CN116123998A - Method for measuring overhead explosion points in real time based on video acquisition at multiple stations - Google Patents
Method for measuring overhead explosion points in real time based on video acquisition at multiple stations Download PDFInfo
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- CN116123998A CN116123998A CN202211621401.XA CN202211621401A CN116123998A CN 116123998 A CN116123998 A CN 116123998A CN 202211621401 A CN202211621401 A CN 202211621401A CN 116123998 A CN116123998 A CN 116123998A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
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- Length Measuring Devices By Optical Means (AREA)
Abstract
The application provides a method for measuring an air explosion point in real time based on video acquisition by multiple stations, which comprises the following steps: setting station setting parameters: laying a plurality of measurement sites according to actual conditions and initializing parameters; actual measurement of the station distribution parameters: the method comprises the steps of respectively measuring actual station distribution parameters of a plurality of measuring stations through a high-precision positioning module and a high-precision angle sensor module, and determining the distances among the measuring stations; determining and calibrating two-dimensional coordinates of a frying point: the plurality of measuring devices respectively acquire continuous video of the explosion point through the camera module, perform image processing to obtain two-dimensional coordinates of the explosion point, and perform space calibration on the two-dimensional coordinates of the explosion point; determining the position of an aerial bomb spot: and carrying out intersection processing according to the read parameters of the plurality of measurement stations to obtain the position of the overhead explosion point. The method and the device improve the accuracy of measuring the position of the overhead explosion point.
Description
Technical Field
The application relates to the technical field of bomb spot positioning, in particular to a method for measuring overhead bomb spots in real time based on video acquisition by multiple sites.
Background
The traditional aerial bomb spot position measuring algorithm is to shoot bomb spot images in different directions by using two high-speed cameras, calculate the position of the aerial bomb spot by using an intersection algorithm, and perform post-processing on the two acquired images based on a PC end. The traditional method needs to manually measure the distance between the devices, meanwhile, the influence of the roll angle of the devices on the measurement result is not considered, the measurement result is not time aligned, and meanwhile, the method has poor convenience and higher measurement error. In order to further improve the accuracy of measurement of the overhead explosion points and the convenience of the process, the satellite is adopted to measure the distance between equipment, the influence of the roll angle of the equipment is considered, and the real-time measurement of the overhead explosion points based on video acquisition by adopting multiple stations is very important.
The problems of the prior art are: the number of the designed equipment is small, the influence of the rolling angle of the equipment is ignored and the time alignment of the measurement result is not carried out, so that the measurement result precision is poor, the distance between the equipment is required to be measured manually, the workload of the measuring process of the explosion point is increased, and the acquired two images are subjected to post-processing based on the PC end, so that the real-time performance is not realized.
Disclosure of Invention
The application provides a real-time measurement method for an air explosion point based on video acquisition at multiple stations, which can be used for solving the technical problem of inaccurate measurement of the air explosion point caused by neglecting the influence of a roll angle of equipment.
The application provides a method for measuring an air explosion point in real time based on video acquisition by multiple stations, which comprises the following steps:
Optionally, the initialization parameters include a distance L between the plurality of measurement stations, a yaw angle T of each measurement station Yaw Pitch angle T Pitch 。
Optionally, the high-precision positioning module and the high-precision angle sensor module are used for respectively measuring actual station distribution parameters of a plurality of measurement stations and determining the distance between the measurement stations, and the method comprises the following steps:
step 21, determining the position parameters of the measurement site: measuring longitude S of multiple sites by high-precision positioning module i Latitude N j The method comprises the steps of carrying out a first treatment on the surface of the The high-precision positioning module is a multi-frequency RTK positioning and orientation module developed based on ZED-F9P, and the multi-frequency band receiver can provide centimeter-level precision in a few seconds and can simultaneously receive GPS, GLONASS, galileo and Beidou navigation signals;
step 22, according to longitude S i Latitude N j The baseline distance between any two measuring stations is obtained as follows:
wherein m is the interval when the latitude differs by 1 DEG, n is the interval when the longitude differs by 1 DEG, and the values are respectively as follows:
m＝111319.4888943678
step 23, determining measured angle parameters of the measurement station: measuring actual yaw angles T of multiple stations by using high-precision angle sensor module Yaw Pitch angle T Pitch Roll angle T Roll ；
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 calculation and Kalman dynamic filtering algorithm, adopts digital filtering processing, and integrates a gesture resolver in the high-precision angle sensor module to be matched with the dynamic Kalman filtering algorithm.
