摘要
目标距离是战场进行作战决策和武器使用时考虑的一个重要参数。在传统的二维被动跟踪系统基础上,将目标建模为椭圆刚体。论文借鉴修正极坐标(MPC)的思想,利用刚体目标的尺寸参数,建立目标的状态模型和测量模型。采用无迹卡尔曼滤波(UKF)算法进行解距离,为工程实现提供了可能性,并从不同的初始条件下分析了距离误差。Monte-Carlo仿真表明:在新的状态模型下利用UKF算法进行解距离,可以达到较高的精度。其中传感器与目标的相对速度和刚体目标的尺寸对距离解的精度影响较大。
Target distance is an important parameter for war decision and weapon attack on the battlefield. Elliptical target are intro- duced into the traditional bearing-only tracking system. New state and measurement models are presented by using the dimension of rigid tar get and design idea of Modified Polar Coordinate（MPC）. Solving distance by using Unscented Kalman Filter（UKF） can be implemented in engineering, the error of distance solving from different initial conditions is analyzed. Monte-Carlo simulation results show that higher preci- sion of distance solving can be achieved by using UKF. Also the speed between target and the observer and the dimension of the target play more important role in the precision of distance solving.
出处
《计算机与数字工程》
2013年第7期1070-1073,共4页
Computer & Digital Engineering
基金
国家自然科学基金项目(编号:61104186)资助
关键词
非质点
纯方位
非线性滤波器
解距离
non-particle
bearing-only
nonlinear filter
distance solving
