A system and method for detecting the point of detonation of an ammunition round

Abstract

This invention discloses a system and method for detecting ammunition detonation points, including detonation point measurement software, infrared image acquisition equipment, infrared positioning markers, meteorological information acquisition equipment, RTK base station, equipment and information acquisition unit, and basic support environment. This invention measures the detonation point using infrared images, calculates the detonation point using ballistic simulation, and then determines the detonation point through data fusion, which can greatly improve the accuracy and precision of detonation point detection.

Description

Technical Field

[0001] This invention relates to the field of training, and in particular to a system and method for detecting the detonation point of ammunition. Background Technology

[0002] Detection of detonation points in ammunition is crucial for equipment development, testing, and training, and has always been a key and challenging area of ​​research in the military field both domestically and internationally. Currently, detonation point coordinate detection technologies and methods are primarily based on the phenomenon of ammunition explosions. Representative detection technologies include: manual observation and measurement using a theodolite; electromagnetic wave detection technologies based on visible light, infrared, and radar; and mechanical wave detection technologies based on sound waves and seismic waves, each with its own advantages and disadvantages. For example, manual observation is simple but has low accuracy and poor real-time performance; visible light detection offers strong real-time performance but is significantly affected by visibility and smoke / dust; radar detection is suitable for beyond-visual-range and large targets but not for detecting the detonation points of artillery shells and obstacle-clearing projectiles; acoustic detection can be used 24 / 7 and in all weather conditions, but has a large error in detecting multiple detonations; seismic wave detection has high requirements for the soil conditions in the ammunition impact area, limiting its application; infrared detection has all-weather capability but has a large error in detecting the number of multiple detonations. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide an infrared image measurement method for the explosion point, which uses ballistic simulation to calculate the explosion point and then determines the explosion point through data fusion, thereby greatly improving the accuracy and precision of explosion point detection.

[0004] The technical solution to achieve the objective of this invention is as follows:

[0005] A munition detonation point detection system includes detonation point measurement software, infrared image acquisition equipment, infrared positioning markers, meteorological information acquisition equipment, RTK base station, equipment and information acquisition unit, and basic support environment;

[0006] The detonation point measurement software is used to collect firing parameters, equipment posture, meteorological information, infrared images, payload posture, and infrared positioning mark information to complete the detonation point calculation.

[0007] The infrared image acquisition device is used to acquire infrared images of ammunition detonation points and infrared positioning markers;

[0008] The infrared positioning marker provides accurate reference position information by subtracting the measured position from the actual position, and corrects the measured position of the explosion point.

[0009] The meteorological information acquisition equipment is used to measure meteorological information such as wind force, air pressure, temperature, and humidity in a local area of ​​the training ground, and provides it to the detonation point measurement software for ballistic simulation.

[0010] The RTK base station is used for differential positioning of infrared image acquisition equipment, infrared positioning markers, equipment and information acquisition units to improve positioning accuracy;

[0011] The equipment and information acquisition unit are used to collect information such as the position and firing parameters of the obstacle-breaking equipment and provide it to the detonation point measurement software for ballistic simulation.

[0012] The basic support environment is used to provide the computing services, storage services, communication services, positioning services, timing services, meteorological services, ballistic models, geographic information, and historical test data required for system operation.

[0013] The detection method is as follows:

[0014] (1) Complete the initial deployment of the system, including starting the explosion point measurement software, setting up RTK base stations, setting up infrared positioning markers, planning UAV flight paths, and testing the communication of the entire system;

[0015] (2) The equipment and information collection unit collects shooting parameters and equipment position data, while the meteorological information collection equipment collects meteorological information such as wind force, air pressure, temperature, and humidity in the local area of ​​the training ground. All of the above data are sent to the shooting information processing module for comprehensive processing in real time.

[0016] (3) The ballistic simulation module combines firing parameters, equipment position, meteorological information, ballistic model and other data to complete the ballistic simulation;

[0017] (4) The detonation point simulation module combines geographic information data and ballistic simulation data to complete the simulation calculation of the detonation point;

[0018] (5) The infrared image acquisition device acquires infrared images of the ammunition detonation point and infrared positioning markers and sends them to the infrared image processing module in real time; it also acquires infrared load pose information and sends it to the detonation point measurement module.

[0019] (6) The infrared image processing module completes the analysis, identification and extraction of infrared features of the explosion point, the determination of the explosion point center, and the calculation of the relative position between the explosion point center and the infrared positioning mark.