Optionally, the determining and calibrating the two-dimensional coordinates of the explosion point includes:
step 31, collection and processing of the video of the explosion point:
the cameras of the measuring stations respectively perform continuous video acquisition on the explosion points, and perform image graying and image segmentation processing to obtain binarization explosion point images;
step 32, determining the location of the centroid of the frying point:
assuming that the binarized frying point image has a frying point image size of M×N, determining the centroid position of the frying point based on a square weighted gray level gravity center method:
wherein, M, N explodes the pixel point of horizontal and vertical direction of the dot image; (x, y) is the coordinates of the corresponding pixel point in the bomb dot image; f (x, y) is the gray value of the corresponding pixel point, x C ，y C Horizontal and vertical coordinates for the centroid of the frying point being determined;
step 33, determining two-dimensional coordinates of the explosion point:
let the horizontal coordinate of the camera pixel size be e 1 Vertical coordinate e of camera pixel size 2 The two-dimensional coordinates (x_c, y_c) of the bomb spot are:
x_c＝x C e 1
y_c＝y C e 2 #(5)
step 34, calibrating two-dimensional coordinates of the explosion point: multiple measuring stations respectively utilizing the measured roll angle T Roll Performing space calibration on the two-dimensional coordinates of the explosion point to obtain 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)。
optionally, determining the overhead frying point location includes:
step 41, setting each parameter of any two stations as follows: measuring station baseline spacing L and yaw angle T Yaw1 And T Yaw2 Pitch angle T Pitch1 And T Pitch2 Focal length f and two-dimensional coordinates of the explosion point (x 1 ,y 1 ) And (x) 2 ,y 2 ) The air explosion point positions measured by two stations based on the intersection algorithm are as follows:
in the formula, subscript 1 in each parameter represents a parameter corresponding to a first site; subscript 2 represents a parameter corresponding to the second site;
solving a plurality of groups of air explosion point positions: z1, Z2, … and Zn;
step 42, averaging the multiple groups of air explosion point positions to obtain the final air explosion point position:
where n represents the number of burst points.
According to the method, parameters of the measuring station are actually measured through the high-precision positioning module and the high-precision angle sensor, the baseline interval error and the initial measurement value error of the measuring station are reduced, the two-dimensional coordinates of the explosion point are calibrated according to the measured parameters, the measurement precision of the position of the explosion point in the air is improved, and real-time processing is performed.
Drawings
FIG. 1 is a main flow chart of an air burst point position measurement algorithm provided in an embodiment of the present application;
FIG. 2 is a flowchart of a step of determining actual measurement station parameters according to an embodiment of the present application;
FIG. 3 is a flowchart of a two-dimensional coordinate determination and calibration procedure for a frying point according to an embodiment of the present application;
FIG. 4 is a flowchart illustrating steps for calculating the location of an overhead frying point according to an embodiment of the present disclosure;
fig. 5 is a schematic diagram of calculation of an overhead bomb spot position according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
The application provides a method for measuring an air explosion point in real time based on video acquisition by multiple stations, which comprises the following steps:
The initialization parameters include the distance L (unit meter) between a plurality of measuring stations, and the yaw angle T of each measuring station Yaw (unit degree), pitch angle T Pitch (in degrees).
Specifically, step 20 includes:
step 21, determining the position parameters of the measurement site: measuring longitude S of multiple sites by high-precision positioning module i Latitude N j The method comprises the steps of carrying out a first treatment on the surface of the The high-precision positioning module is a multi-frequency RTK positioning and orientation module developed based on ZED-F9P, and the multi-frequency band receiver can provide centimeter-level precision in a few seconds and can simultaneously receive GPS, GLONASS, galileo and Beidou navigation signals;
step 22, according to longitude S i Latitude N j The baseline distance between any two measuring stations is obtained as follows:
where m is a pitch when the latitude differs by 1 °, n is a pitch when the longitude differs by 1 °, and the values thereof are (in meters) respectively:
m＝111319.4888943678
step 23, determining measured angle parameters of the measurement station: measuring actual yaw angles T of multiple stations by using high-precision angle sensor module Yaw (unit degree), pitch angle T Pitch (unit degree), roll angle T Roll (in degrees);
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 calculation and Kalman dynamic filtering algorithm, can quickly calculate the current real-time motion gesture of the module, adopts digital filtering processing, can effectively reduce measurement noise and improves measurement precision; the high-precision angle sensor module is internally integrated with a gesture resolver, and is matched with a dynamic Kalman filtering algorithm, so that the current gesture of the module can be accurately output under a dynamic environment, the gesture measurement precision is 0.001 degree, and the stability is extremely high.
