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• W2184232010 abstract "In this paper an estimation algorithm for a class of discrete- time nonlinear systems is proposed. The system structure we deal with is partitionable into subsystems, each affine w.r.t. the corresponding part of the state vector. The algorithm consists of a bank of interlaced Kalman filters, and each of them estimates a part of the state, considering the remaining parts as known time-varying parameters whose values are evaluated by the other filters at the previous step. The procedure neglects the subsystem coupling terms in the covariance matrix of the state estimation error and counteracts the errors so introduced by suitably increasing the noise covariance matrices. Comparisons through numerical simulations with the extended Kalman filter and its modified versions proposed in the literature illustrate the good tradeoff provided by the algorithm between the reduction of the computational load and the estimation accuracy." @default.
• W2184232010 created "2016-06-24" @default.
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• W2184232010 date "1999-01-01" @default.
• W2184232010 modified "2023-09-27" @default.
• W2184232010 title "Technical Notes and Correspondence An Interlaced Extended Kalman Filter" @default.
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