[0020] (7) The detonation point measurement module uses the relative position of the detonation point center and the infrared positioning marker provided by the infrared image processing module, and combines this with the position of the infrared marker and the pose information of the infrared load, to correct the position of the detonation point. The specific method is as follows: assuming the actual position coordinates of the infrared marker are (x... hs ,y hs The measured coordinate position is (x hc ,y hc The actual location coordinates of the explosion point are (x... bs ,y bs The measured coordinate position is (x bc ,ybc The distance between the drone and the infrared marker is L. h The distance from the explosion point is L b The actual location of the explosion point (x) bs ,y bs )=(x bc ,y bc )+L b / L h ((x hs ,y hs )-(x hc ,y hc ));

[0021] (8) The explosion point calculation module combines the explosion point location measured by the explosion point measurement module and the explosion point location simulated by the explosion point simulation module, and calculates the actual location of the explosion point through a data fusion algorithm.

[0022] (9) The deep learning module 17 continuously optimizes the algorithm model of the explosion point calculation module by learning historical experimental data and explosion point data calculated by this system, so as to improve the accuracy and precision of explosion point calculation.

[0023] The technical effects of this invention are as follows:

[0024] (1) The accuracy of detonation point coordinate detection was improved by using infrared positioning markers.

[0025] A method to improve the accuracy of detonation point measurement using infrared positioning markers is proposed. This method involves using the difference between the measured position of the infrared positioning marker and the actual position to correct the measured position of the detonation point, thereby improving the accuracy of the detonation point measurement.

[0026] (2) Combining aerial observation with ballistic simulation improves the accuracy of detecting the number of detonation points.

[0027] When multiple munitions detonate simultaneously, an unmanned aerial vehicle (UAV) platform is used to collect infrared images of the detonation points from an aerial perspective. This improves the visibility and field of view of the observation, reduces the impact of the merging and adhesion between infrared images of the detonation points during multiple explosions on the measurement of the number of detonation points, and, combined with simulated detonation point data, significantly improves the accuracy of detonation point detection through data fusion algorithms. Attached Figure Description

[0028] Figure 1 System composition and principle diagram; overall structure of the invention. Detailed Implementation

[0029] The present invention will now be described in detail with reference to the accompanying drawings. The embodiments listed are only for the purpose of helping to understand the present invention and should not be construed as limiting the scope of protection of the invention. For those skilled in the art, improvements and modifications can be made to the present invention without departing from the principles and ideas of the present invention, and such improvements and modifications also fall within the scope of protection of the claims of the present invention.

[0030] Combination Figure 1 As shown, the present invention includes explosion point measurement software 1, infrared image acquisition device 2, infrared positioning marker 3, meteorological information acquisition device 4, RTK base station 5, equipment and information acquisition unit 6, and basic support environment 7.

[0031] The detonation point measurement software 1 includes a shooting information processing module 11, a ballistic simulation module 12, a detonation point simulation module 13, an infrared image processing module 14, a detonation point measurement module 15, a detonation point calculation module 16, and a deep learning module 17.

[0032] The shooting information processing module 11 is used to receive shooting parameters, equipment position and attitude data provided by the equipment and information acquisition unit 6, and meteorological information such as wind force, air pressure, temperature and humidity provided by the meteorological information acquisition device 4. After comprehensive processing, it is sent to the ballistic simulation module 12.

[0033] The ballistic simulation module 12 performs ballistic simulation calculations based on the data provided by the shooting information processing module 11 and the ballistic model.

[0034] The detonation point simulation module 13, in conjunction with the ballistic data provided by the ballistic simulation module 12 and the geographic information data, is used for the simulation calculation of the detonation point.

[0035] The infrared image processing module 14 is used to receive infrared images captured in real time by the infrared image acquisition device 4, and to perform infrared feature analysis, identification and extraction of the explosion point, determination of the explosion point center, and calculation of the relative position between the explosion point center and the infrared positioning marker 3.

[0036] The detonation point measurement module 15 is used to receive the relative position data between the detonation point center and the infrared positioning marker 3 after processing by the infrared image processing module 14, and combine it with the pose data of the infrared image acquisition device 2 and the position information of the infrared positioning marker 3 to realize the measurement of the detonation point.

[0037] The explosion point calculation module 16 is used to receive the measured explosion point data provided by the explosion point measurement module 15, receive the simulated explosion point data provided by the explosion point simulation module 13, and complete the explosion point calculation through a data fusion algorithm.

[0038] The deep learning module 17 can continuously optimize the algorithm model of the explosion point calculation module 16 by learning historical experimental data and explosion point data calculated by the system.

[0039] The infrared image acquisition device 2 is used to acquire infrared images of ammunition detonation points and infrared positioning markers 3, and mainly consists of a drone, an infrared payload, and a Beidou positioning module a.

[0040] The drone is a multi-rotor drone, mainly used to carry infrared payloads and Beidou positioning modules.

[0041] The infrared payload is mainly used to acquire infrared images in real time and can autonomously measure its own pitch angle and other attitude information.