Specifically, step 30 includes:
step 31, collection and processing of the video of the explosion point:
the cameras of the measuring stations respectively perform continuous video acquisition on the explosion points, and perform image graying and image segmentation processing to obtain binarization explosion point images;
step 32, determining the location of the centroid of the frying point:
assuming that the binarized frying point image size is m×n (unit pixel), the centroid position of the frying point is determined based on the square weighted gray-scale gravity center method:
wherein, M, N explodes the pixel point of horizontal and vertical direction of the dot image; (x, y) is the coordinates of the corresponding pixel point in the bomb dot image; f (x, y) is the gray value of the corresponding pixel point, x C ，y C Horizontal and vertical coordinates for the centroid of the frying point being determined;
step 33, determining two-dimensional coordinates of the explosion point:
let the horizontal coordinate of the camera pixel size be e 1 Vertical coordinate e of camera pixel size 2 The two-dimensional coordinates (x_c, y_c) of the frying point (in meters) are:
x_c＝x C e 1
y_c＝y C e 2 #(5)
step 34, calibrating two-dimensional coordinates of the explosion point: multiple measuring stations respectively utilizing the measured roll angle T Roll Space calibration is carried out on the two-dimensional coordinates of the explosion point (unit degree), so that new two-dimensional coordinates (x, y) of the explosion point are obtained:
x＝x_c·cos(T Roll )+y_c·sin(T Roll )#(6)
y＝y_c·sin(T Roll )-x_c·sin(T Roll )#(7)。
Specifically, step 40 includes:
step 41, setting each parameter of any two stations as follows: measuring station baseline spacing L (unit meter), yaw angle T Yaw1 And T Yaw2 (unit degree), pitch angle T Pitch1 And T Pitch2 (unit degree), focal length f (unit meter), and two-dimensional coordinates of the frying point (x) 1 ,y 1 ) And (x) 2 ,y 2 ) The air explosion point positions measured by two stations based on the intersection algorithm are as follows:
in the formula, subscript 1 in each parameter represents a parameter corresponding to a first site; subscript 2 represents a parameter corresponding to the second site;
solving a plurality of groups of air explosion point positions: z1, Z2, … and Zn;
step 42, averaging the multiple groups of air explosion point positions to obtain the final air explosion point position:
where n represents the number of burst points.
According to the method, parameters of the measuring station are actually measured through the high-precision positioning module and the high-precision angle sensor, the baseline interval error and the initial measurement value error of the measuring station are reduced, the two-dimensional coordinates of the explosion point are calibrated according to the measured parameters, the measurement precision of the position of the explosion point in the air is improved, and real-time processing is performed.
The above-described embodiments of the present application are not intended to limit the scope of the present application.
Claims (5)
1. The method for measuring the overhead explosion points in real time based on video acquisition by multiple stations is characterized by comprising the following steps:
step 10, setting station setting parameters: laying a plurality of measurement sites according to actual conditions and initializing parameters;
step 20, actual measurement of station setting parameters is determined: the method comprises the steps of respectively measuring actual station distribution parameters of a plurality of measuring stations through a high-precision positioning module and a high-precision angle sensor module, and determining the distances among the measuring stations;
step 30, determining and calibrating two-dimensional coordinates of the explosion point: the plurality of measuring devices respectively acquire continuous video of the explosion point through the camera module, perform image processing to obtain two-dimensional coordinates of the explosion point, and perform space calibration on the two-dimensional coordinates of the explosion point;
step 40, determining the position of the overhead explosion point: and carrying out intersection processing according to the read parameters of the plurality of measurement stations to obtain the position of the overhead explosion point.
