Multi-station video-based real-time measurement method for air burst point

Abstract

The application provides a multi-station video acquisition-based real-time measurement method for an air burst point, comprising: setting station arrangement parameters: arranging multiple measurement stations according to actual conditions and initializing parameters; determining actual station arrangement parameters: measuring actual station arrangement parameters of the multiple measurement stations by a high-precision positioning module and a high-precision angle sensor module respectively, and determining distances between the measurement stations; determining and calibrating a two-dimensional coordinate of a burst point: multiple measurement devices respectively perform continuous video acquisition on the burst point by camera modules, perform image processing to obtain a two-dimensional coordinate of the burst point, and calibrate the two-dimensional coordinate of the burst point in space; and determining a position of the air burst point: performing intersection processing according to parameters of the multiple measurement stations to obtain the position of the air burst point. The application improves the precision of the measurement of the position of the air burst point.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of burst point positioning, and particularly relates to a multi-station real-time measurement method for air burst points based on video acquisition. BACKGROUND

[0002] A traditional air burst point position measurement algorithm uses two high-speed cameras to shoot burst point images at different orientations, uses intersection algorithm to calculate the position of the air burst point, and performs post-processing on the two acquired images based on a PC. Since the traditional method needs manual measurement of the distance between devices, does not consider the influence of the roll angle of the device on the measurement result, does not time-align the measurement result, and is not real-time, the convenience is poor and the measurement error is high. In order to further improve the air burst point measurement accuracy and the convenience of the process, it is crucial to use satellites to measure the distance between devices, consider the influence of the roll angle of the device, and use a multi-station real-time measurement method for air burst points based on video acquisition.

[0003] The existing technology has the following problems: the number of designed devices is small, the influence of the roll angle of the device is ignored, and the measurement result is not time-aligned, so that the measurement result accuracy is poor, the distance between devices needs to be measured manually, the workload of the burst point measurement process is increased, and the two acquired images are processed based on a PC, which is not real-time. SUMMARY

[0004] The present application provides a multi-station real-time measurement method for air burst points based on video acquisition, which can be used to solve the technical problem of inaccurate measurement of air burst points caused by ignoring the influence of the roll angle of the device.

[0005] The present application provides a multi-station real-time measurement method for air burst points based on video acquisition, which includes the following steps:

[0006] Step 10, setting the station arrangement parameters: arranging multiple measurement stations according to the actual situation and initializing the parameters;

[0007] Step 20, determining the actual station arrangement parameters: measuring the actual station arrangement parameters of the multiple measurement stations by the high-precision positioning module and the high-precision angle sensor module, and determining the distance between the measurement stations;

[0008] Step 30, determining and calibrating the two-dimensional coordinates of the burst point: multiple measurement devices respectively acquire continuous videos of the burst point through the camera module, process the images to obtain the two-dimensional coordinates of the burst point, and calibrate the two-dimensional coordinates of the burst point in space;

[0009] Step 40, determining the position of the air burst point: performing intersection processing according to the parameters of the multiple measurement stations to obtain the position of the air burst point.

[0010] Optionally, the initialization parameters include the distance L between the multiple measurement sites, the yaw angle T of each measurement site Yaw , the pitch angle T Pitch .

[0011] Optionally, the actual stationing parameters of the multiple measurement sites are measured by the high-precision positioning module and the high-precision angle sensor module respectively, and the distance between the measurement sites is determined, including:

[0012] Step 21, determining the position parameters of the measurement sites: the longitude S i , the latitude N j of the multiple sites are measured by the high-precision positioning module respectively; the high-precision positioning module is a multi-frequency RTK positioning and orientation module developed based on ZED-F9P, and the multi-band receiver can provide centimeter-level accuracy within seconds and can simultaneously receive GPS, GLONASS, Galileo and Beidou navigation signals;

[0013] Step 22, according to the longitude S i , the latitude N j , the baseline distance between any two measurement sites is:

[0014]

[0015] Where m is the distance when the latitude difference is 1°, and n is the distance when the longitude difference is 1°, and their values are:

[0016] m = 111319.4888943678

[0017]

[0018] Step 23, determining the actual angle parameters of the measurement sites: the actual yaw angle T Yaw , the pitch angle T Pitch , the roll angle T Roll of the multiple sites are measured by the high-precision angle sensor module;

[0019] The high-precision angle sensor module integrates high-precision gyroscopes, accelerometers, and geomagnetic field sensors, uses high-performance microprocessors and dynamic calculation and Kalman dynamic filtering algorithms, and uses digital filtering processing. The high-precision angle sensor module integrates an attitude solver internally, and cooperates with the dynamic Kalman filtering algorithm.

