High-precision pose and velocity measuring method for projectiles based on kalman filtering algorithm
Liang Zhang, Lizhi Qian, Quan Li Ning, Jingxiao Wang · 2015
An original method is presented in this paper, which attempts to make use of the kalman filtering algorithm and maintain accuracy in position, attitude and velocity estimation for a fast moving projectile, the velocity and the pose (position and attitude) could also be obtained, then the simulation are presented and compared with the conventional least square method.The simulation result showed that the kalman filter algorithm is more accurate and stability than the conventional least squares algorithm, meanwhile, the trajectory of the projectile obtained by the kalman filter algorithm is very close to the real trajectory. 1.IntroductionIt is necessary to capture the motion parameters of fast moving projectiles, such as pose (including position and attitude), velocity (including speed and moving direction), and angle of attack (AOA, the angle of the attitude and the moving direction).These parameters have major influence on the weapon performance and accuracy.Until recently, many optoelectronic-based [1-2], image-based methods [3-6], etc., have been employed to perform this task.Because of the relatively high precision signal that the radar systems could provide, and maturity of the signal processing algorithms, radar tracking methods have many benefits against alternative methods especially the target is a fast moving [7][8][9].Therefore, it is a trend to develop a new method for projectile tracking such as high-precision pose and velocity measuring.An original method is presented in this paper, which attempts to make use of the kalman filtering algorithm and maintain accuracy in position, attitude and velocity estimation for a fast moving projectile, the velocity and the pose (position and attitude) could also be obtained, then the simulation are presented and compared with the conventional least square method. Measuring method for projectiles trackingIn order to capture the motion parameters of fast moving projectiles, it can be divided into three steps.Firstly, a system of gathering data about where the projectile is located should be provided.The system discussed in this paper is radar.Secondly, a method for accurate estimation of the projectile's position, velocity should be presented.The method used in this paper is kalman filtering algorithm for projectiles tracking, finally, once the enough data can be collected and analyzed, the projectile trajectory can be determined and simulated using the computer 3.Target detectionThe purpose of this step is to take raw environmental data and turn it into a series of points plotted in Cartesian space.These points represent the trajectory of the projectile and are made up of a list of points (x0, y0, z0).. (xn, yn, zn) where n is the number of positions sampled and a time difference t which is the time difference between each sample [10].For tracking objects at both long and short distances, Tracking radar systems are used to measure the target's relative position in range, azimuth angle, elevation angle, and velocity.Then, by using and keeping track of these measured parameters the radar can predict their future values.Target tracking is important to military radars as well as to most civilian radars.In military radars, tracking