Unscented Kalman Filter Over Unreliable Communication Networks With Markovian Packet Dropouts

Unscented Kalman Filter Over Unreliable Communication Networks With Markovian Packet Dropouts
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针对具有马尔可夫数据包丢失的不可靠通信网络的无味卡尔曼滤波器

DOI:
10.1109/tac.2013.2263650
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发表时间:
2013-05
影响因子:
6.8
通讯作者:
Yuanqing Xia
Yuanqing Xia
中科院分区:
计算机科学2区
文献类型:
--
作者:
Li Li;Yuanqing Xia

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本文研究了离散时间修正无迹卡尔曼滤波(MUKF)通过网络将测量输出传输到滤波器时的稳定性。由于通信信道状态并不总是随时间变化,因此观测的到达被建模为两状态时齐马尔可夫过程γk。分析了估计误差协方差矩阵在分组接收时刻的稳定性。给出了峰值协方差稳定性和通常协方差稳定性的充分条件(与Hk和初始条件有关)。此外,不同类型的稳定性概念之间的关系示出了系统与独立同分布观测辍学。数值例子说明了所开发的技术的有效性。
The paper investigates the stability of the discrete-time modified unscented Kalman filter (MUKF) in transmitting measurement outputs to the filter via a network. Since the communication channel states do not always vary in time, the arrival of the observations is modeled as a two state time-homogeneous Markov process γk. The stability of the estimation error covariance matrices at packet reception times is analyzed. Sufficient conditions (related to Hk and the initial conditions) for the peak covariance stability and the usual covariance stability are given. Also the relationship between the different types of stability notions is illustrated for systems with i.i.d observation dropouts. Numerical example is given to illustrate the effectiveness of the techniques developed.
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