations, we can find the correction coefficients. , .

[0088] After obtaining the pixel offset correction coefficient for each region using the above method, the pixel offset of subsequent measurement points can be corrected using the obtained correction model. Then, the target angle value can be calculated using the pixel offset corrected for camera distortion.

[0089] Furthermore, the calculation formula used for the systematic error correction of the target composite angle is as follows:

[0090] ;

[0091] in,( , The target surface correction pixel offset is the amount of the target surface when the i-th optical measurement device acquires the j-th target in the k-th frame of the time-series image. L is the zero position difference, C is the aiming difference, H is the horizontal axis difference, and g is the orientation difference. The composite azimuth angle of the target when the i-th optical measuring device acquires the j-th target in the k-th time-series image. The composite elevation angle of the target when the i-th optical measuring device acquires the j-th target in the k-th frame of the time sequence image:

[0092]

[0093] in, The azimuth encoder angle value is used when the i-th optical measurement device acquires the main target in the k-th frame of the time sequence image. For the i-th optical measurement device acquiring the pitch encoder angle value of the main target in the k-th frame of the time sequence image, ( , The target surface correction pixel offset is the value used when the i-th optical measurement device acquires the j-th target in the k-th frame of the time-series image. Let be the focal length value of the i-th optical measuring device.

[0094] Furthermore, in step S3, the matching and intersection operation of corresponding points for each target between different stations is specifically as follows:

[0095] S31: Select any two optical measuring devices from all deployed optical measuring devices. Based on the positions of the two stations corresponding to the two selected optical measuring devices in the geodetic coordinate system, measure the k-th frame of the time series image observed by station one. The k-th frame of the time-series image observed from the target and station 2. The coplanar difference between the current target pairs is calculated using the following formula: (The formula is not provided in the original text.)

[0096] ;

[0097] in, For the k-th frame of the time series image observed at station one The azimuth angle of the target location For the k-th frame of the time series image observed at station one The pitch angle of the target location For the k-th frame of the time series image observed at station two, the first... The azimuth angle of the target location For the k-th frame of the time series image observed at station two, the first... The pitch angle of the target location , , , , , These are all intermediate calculations. The k-th time series image observed at station one The k-th frame of the time sequence image observed by the target and station 2. The coplanar difference between the two targets is given by (X1, Y1, Z1), which represents the coordinates of station 1 in the geodetic coordinate system, and (X2, Y2, Z2), which represents the coordinates of station 2 in the geodetic coordinate system.

[0098] S32: If the coplanar difference of the current target pair to be matched If the value is less than the corresponding set measurement accuracy threshold, then the first... The first goal and the first The target is designated as the s-th point target with the same name in the k-th frame of the temporal image;

[0099] S33: The position coordinates of the s-th corresponding point target in the k-th time series image are obtained by performing intersection calculation on the s-th corresponding point target in the k-th time series image using the following formula ( , , ):

[0100] ;

[0101] in, These are weighting coefficients;

[0102] S34: Replace the current target pair with the next target pair to be matched in the k-th frame time sequence image. Repeat steps S31-S33 until the matching of all the same-name point targets measured by the two stations in the k-th frame time sequence image is completed, and obtain the position coordinates of all targets in three-dimensional space at the measurement time corresponding to the k-th frame time sequence image.

[0103] S35: Replace the k-th frame time series image with the (k+1)-th frame time series image, and repeat steps S31-S34 until the spatial three-dimensional coordinates of all targets at all observation times are obtained.

[0104] It should be noted that the matching and intersection of multi-target corresponding trajectory data points mainly distinguishes corresponding points by using trajectory non-plane difference and accuracy screening. First, data preprocessing is performed to correct errors and obtain high-precision measurement data to improve data accuracy. Then, the corresponding point matching algorithm is used to obtain intersection data for high-precision final fast processing results.