[0042] The Beidou positioning module a is used to measure the position information of the infrared payload and perform differential positioning through the RTK base station to improve positioning accuracy.

[0043] The infrared positioning marker 3 is mainly used to provide accurate reference position information to improve the accuracy of detonation point measurement. It mainly consists of a flexible low emissivity target, a Beidou positioning module b, and a ground fixation device.

[0044] The flexible low emissivity target is a material with low infrared radiation characteristics. In infrared images, it forms a clear grayscale contrast with the high infrared radiation characteristics of the explosion point, and is mainly used for the accurate identification of infrared positioning markers.

[0045] The Beidou positioning module b is used to measure the location information of the infrared positioning marker and perform differential positioning through the RTK base station to improve positioning accuracy.

[0046] The meteorological information acquisition device 4 is mainly used to measure meteorological information such as wind force, air pressure, temperature, and humidity in a local area of ​​the training ground, and to provide it to the detonation point measurement software 1 for ballistic simulation.

[0047] The RTK base station 5 is mainly used for differential positioning of the infrared image acquisition device 2, infrared positioning marker 3, equipment and information acquisition unit 6, so as to improve positioning accuracy.

[0048] The equipment and information acquisition unit 6 is mainly used to collect information such as the position and firing parameters of the obstacle-breaking equipment and provide it to the detonation point measurement software 1 for ballistic simulation. It mainly consists of obstacle-breaking equipment, information acquisition device, Beidou positioning module c, etc.

[0049] The information collector is mainly used to collect data such as the firing parameters, attitude information, and ammunition firing time of the equipment, and to provide the data to the detonation point measurement software 1 for ballistic simulation.

[0050] The Beidou positioning module c is used to measure the location information of the obstacle-clearing equipment and perform differential positioning through RTK base stations to improve positioning accuracy.

[0051] The basic support environment 7 mainly provides computing services, storage services, communication services, positioning services, timing services, meteorological services, ballistic models, geographic information, historical test data and other data required for system operation.

[0052] A method for detecting the detonation point of ammunition, the procedure of which includes the following steps:

[0053] (1) Complete the initial deployment of the system, including starting the explosion point measurement software 1, setting up RTK base stations 5, setting up infrared positioning markers 3, planning UAV flight paths, and testing the communication of the entire system;

[0054] (2) The equipment and information collection unit 6 collects shooting parameters and equipment position data, and the meteorological information collection device 4 collects meteorological information such as wind force, air pressure, temperature and humidity in the local area of ​​the training ground. All of the above data are sent to the shooting information processing module 11 for comprehensive processing in real time.

[0055] (3) The ballistic simulation module 12 combines firing parameters, equipment position, meteorological information, ballistic model and other data to complete the ballistic simulation;

[0056] (4) The explosion point simulation module 13 combines geographic information data and ballistic simulation data to complete the simulation calculation of the explosion point;

[0057] (5) The infrared image acquisition device 2 acquires infrared images of the ammunition detonation point and the infrared positioning mark 3 and sends them to the infrared image processing module 14 in real time; it also acquires the infrared load pose and sends it to the detonation point measurement module 15.

[0058] (6) The infrared image processing module 14 completes the analysis, identification and extraction of infrared features of the explosion point, the determination of the explosion point center, and the calculation of the relative position between the explosion point center and the infrared positioning mark 3.

[0059] (7) The detonation point measurement module 15 corrects the position of the detonation point by using the relative position of the detonation point center and the infrared positioning marker 3 provided by the infrared image processing module 14, and by combining the position of the infrared positioning marker and the infrared load pose information. The specific method is as follows: assuming the actual position coordinates of the infrared marker are (x... hs ,y hs The measured coordinate position is (x hc ,y hc The actual location coordinates of the explosion point are (x... bs ,y bs The measured coordinate position is (x bc ,y bc The distance between the drone and the infrared marker is L.h The distance from the explosion point is L b The actual location of the explosion point (x) bs ,y bs )=(x bc ,y bc )+L b / L h ((x hs ,y hs )-(x hc ,y hc ));

[0060] (8) The explosion point calculation module 16 combines the explosion point position measured by the explosion point measurement module 15 and the explosion point position simulated by the explosion point simulation module 13 to calculate the actual position of the explosion point through a data fusion algorithm.

[0061] (9) The deep learning module 17 continuously optimizes the algorithm model of the explosion point calculation module 16 by learning historical experimental data and explosion point data calculated by the system, so as to improve the accuracy and precision of explosion point calculation.

