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Performance Comparison of the two-stage Kalman Filtering Techniques for Density Prediction

Saeid Zoghi

Abstract


The advanced optimal partitioned state Kalman estimator (OPSKE) developed to overwhelm these problems of traditional approaches. In this article, we compare performance of the OPSKE with the OTSKE and the AUSKE in the maneuvering target tracking (MTT) badly behaved. We provide some analytic results to demonstrate the computational advantages of the OPSKE. Author of this paper compare these two algorithms with target tracking problem, because in that problem they dealing with so many parameters which are useful for estimating the workability of such filters. As a result, we introduce the better filter for estimation and prediction and we discuss about different applications of such filter in chemical engineering, for example, the amount of density or degree of different dopants in a special wafer.

Keywords: estimation, new predictor, Kalman filtering in chemical engineering, prediction

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References


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DOI: https://doi.org/10.37628/ijmdic.v2i1.180

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