[0105] The matching process employs a dual-loop processing method. The first loop matches all targets in station A with all targets in station B. The second loop matches targets based on their simultaneous moments. For example, in the above figure, the cyclical calculation process for the Nth target in station A and the Mth target in station B involves performing intersection calculations between the i-th target of the former and the j-th target of the latter at the same moment, and completing the matching calculation between the entire two-dimensional trajectory based on time synchronization.

[0106] Furthermore, step S4 specifically includes the following steps:

[0107] S41: By performing linear curve fitting on the spatial three-dimensional coordinates of the main target and each secondary target at different observation times using the following formula, the fitting curve of the main target can be expressed as:

[0108] ;

[0109] in, The spatial three-dimensional trajectory fitted to the main target, where t is the observation time. , , , , and All are fitting coefficients;

[0110] No. The fitted curve for each objective can be represented as:

[0111] ;

[0112] in, For the first The spatial three-dimensional trajectory fitted to the target in each iteration, where t is the observation time. , , , , and All are fitting coefficients;

[0113] The first is constructed using the following formula. Distance function between the trajectories of the individual and the main target:

[0114] ;

[0115] in, The three-dimensional trajectory of the main target in space. For the first The three-dimensional spatial trajectory of each target For the first The distance function between the trajectories of each secondary target and the primary target;

[0116] S42: Solve for the partial derivative of the distance function between trajectories using the following formula:

[0117] ;

[0118] in, The value at time 0 of the linear curve in the x-direction of the main target. The value at time 0 of the linear curve in the y-direction of the main target. The value at time 0 of the linear curve in the z-direction of the main target. For the first The value at time 0 of the linear curve of the x-direction of each sub-target. For the first The value at time 0 of the linear curve of the y-direction of each sub-target. For the first The value at time 0 of the linear curve of the z-direction of each sub-target. , , , , , , , , , , and These are all intermediate parameters and have no physical meaning.

[0119] S43: Solve for the main objective and the... using the following formula Spatial miss distance and corresponding time between individual targets:

[0120] ;

[0121] ;

[0122] ;

[0123] in, For the first Spatial miss distance between secondary targets and primary target In order to be with the first The time corresponding to the spatial miss distance between each secondary target and the primary target. , and This is an intermediate parameter with no physical meaning.

[0124] S44: Replace the r-th sub-target with the (r+1)-th sub-target and repeat steps S41-S43 until the minimum spatial miss distance and corresponding time between the main target and each sub-target are obtained: R is the total number of sub-targets.

[0125] It should be noted that the calculation of the miss distance fitting mainly utilizes multi-target intersection data based on the same frame principle to calculate the miss distance. First, the trajectory of the target is obtained through intersection, and then the data is encrypted through interpolation and fitting. The difference between the two curves is used to construct the minimum miss distance function and find the extreme value to obtain the minimum miss distance. At the same time, the time corresponding to the minimum miss distance is obtained.

[0126] The fitted curves based on the two objectives are subtracted at a specified frequency at the same time. , , ,Pick The minimum value of is the closest point between two targets in the trajectory space.

[0127] When using a When using a polynomial of order 2 to fit the sampling information of a single frame, choosing an appropriate order is crucial. The order of the fitting polynomial is generally no greater than 2. This is mainly because the number of measured frames within the same frame is relatively small, resulting in a very short time span for the sampling points, only a few hundred milliseconds. Meanwhile, the relative speed between targets is high, and significant changes will not occur within such a short time. Therefore, linear fitting is preferable for the fitting curve.

[0128] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0129] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A high-precision, rapid method for measuring miss distances from multiple targets, characterized in that: Specifically, the steps include the following: S1: Deploy no fewer than two optical measurement devices to enable the two optical measurement devices to simultaneously track the main target. When the secondary target enters the field of view of each optical measurement device, each optical measurement device acquires a continuous frame at the same observation time to obtain the time-series image sequence acquired by each optical measurement device. S2: In the time-series image sequences acquired by each optical measurement device, obtain the pixel offset of the center position of each target in each time-series image relative to the center position of the corresponding time-series image, and obtain the two-dimensional angle value of each time-series image acquired by each optical measurement device. S3: Perform data preprocessing operations on the pixel offset of each target in each time series image and the two-dimensional angle values ​​of each time series image collected by each optical measurement device. Then, perform matching and intersection operations on the same trajectory data points of each target between different stations to obtain the spatial three-dimensional coordinates of all targets at different observation times. S4: Perform linear curve fitting on the spatial three-dimensional coordinates of the main target and each secondary target at different observation times, and construct the trajectory distance function based on the fitting results. By iteratively solving the trajectory distance function, obtain the minimum spatial miss distance and corresponding time between the main target and each secondary target.