Claims

1. A system for detecting the detonation point of ammunition, characterized in that, It includes explosive point measurement software (1), infrared image acquisition equipment (2), infrared positioning markers (3), meteorological information acquisition equipment (4), RTK base station (5), equipment and information acquisition unit (6), and basic support environment (7); The detonation point measurement software (1) is used to collect firing parameters, equipment posture, meteorological information, infrared images, load posture and infrared positioning mark information to complete the detonation point calculation; The infrared image acquisition device (2) is used to acquire infrared images of ammunition detonation points and infrared positioning markers; The infrared positioning marker (3) provides accurate reference position information by making a difference between the measured position and the actual position, and corrects the measured position of the explosion point; The meteorological information acquisition device (4) is used to measure the meteorological information of a local area of ​​the training ground and provide it to the detonation point measurement software for ballistic simulation. The RTK base station (5) is used for differential positioning of infrared image acquisition equipment, infrared positioning markers, equipment and information acquisition units to improve positioning accuracy; The equipment and information acquisition unit (6) is used to acquire the position and firing data of the obstacle-breaking equipment and provide it to the detonation point measurement software for ballistic simulation. The basic support environment (7) is used to provide the computing services, storage services, communication services, positioning services, timing services, meteorological services, ballistic models, geographic information and historical test data required for system operation; The infrared image acquisition device (2) includes a drone, an infrared payload, and a Beidou positioning module a. The drone is used to carry the infrared payload and the Beidou positioning module a. The infrared payload is used to acquire infrared images in real time and autonomously measure its own pitch angle attitude information. The Beidou positioning module a is used to measure the position information of the infrared payload and perform differential positioning through an RTK base station. The infrared positioning marker (3) includes a flexible low emissivity target, a Beidou positioning module b, and a ground fixer. The flexible low emissivity target is made of a material with low infrared radiation characteristics, which forms a grayscale contrast with the high infrared radiation characteristics of the explosion point in the infrared image. The Beidou positioning module b is used to measure the position information of the infrared positioning marker 3 and perform differential positioning through an RTK base station. The explosion point measurement software (1) includes a shooting information processing module (11), a ballistic simulation module (12), an explosion point simulation module (13), an infrared image processing module (14), an explosion point measurement module (15), an explosion point calculation module (16), and a deep learning module (17).

2. The ammunition detonation point detection system according to claim 1, characterized in that, The equipment and information acquisition unit (6) includes obstacle-breaking equipment, information acquisition device and Beidou positioning module c. The information acquisition device is used to collect the firing parameters, attitude information and ammunition firing time data of the equipment, and provide the data to the detonation point measurement software (1) for ballistic simulation. The Beidou positioning module c is used to measure the position information of the obstacle-breaking equipment and perform differential positioning through RTK base station.

3. The ammunition detonation point detection system according to claim 1, characterized in that, The drone in question is a multi-rotor drone.

4. A method for detecting the detonation point of ammunition, applicable to the ammunition detonation point detection system according to any one of claims 1-3, characterized in that, Complete the initial deployment of the system, including starting the explosion point measurement software (1), setting up the RTK base station (5), setting up the infrared positioning marker (3), planning the UAV trajectory, and testing the communication of the entire system; The shooting parameters and equipment posture data collected by the equipment and information collection unit (6) and the meteorological information data of the local area of ​​the training ground collected by the meteorological information collection device (4) are sent to the shooting information processing module (11) in real time for comprehensive processing. The ballistic simulation module (12) combines firing parameters, equipment posture, meteorological information, and ballistic model to complete ballistic simulation. The detonation point simulation module (13) combines geographic information data and ballistic simulation data to complete the simulation calculation of the detonation point; The infrared image acquisition device (2) acquires infrared images of the ammunition detonation point and the infrared positioning mark, and sends them to the infrared image processing module (14) in real time; it acquires infrared load pose information and sends it to the detonation point measurement module (15); the infrared image processing module (14) completes the infrared feature analysis, identification and extraction of the detonation point, the determination of the detonation point center, and the calculation and processing of the relative position between the detonation point center and the infrared positioning mark (3); The detonation point measurement module 15 corrects the position of the detonation point by using the relative position of the detonation point center and the infrared positioning mark (3) provided by the infrared image processing module (14) and combining the position of the infrared positioning mark and the infrared load pose information. The explosion point calculation module (16) combines the explosion point measurement module (15) measuring the explosion point position and the explosion point simulation module (13) simulating the explosion point position, and calculates the actual position of the explosion point through a data fusion algorithm. When multiple munitions detonate simultaneously, the UAV is used to collect infrared images of the detonation points from an aerial perspective, improving the visibility and field of view of the observation, reducing the impact of the merging and adhesion between the infrared images of the detonation points when multiple munitions explode on the measurement of the number of detonation points, and then combining the simulated detonation point positions with the data fusion algorithm to calculate the actual position of the detonation point. The deep learning module (17) continuously optimizes the algorithm model of the explosion point calculation module (16) by learning historical experimental data and explosion point data calculated by the system.

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