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Abstract

In this article, a robust non-linear recursive algorithm, featuring a highly reduced computational load, is proposed to estimate the thrust acceleration of a typical flight vehicle. The robustness of this new algorithm allows a significant increase of deviations in initial values of the estimated parameters. In the proposed algorithm, at first, a transformation of the non-linear measurement equation to a linear one, without any approximation, is obtained. Then the recursive least squares algorithm is applied to the transformed equation. The maximum achievable accuracy of the estimation for the non-linear problem is obtained analytically by the Cramer—Rao lower bound and is compared with simulation results. Extensive simulations showed that the new method provides an unbiased as well as a more robust thrust acceleration estimate in comparison with the extended Kalman filter. Moreover, the proposed method is beneficial in that it has a lower number of parameters and results in a simple design with less computational effort.

Keywords

thrust acceleration non-linear recursive least squares extended Kalman filter robustness

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Thrust acceleration estimation using an on-line non-linear recursive least squares algorithm

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