2. The high-precision, rapid measurement method for multi-target miss distance according to claim 1, characterized in that: Step S2 specifically includes the following steps: S21: Obtain the coordinates of the center position of the kth time series image in the image coordinate system in the time series image sequence acquired by the i-th optical measurement device, and the two-dimensional angle value of the kth time series image acquired by the i-th optical measurement device. The image coordinate system is constructed with the lower left corner of the corresponding time series image as the origin. The direction from the origin to the right is taken as the positive x-axis, and the direction from the origin to the top is taken as the positive y-axis. S22: Obtain the coordinates of the center position of each target in the k-th time series image in the image coordinate system of the time series image sequence acquired by the i-th optical measurement device; S23: In the k-th time-series image of the time-series image sequence acquired by the i-th optical measurement device, obtain the pixel offset between the center position of each target and the center position of the time-series image; S24: Replace the kth time-series image with the (k+1)th time-series image in the time-series image sequence acquired by the i-th optical measurement device. Repeat steps S21-S23 until the pixel offset of each target relative to the center position of the corresponding time-series image is obtained in all time-series images in the time-series image sequence acquired by the i-th optical measurement device. S25: Replace the (i+1)th optical measurement device with the ith optical measurement device and repeat steps S21-S24. In the time-series image sequence obtained by each optical measurement device, obtain the pixel offset of the center position of each target in each time-series image relative to the center position of the corresponding time-series image, as well as the two-dimensional angle value of each time-series image acquired by each optical measurement device.

3. The high-precision, rapid measurement method for multi-target miss distance according to claim 1, characterized in that: In step S3, the data preprocessing operations include optical system distortion correction and target synthetic angle light wave refraction correction.

4. The high-precision, rapid measurement method for multi-target miss distance according to claim 3, characterized in that: The imaging field of view of each optical measurement device is divided into zones. Optical system distortion correction employs a bivariate quadratic polynomial model to solve for the pixel offset correction coefficients in the X and Y directions for each zone. Based on these coefficients, the pixel offset of the target within the corresponding zone is corrected. The bivariate quadratic polynomial model is as follows: ； in,( , The target surface correction pixel offset of the j-th target in the k-th frame time sequence image acquired by the i-th optical measurement device. for Pixel offset correction factor in direction. for Pixel offset correction factor in direction, ( , ) represents the actual pixel offset of the j-th target in the k-th frame of the time sequence image acquired by the i-th optical measurement device.

5. The high-precision, rapid measurement method for multi-target miss distance according to claim 4, characterized in that: The formula used for calculating the systematic error correction of the target composite angle is as follows: ； in,( , The target surface correction pixel offset is the amount of the target surface when the i-th optical measurement device acquires the j-th target in the k-th frame of the time-series image. L is the zero position difference, C is the aiming difference, H is the horizontal axis difference, and g is the orientation difference. The composite azimuth angle of the target when the i-th optical measuring device acquires the j-th target in the k-th time-series image. The composite elevation angle of the target when the i-th optical measuring device acquires the j-th target in the k-th frame of the time sequence image: in, The azimuth encoder angle value is used when the i-th optical measurement device acquires the main target in the k-th frame of the time sequence image. For the i-th optical measurement device acquiring the pitch encoder angle value of the main target in the k-th frame of the time sequence image, ( , The target surface correction pixel offset is the value used when the i-th optical measurement device acquires the j-th target in the k-th frame of the time-series image. Let be the focal length value of the i-th optical measuring device.

