Moving target trajectory estimation using kalman, curve fitting and anfis methods

Timur İnan
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引用次数: 2

Abstract

Estimation of the possible position of the moving targets after a few steps has great significance especially in terms of defense industry. If a shoot aiming at the target is planned, the issue of estimation of forward position of the target gains importance in terms of accurate strike of the bullet at the target. In target tracking, impact of three different methods as motion estimation method on various motion types has been examined in our study. Motion types have been examined in four different types, which are rectilinear motion, circular motion, sinusoidal motion and curvilinear motion. On the other hand, estimation methods have been examined under three different titles. These are Kalman estimation method, curve fitting method and Anfis method. Different motion types have been examined with different estimation methods and the results obtained have been presented.
利用卡尔曼、曲线拟合和反算法进行运动目标轨迹估计
对移动目标经过几步后的可能位置进行估计具有重要的意义,特别是在国防工业方面。如果计划对目标进行射击,目标前方位置的估计问题在子弹准确击中目标方面变得重要。在目标跟踪中,我们研究了三种不同的运动估计方法对不同运动类型的影响。运动类型已经检查了四种不同的类型,即直线运动,圆周运动,正弦运动和曲线运动。另一方面,在三个不同的题目下审查了估计方法。这三种方法分别是卡尔曼估计法、曲线拟合法和安费斯法。用不同的估计方法研究了不同的运动类型,并给出了结果。
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