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首页> 外文期刊>Aerospace and Electronic Systems, IEEE Transactions on >Tracking Reentry Ballistic Targets using Acceleration and Jerk Models
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Tracking Reentry Ballistic Targets using Acceleration and Jerk Models

机译：使用加速度和加速度率模型跟踪再入弹道目标

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摘要

In this paper an acceleration model and a jerk model are proposed for estimation of the kinematic state of reentry ballistic targets (RBTs) using extended Kalman filters (EKF). The models proposed here use the equations of target kinematics only and do not assume any model parameterization for variation of the ballistic coefficient and air density a priori, as found in the literature. The novelty lies in estimation of the ratio ($gamma$) of air density and ballistic coefficient and its time derivatives using a separate Kalman filter (KF) ($gamma$-filter) which utilizes pseudo measurements of $gamma$ computed from the velocity and acceleration estimated by the EKF at each time step. The parameter $gamma$ and its derivatives estimated by the $gamma$-filter are, in turn, used for the estimation of position, velocity, acceleration, and jerk in the EKF. The use of the pseudo measurements of $gamma$ makes the algorithms inherently adaptive to variations of the ballistic coefficient and air density during reentry. A comparative assessment of several dynamic models for reentry of ballistic targets reported in the literature and those proposed here demonstrates that the estimation errors in velocity and acceleration are significantly less for the proposed models compared with the existing ones.
机译：本文提出了一种加速模型和加加速度模型，用于使用扩展卡尔曼滤波器（EKF）估算再入弹道目标（RBT）的运动状态。如文献中所发现的，这里提出的模型仅使用目标运动学方程，并且不假设任何模型参数用于先验地改变弹道系数和空气密度。新颖之处在于使用单独的卡尔曼滤波器（KF）（$伽马滤波器）估算空气密度与弹道系数之比（$伽马）及其时间导数，该滤波器利用根据速度计算出的伪伽马值EKF在每个时间步长估算的加速度。反过来，由$ gamma $滤波器估计的参数$ gamma $及其导数用于估计EKF中的位置，速度，加速度和加速度。伪测量值γ的使用使算法固有地适应了折返过程中弹道系数和空气密度的变化。对文献中报告的和本文提出的弹道目标再入的几种动态模型进行的比较评估表明，与现有模型相比，所提出模型的速度和加速度估计误差明显较小。

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