Abstract
Abstract A design procedure for the measurement process is proposed to decrease the computational burden of state estimation in linear discrete-time systems. System order reduction is involved, which is achieved by a derived transformation, yielding an alternative system and measurement process representation that includes time delays in both the system and the measurement process. Without loss of filter optimality, measurement designs yielding reductions in the computational requirements of the Kalman filter applied to the reduced order system are derived. A computational comparison is included to show that the proposed method, as opposed to the direct application of the Kalman filter, can yield large reductions in the filter computation time.
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