2. The method of claim 1, wherein the initialization parameters include a distance L between the plurality of measurement sites, a yaw angle T of each measurement site Yaw Pitch angle T Pitch 。
3. The method of claim 1, wherein measuring actual site placement parameters of the plurality of measurement sites and determining distances between the measurement sites by the high-precision positioning module and the high-precision angle sensor module, respectively, comprises:
step 21, determining the position parameters of the measurement site: measuring longitude S of multiple sites by high-precision positioning module i Latitude N j The method comprises the steps of carrying out a first treatment on the surface of the The high-precision positioning module is a multi-frequency RTK positioning and orientation module developed based on ZED-F9P, and the multi-frequency band receiver can provide centimeter-level precision in a few seconds and can simultaneously receive GPS, GLONASS, galileo and Beidou navigation signals;
step 22, according to longitude S i Latitude N j The baseline distance between any two measuring stations is obtained as follows:
wherein m is the interval when the latitude differs by 1 DEG, n is the interval when the longitude differs by 1 DEG, and the values are respectively as follows:
m＝111319.4888943678
step 23, determining measured angle parameters of the measurement station: measuring actual yaw angles T of multiple stations by using high-precision angle sensor module Yaw Pitch angle T Pitch Roll angle T Roll ；
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 calculation and Kalman dynamic filtering algorithm, adopts digital filtering processing, and integrates a gesture resolver in the high-precision angle sensor module to be matched with the dynamic Kalman filtering algorithm.
4. The method of claim 1, wherein the two-dimensional coordinates of the frying point are determined and calibrated, comprising:
step 31, collection and processing of the video of the explosion point:
the cameras of the measuring stations respectively perform continuous video acquisition on the explosion points, and perform image graying and image segmentation processing to obtain binarization explosion point images;
step 32, determining the location of the centroid of the frying point:
assuming that the binarized frying point image has a frying point image size of M×N, determining the centroid position of the frying point based on a square weighted gray level gravity center method:
wherein, M, N explodes the pixel point of horizontal and vertical direction of the dot image; (x, y) is the coordinates of the corresponding pixel point in the bomb dot image; f (x, y) is the gray value of the corresponding pixel point, x C ，y C Horizontal and vertical coordinates for the centroid of the frying point being determined;
step 33, determining two-dimensional coordinates of the explosion point:
let the horizontal coordinate of the camera pixel size be e 1 Vertical coordinate e of camera pixel size 2 The two-dimensional coordinates (x_c, y_c) of the bomb spot are:
x_c＝x C e 1
y_c＝y C e 2 #(5)
step 34, calibrating two-dimensional coordinates of the explosion point: multiple measuring stations respectively utilizing the measured roll angle T Roll Performing space calibration on the two-dimensional coordinates of the explosion point to obtain 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)。
5. the method of claim 1, wherein determining the overhead bomb spot location comprises:
step 41, setting each parameter of any two stations as follows: measuring station baseline spacing L and yaw angle T Yaw1 And T Yaw2 Pitch angle T Pitch1 And T Pitch2 Focal length f and two-dimensional coordinates of the explosion point (x 1 ,y 1 ) And (x) 2 ,y 2 ) The air explosion point positions measured by two stations based on the intersection algorithm are as follows:
in the formula, subscript 1 in each parameter represents a parameter corresponding to a first site; subscript 2 represents a parameter corresponding to the second site;
solving a plurality of groups of air explosion point positions: z1, Z2, … and Zn;
step 42, averaging the multiple groups of air explosion point positions to obtain the final air explosion point position:
where n represents the number of burst points.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117848169A (en) * | 2024-03-08 | 2024-04-09 | 中国科学院长春光学精密机械与物理研究所 | Automatic detection system and method for frying point time based on double-station intersection |
| CN117974967A (en) * | 2024-03-28 | 2024-05-03 | 沈阳长白电子应用设备有限公司 | Fried spot position measurement method based on image identification positioning |
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2022
- 2022-12-16 CN CN202211621401.XA patent/CN116123998A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117848169A (en) * | 2024-03-08 | 2024-04-09 | 中国科学院长春光学精密机械与物理研究所 | Automatic detection system and method for frying point time based on double-station intersection |
| CN117848169B (en) * | 2024-03-08 | 2024-04-30 | 中国科学院长春光学精密机械与物理研究所 | Automatic detection system and method for frying point time based on double-station intersection |
| CN117974967A (en) * | 2024-03-28 | 2024-05-03 | 沈阳长白电子应用设备有限公司 | Fried spot position measurement method based on image identification positioning |
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