[0020] Optionally, the determination and calibration of the two-dimensional coordinates of the burst points include:

[0021] Step 31, acquisition and processing of burst point video:

[0022] The camera of each of the plurality of measuring stations continuously collects video of the burst point, and performs image graying and image segmentation to obtain a binary image of the burst point.

[0023] Step 32, determining the position of the centroid of the burst point:

[0024] Supposing that the size of the binary image of the burst point is M x N, the position of the centroid of the burst point is determined based on a square weighted gray centroid method:

[0025]

[0026]

[0027] wherein M and N are pixel points in horizontal and vertical directions of the burst point image; (x, y) is the coordinate of a corresponding pixel point in the burst point image; f(x, y) is the gray value of the corresponding pixel point; x C , y C are the horizontal and vertical coordinates of the centroid of the burst point to be solved;

[0028] Step 33, determining the two-dimensional coordinates of the burst point:

[0029] Supposing that the horizontal coordinate of the pixel size of the camera is e1, the vertical coordinate of the pixel size of the camera is e2, and the two-dimensional coordinates (x_c, y_c) of the burst point are:

[0030] x_c=x C e1

[0031] y_c=y C e2#(5)

[0032] Step 34, calibrating the two-dimensional coordinates of the burst point: each of the plurality of measuring stations respectively uses the measured roll angle T Roll to calibrate the two-dimensional coordinates of the burst point in space to obtain new two-dimensional coordinates (x, y) of the burst point:

[0033] x=x_c·cos(T Roll )+y_c·sin(T Roll )#(6)

[0034] y=y_c·sin(T Roll )-x_c·sin(T Roll )#(7).

[0035] Optionally, determining the position of the burst point in the air comprises:

[0036] Step 41, supposing that the parameters of each of the two stations are: the baseline distance L of the measuring station, the yaw angles T Yaw1 and T Yaw2 , the pitch angles T Pitch1 and T Pitch2, focal length is f and burst point two-dimensional coordinates (x1, y1) and (x2, y2), based on the intersection algorithm two stations measured in the air burst point position is:

[0037]

[0038] In the formula, the subscript 1 in each parameter represents the parameter corresponding to the first station; the subscript 2 represents the parameter corresponding to the second station;

[0039] A plurality of sets of air burst point positions Z1, Z2, …, Zn are obtained;

[0040] Step 42, average a plurality of sets of air burst point positions to obtain the position of the final air burst point:

[0041]

[0042] In the formula, n represents the number of burst points.

[0043] The present application measures the parameters of the measurement station through a high-precision positioning module and a high-precision angle sensor, reduces the measurement station baseline distance error and the measurement initial value error, and calibrates the two-dimensional coordinates of the burst point according to the measured parameters, improves the accuracy of the air burst point position measurement, and performs real-time processing. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 The main flowchart of the air burst point position measurement algorithm provided by the embodiment of the present application;

[0045] Figure 2 The flowchart of the measured station parameter determination step provided by the embodiment of the present application;

[0046] Figure 3 The flowchart of the burst point two-dimensional coordinate determination and calibration step provided by the embodiment of the present application;

[0047] Figure 4 The flowchart of the air burst point position calculation step provided by the embodiment of the present application;

[0048] Figure 5 The air burst point position calculation principle diagram provided by the embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical scheme and advantages of the present application clearer, the following will combine the drawings to further describe the embodiment of the present application in detail.

[0050] The present application provides a multi-station real-time measurement method for air burst points based on video acquisition, which comprises:

[0051] Step 10, set the station parameter: according to the actual situation, multiple measurement stations are laid out and the parameters are initialized.

[0052] The initialization parameters include the distance L (unit: meter) between multiple measurement stations, the yaw angle T Yaw (unit: degree) of each measurement station, the pitch angle T Pitch (unit: degree) of each measurement station.

[0053] Step 20, determine the actual station parameter: the actual station parameters of multiple measurement stations are measured by the high-precision positioning module and the high-precision angle sensor module respectively, and the distance between the measurement stations is determined.

