Moving-horizon estimation approach for nonlinear systems with measurement contaminated by outliers

Moath Jamal Awawdeh (Higher Colleges of Technology (HCT))
Tarig Faisal (Higher Colleges of Technology (HCT))
Anees Bashir (Higher Colleges of Technology (HCT))
Abdel Ilah Nour Alshbatat (Tafila Technical University)
Rana T. H. Momani (Zarqa University)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 22, No 1: February 2024

An application of moving-horizon strategy for nonlinear systems with possible outliers in measurements is addressed. With the increased success of movinghorizon strategy in the state estimation for linear systems with outliers acting on the measurement, investigating the nonlinear approach is highly required. In this paper we applied the nonlinear version which has been presented in the literature in term of discrete-time linear time-invariant systems, where the applied strategy considers minimizing a least-squares functions in which each measure possibly contaminated by outlier is left out in turn and the lowest cost is propagated. The moving horizon filter effectiveness as compared with the extended Kalman filter is shown by means of simulation example and estimation error comparison. The moving horizon filter shows the feature of resisting outliers with robust estimation