FADS based aerodynamic parameters estimation for mars entry considering fault detection and tolerance

Abstract Flush air data system (FADS) is able to sense pressure distribution on the surface of the vehicle's forebody during Mars entry phase. Existing studies on the FADS-based aerodynamics data estimation for Mars entry have not attached adequate attention to the potential FADS fault, which should not be ignored in practice from a reliability viewpoint. In this paper, a hybrid method is proposed to simultaneously achieve aerodynamic parameters estimation of Mars entry vehicle and FADS fault detection and tolerance. The estimation procedure merges triples algorithm based coarse estimation with least-square based precise estimation. Meanwhile, a fault identifier matrix is embedded in the estimation procedure, which is worked out from chi-square detection algorithm. The estimation with FADS fault tolerance is realized by the fusion of chi-square detection, hybrid estimation, and random sample consensus algorithms. Comparison simulations demonstrate the effectiveness of the proposed technique.

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