[0054] Specifically, step 20 includes:

[0055] Step 21, determine the position parameters of the measurement stations: the longitude S i and the latitude N j of multiple stations are measured by the high-precision positioning module; the high-precision positioning module is a multi-frequency RTK positioning and orientation module developed based on ZED-F9P, and the multi-band receiver can provide centimeter-level accuracy within seconds and can simultaneously receive GPS, GLONASS, Galileo and Beidou navigation signals;

[0056] Step 22, according to the longitude S i and the latitude N j , the baseline distance between any two measurement stations is:

[0057]

[0058] Where m is the distance when the latitude difference is 1°, and n is the distance when the longitude difference is 1°, and their values are (unit: meter) respectively:

[0059] m = 111319.4888943678

[0060]

[0061] Step 23, determine the actual angle parameters of the measurement stations: the actual yaw angle T Yaw (unit: degree), the pitch angle T Pitch (unit: degree), and the roll angle T Roll (unit: degree) of multiple stations are measured by the high-precision angle sensor module.

[0062] The high-precision angle sensor module integrates a high-precision gyroscope, an accelerometer, and a geomagnetic field sensor, adopts a high-performance microprocessor and a dynamic solution and Kalman dynamic filtering algorithm, can quickly solve the real-time motion posture of the module at present, and adopts digital filtering processing, can effectively reduce measurement noise, and improve measurement precision; the high-precision angle sensor module internally integrates a posture solver, cooperates with a dynamic Kalman filtering algorithm, can accurately output the current posture of the module in a dynamic environment, and the posture measurement precision is 0.001 degrees, and the stability is extremely high.

[0063] Step 30, determination and calibration of the two-dimensional coordinates of the shot point: a plurality of measuring devices respectively collect continuous videos of the shot point through the camera module, perform image processing to obtain the two-dimensional coordinates of the shot point, and perform spatial calibration on the two-dimensional coordinates of the shot point.

[0064] Specifically, step 30 includes:

[0065] Step 31, collection and processing of the shot point video:

[0066] The cameras of a plurality of measuring stations respectively collect continuous videos of the shot point, perform image greying and image segmentation processing, and obtain a binary shot point image;

[0067] Step 32, determination of the position of the shot point centroid:

[0068] Supposing that the size of the binary shot point image is MxN (unit: pixel), the position of the shot point centroid is determined based on a square weighted gray centroid method:

[0069]

[0070]

[0071] Wherein, M and N are pixel points in the horizontal and vertical directions of the shot point image; (x, y) is the coordinate of the corresponding pixel point in the shot point image; f(x, y) is the gray value of the corresponding pixel point, x C , y C are the horizontal and vertical coordinates of the shot point centroid to be solved;

[0072] Step 33, determination of the two-dimensional coordinates of the shot point:

[0073] Supposing that the horizontal coordinate of the pixel size of the camera is e1, and the vertical coordinate of the pixel size of the camera is e2 (unit: meter), the two-dimensional coordinates (x_c, y_c) of the shot point are:

[0074] x_c=x C e1

[0075] y_c=y C e2#(5)

[0076] Step 34, calibration of the two-dimensional coordinates of the burst point: the multiple measurement stations respectively calibrate the two-dimensional coordinates of the burst point by using the measured roll angle T Roll (unit degree) to obtain new two-dimensional coordinates (x, y) of the burst point:

[0077] x = x_c*cos(T Roll )+y_c*sin(T Roll )#(6)

[0078] y = y_c*sin(T Roll )-x_c*sin(T Roll )#(7).

[0079] Step 40, determining the position of the aerial burst point: according to the read parameters of the multiple measurement stations, intersection processing is performed to obtain the position of the aerial burst point.

[0080] Specifically, step 40 includes:

[0081] Step 41, assuming that the parameters of any two stations are: the baseline distance L (unit: meter) of the measurement station, the yaw angles T Yaw1 and T Yaw2 (unit degree), the pitch angles T Pitch1 and T Pitch2 (unit degree), the focal length f (unit: meter), and the two-dimensional coordinates (x1, y1) and (x2, y2) of the burst point, based on the intersection algorithm, the positions of the aerial burst point measured by the two stations are:

[0082]

[0083] In the formula, the subscript 1 in each parameter represents the parameter corresponding to the first station; the subscript 2 represents the parameter corresponding to the second station;

[0084] A plurality of aerial burst point positions Z1, Z2, …, Zn are obtained.

[0085] Step 42, averaging the plurality of aerial burst point positions to obtain the position of the final aerial burst point:

[0086]

[0087] In the formula, n represents the number of burst points.

[0088] The present application measures the parameters of the measurement station through a high-precision positioning module and a high-precision angle sensor, reduces the baseline distance error and the initial measurement error of the measurement station, calibrates the two-dimensional coordinates of the burst point according to the measured parameters, improves the precision of the aerial burst point position measurement, and performs real-time processing.

[0089] The above-described embodiments of the present application do not constitute a limitation on the protection scope of the present application.

