Research On Calibration Of Rifle Shooting Target

Rifle Shooting is the military, armed police, public the necessary content of the training, It is one of the subjects which were trained hard risk. The gunman at present mainly rely on experience and their own judgment for aimed shot, individual countries use a single sensor to detect the surrounding environment in order to determine the gunman firing position, battlefield environment rapidly changing, many factors affect the shooter aiming position, considering the influence the bullet flying mainly by wind speed and direction, temperature, humidity and air pressure, and if you use a single sensor to detect an environmental parameter is difficult to make shooters do first hit, therefore, the use of multi-sensor measurement environment parameters, then conveying the measured data to the controller, considering multi-sensor in the testing environment of environmental parameters in the existence of false noise, when the Controller processing the sensor input data cannot eliminate the noise.Against these problems, In this paper, in order to eliminate multi-sensor generated false noise when detection the shooter surrounding environmental parameters, more accurately using the detected parameters, thus the displacement can be accurate fusion. On the basis of the In-depth study estimation theory fusion, Through two aspects to study displacement fusion problem when the shooters shooting, on the one hand the deficiency of the existing weighted fusion algorithm, proposed an improved weighted fusion method, And to apply this method for a shooter aiming position displacement fusion; first, based on the classic kalman filtering algorithm study realize the principle of the centralized filtering algorithm kalman, federal kalman filtering algorithm and adaptive kalman filtering algorithm, and through the simulation analysis to study the fusion precision of three algorithms, secondly based on kinetic theory established the model of shooter in the firing position sighting,the shooters need to target transformation location as a maneuvering target, finally, as the shooter needs to aim location for a maneuvering target, for the first time to adopt adaptive Kalman filtering algorithm for a specific instance of multiple displacement data fusion.The results show, sequential dynamic weighted fusion algorithm proposed fusion accuracy is high than the existing weighted fusion algorithm; the simulation analysis shows, adaptive Fusion precision kalman filtering algorithm is high than centralized filtering algorithm kalman and federal kalman filtering algorithm; verified by an example, Sequential dynamic weighted fusion algorithm and adaptive kalman Filtering Fusion Algorithm have a certain fusion ability to shooter aiming the change of the position of the displacement data, can reflect the need to Shooters aim position when he shooting. So the research of this article has a certain practicality.