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Relative motion and thrust estimation of a non-cooperative maneuvering target with adaptive filter

机译:自适应滤波器的非合作机动目标相对运动和推力估计

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With the rapid increase in the number of spacecraft in outer space, the unknown maneuvers of a spacecraft significantly increase the probability of a collision between neighborhoods. In order to guarantee the safety of an operational spacecraft, we need to estimate and predict the relative trajectories of a non-cooperative target in real time. Traditional filter routines are ineffective when the target spacecraft performs unknown continuous maneuvers. In this work, we focus on the development of relative estimators with enhanced robustness against unknown maneuvers. First, a variable state dimension estimator based on filter switching and covariance inflation is proposed to adaptively cope with a constant unknown maneuver. To strengthen the robustness in response to the time-varying maneuvers, a novel observer-enhanced Kalman filter is subsequently proposed by incorporating an observer into the filtering routines. Finally, the performance of the proposed estimators is evaluated with a series of numerical simulations, both the advantages and the disadvantages are analyzed using the simulation results.
机译:随着外层空间中航天器数量的迅速增加,航天器的未知动作大大增加了邻域之间发生碰撞的可能性。为了保证航天器的安全,我们需要实时估计和预测非合作目标的相对轨迹。当目标航天器执行未知的连续机动时,传统的过滤程序无效。在这项工作中,我们专注于相对估计器的开发,该估计器具有针对未知操作的增强的鲁棒性。首先,提出了一种基于滤波器切换和协方差膨胀的可变状态维估计器,以自适应地应对恒定的未知机动。为了增强响应时变机动的鲁棒性,随后通过将观察者并入滤波例程中,提出了新颖的观察者增强型卡尔曼滤波器。最后,通过一系列数值模拟对提出的估计器的性能进行了评估,并使用模拟结果分析了优缺点。

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