Unscented kalman filter over unreliable communication networks with markovian packet dropouts

Li Li; Yuanqing Xia

doi:10.1109/TAC.2013.2263650

Unscented kalman filter over unreliable communication networks with markovian packet dropouts

Li Li
, Yuanqing Xia

School of Automation

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

63 Citations (Scopus)

Abstract

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 γ_k. The stability of the estimation error covariance matrices at packet reception times is analyzed. Sufficient conditions (related to H_k 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.

Original language	English
Article number	6517248
Pages (from-to)	3224-3230
Number of pages	7
Journal	IEEE Transactions on Automatic Control
Volume	58
Issue number	12
DOIs	https://doi.org/10.1109/TAC.2013.2263650
Publication status	Published - Dec 2013

Keywords

Markovian packet dropouts
Sojourn times
Stochastic stability
Unscented Kalman filtering

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10.1109/TAC.2013.2263650

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abstract = "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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AB - 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.

KW - Markovian packet dropouts

KW - Sojourn times

KW - Stochastic stability

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Unscented kalman filter over unreliable communication networks with markovian packet dropouts

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Keywords

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