Claims

1. A multi-site real-time measurement method for airborne explosion points based on video acquisition, characterized in that: The method comprises: Step 10: Set station parameters: Arrange multiple measurement stations according to actual conditions and initialize parameters; Step 20, determining the measured station layout parameters: using the high-precision positioning module and the high-precision angle sensor module to measure the actual station layout parameters of multiple measurement sites, and determine the distances between the measurement sites; Step 30, determining and calibrating the two-dimensional coordinates of the explosion point: multiple measuring devices respectively capture continuous video of the explosion point through camera modules, perform image processing to obtain the two-dimensional coordinates of the explosion point, and perform spatial calibration on the two-dimensional coordinates of the explosion point; Step 40, determining the location of the aerial explosion point: performing intersection processing based on the parameters of the multiple measurement sites read to obtain the location of the aerial explosion point; The high-precision positioning module and high-precision angle sensor module measure the actual layout parameters of multiple measurement sites and determine the distance between the measurement sites, including: Step 21: Determine the location parameters of the measurement site: Use the high-precision positioning module to measure the longitude S of multiple sites respectively. i , latitude N j The high-precision positioning module is a multi-frequency RTK positioning and orientation module developed based on the ZED-F9P. The multi-band receiver can provide centimeter-level accuracy within seconds and can simultaneously receive GPS, GLONASS, Galileo and BeiDou navigation signals. Step 22, according to the longitude S i , latitude N j , the baseline distance between any two measurement sites is: Where m is the spacing when the latitude differs by 1°, and n is the spacing when the longitude differs by 1°, and their values ​​are: m＝111319.4888943678 Step 23: Determine the actual angle parameters of the measurement site: Use a high-precision angle sensor module to measure the actual yaw angles T of multiple sites. Yaw , pitch angle T Pitch , roll angle T Roll ; The high-precision angle sensor module integrates a high-precision gyroscope, accelerometer, and geomagnetic field sensor. It uses a high-performance microprocessor and dynamic solver with Kalman dynamic filtering algorithm, and adopts digital filtering processing. The high-precision angle sensor module integrates an attitude solver and cooperates with the dynamic Kalman filtering algorithm.

2. The method according to claim 1, characterized in that Initialization parameters include the distance L between multiple measurement sites, the yaw angle T of each measurement site Yaw , pitch angle T Pitch .

3. The method according to claim 1, characterized in that Determination and calibration of the 2D coordinates of the explosion point, including: Step 31: Collection and processing of explosion point video: The cameras at multiple measurement sites continuously capture videos of the explosion point, perform image grayscale conversion and image segmentation processing, and obtain binary explosion point images; Step 32: Determine the centroid position of the explosion point: Assume that the size of the binary explosion point image is M×N, and the centroid position of the explosion point is determined based on the square weighted grayscale centroid method: Where M and N are the horizontal and vertical pixels of the explosion point image; (x, y) are the coordinates of the corresponding pixel in the explosion point image; f(x,y) is the grayscale value of the corresponding pixel, x C ,y C are the horizontal and vertical coordinates of the centroid of the explosion point; Step 33, determine the two-dimensional coordinates of the explosion point: Assume that the horizontal coordinate of the camera pixel size is e1 and the vertical coordinate of the camera pixel size is e2. The two-dimensional coordinates (x_c, y_c) of the explosion point are: x_c=x C e1 y_c=y C e2 (5) Step 34, 2D coordinate calibration of the explosion point: Multiple measurement stations use the measured roll angle T Roll Perform spatial calibration on the two-dimensional coordinates of the explosion point to obtain the new two-dimensional coordinates (x, y) of the explosion point: x=x_c·cos(T Roll )+y_c·sin(T Roll ) (6) y=y_c·sin(T Roll )-x_c·sin(T Roll ) (7)。 4. The method according to claim 1, wherein Determine the location of the aerial bombing point, including: Step 41: Assume that the parameters of any two stations are: measurement station baseline distance L, yaw angle T Yaw1 and T Yaw2 , pitch angle T Pitch1 and T Pitch2 , focal length f, and the two-dimensional coordinates of the explosion point (x1, y1) and (x2, y2), the position of the explosion point in the air measured by the two stations based on the intersection algorithm is: In the formula, the subscript 1 in each parameter represents the parameter corresponding to the first site; the subscript 2 represents the parameter corresponding to the second site; Find multiple sets of aerial explosion point locations: Z1, Z2, ..., Zn; Step 42, average the positions of multiple aerial explosion points to obtain the final position of the aerial explosion point: Where n represents the number of explosion points.

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