6. The high-precision, rapid measurement method for multi-target miss distance according to claim 5, characterized in that: In step S3, the specific steps for matching and intersectioning corresponding points of targets between different stations are as follows: S31: Select any two optical measuring devices from all deployed optical measuring devices. Based on the positions of the two stations corresponding to the two selected optical measuring devices in the geodetic coordinate system, measure the k-th frame of the time series image observed by station one. The k-th frame of the time-series image observed from the target and station 2. The coplanar difference between the current target pairs is calculated using the following formula: (The formula is not provided in the original text.) ； in, For the k-th frame of the time series image observed at station one The azimuth angle of the target location For the k-th frame of the time series image observed at station one The pitch angle of the target location For the k-th frame of the time series image observed at station two, the first... The azimuth angle of the target location For the k-th frame of the time series image observed at station two, the first... The pitch angle of the target location , , , , , These are all intermediate calculations. The k-th time series image observed at station one The k-th frame of the time sequence image observed by the target and station 2. The coplanar difference between the two targets is given by (X1, Y1, Z1), which represents the coordinates of station 1 in the geodetic coordinate system, and (X2, Y2, Z2), which represents the coordinates of station 2 in the geodetic coordinate system. S32: If the coplanar difference of the current target pair to be matched If the value is less than the corresponding set measurement accuracy threshold, then the first... The first goal and the first The target is designated as the s-th point target with the same name in the k-th frame of the temporal image; S33: The position coordinates of the s-th corresponding point target in the k-th time series image are obtained by performing intersection calculation on the s-th corresponding point target in the k-th time series image using the following formula ( , , ): ； in, These are weighting coefficients; S34: Replace the current target pair with the next target pair to be matched in the k-th frame time sequence image. Repeat steps S31-S33 until the matching of all the same-name point targets measured by the two stations in the k-th frame time sequence image is completed, and obtain the position coordinates of all targets in three-dimensional space at the measurement time corresponding to the k-th frame time sequence image. S35: Replace the k-th frame time series image with the (k+1)-th frame time series image, and repeat steps S31-S34 until the spatial three-dimensional coordinates of all targets at all observation times are obtained.

7. The high-precision, rapid measurement method for multi-target miss distance according to claim 6, characterized in that: Step S4 specifically includes the following steps: S41: By performing linear curve fitting on the spatial three-dimensional coordinates of the main target and each secondary target at different observation times using the following formula, the fitting curve of the main target can be expressed as: ； in, The spatial three-dimensional trajectory fitted to the main target, where t is the observation time. , , , , and All are fitting coefficients; No. The fitted curve for each objective can be represented as: ； in, For the first The spatial three-dimensional trajectory fitted to the target in each iteration, where t is the observation time. , , , , and All are fitting coefficients; The first is constructed using the following formula. Distance function between the trajectories of the individual and the main target: ； in, The three-dimensional trajectory of the main target in space. For the first The three-dimensional spatial trajectory of each target For the first The distance function between the trajectories of each secondary target and the primary target; S42: Solve for the partial derivative of the distance function between trajectories using the following formula: ； in, The value at time 0 of the linear curve in the x-direction of the main target. The value at time 0 of the linear curve in the y-direction of the main target. The value at time 0 of the linear curve in the z-direction of the main target. For the first The value at time 0 of the linear curve of the x-direction of each sub-target. For the first The value at time 0 of the linear curve of the y-direction of each sub-target. For the first The value at time 0 of the linear curve of the z-direction of each sub-target. , , , , , , , , , , and These are all intermediate parameters and have no physical meaning. S43: Solve for the main objective and the... using the following formula Spatial miss distance and corresponding time between individual targets: ； ； ； in, For the first Spatial miss distance between secondary targets and the primary target In order to be with the first The time corresponding to the spatial miss distance between each secondary target and the primary target. , and This is an intermediate parameter with no physical meaning. S44: Replace the r-th sub-target with the (r+1)-th sub-target and repeat steps S41-S43 until the minimum spatial miss distance and corresponding time between the main target and each sub-target are obtained: R is the total number of sub-targets.

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