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Kalman filtering with mixed discrete-continuous observations

机译:混合离散连续观测值的卡尔曼滤波

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The optimal filtering problem for systems subject to both the discrete and continuous measurements is studied. The observability and detectability properties of such systems are investigated pointing out their connections with the existence of stable discrete-continuous observers. The optimal filter is based on the solution of a suitable matrix differential Riccati equation with jumps. Sufficient and necessary conditions for the existence of periodic stabilizing solutions to such an equation are worked out. The main result states that both detectability and stabilizability are necessary and sufficient for the existence of a unique periodic solution which is also stabilizing. Stabilizability and detectability also guarantee asymptotic convergence of the Kalman filter to the steady-state periodic filter irrespective of the initial state covariance. The results are illustrated by means of a numerical example. [References: 17]
机译:研究了经受离散和连续测量的系统的最佳滤波问题。研究了这种系统的可观察性和可检测性,指出了它们与稳定离散连续观测器的存在的联系。最佳滤波器基于具有跳变的合适矩阵微分Riccati方程的解。给出了存在该方程周期稳定解的充分必要条件。主要结果表明,可检测性和稳定性对于既具有稳定性也具有唯一性的周期性解的存在是必要和充分的。稳定度和可检测性也保证了卡尔曼滤波器到稳态周期滤波器的渐近收敛性,而与初始状态协方差无关。结果通过数字示例说明。 [参考:17]

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