A New Estimation Algorithm from Measurements with Multiple-Step Random Delays and Packet Dropouts. (7th April 2010)

• Record Type: Journal Article
• Authors: Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.
• Other Names: Chou Jyh Horng Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2010(2010)
• Publication Date: 2010-04-07
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2010/258065
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The least-squares linear estimation problem using covariance information is addressed in discrete-time linear stochastic systems with bounded random observation delays which can lead to bounded packet dropouts. A recursive algorithm, including the computation of predictor, filter, and fixed-point smoother, is obtained by an innovation approach. The random delays are modeled by introducing some Bernoulli random variables with known distributions in the system description. The derivation of the proposed estimation algorithm does not require full knowledge of the state-space model generating the signal to be estimated, but only the delay probabilities and the covariance functions of the processes involved in the observation equation.