Robust Mars Atmospheric Entry Integrated Navigation based on Parameter Sensitivity

TL;DR

This paper introduces a robust integrated navigation algorithm for Mars atmospheric entry that effectively mitigates the effects of atmospheric density and lift-to-drag ratio uncertainties using a specialized desensitized extended Kalman filter.

Contribution

It develops a novel robust ADEKF with analytical gain that minimizes sensitivity to key parameter uncertainties during Mars entry.

Findings

Reduces navigation errors caused by atmospheric density uncertainties

Improves consistency of navigation during Mars atmospheric entry

Demonstrates effectiveness through numerical simulations

Abstract

This paper presented a robust integrated navigation algorithm based on a special robust desensitized extended Kalman filtering with analytical gain (ADEKF) during the Mars atmospheric entry. The robust ADEKF is designed by minimizing a new function penalized by a trace weighted norm of the state error sensitivities and giving a closed-form gain matrix. The uncertainties of the Mars atmospheric density and the lift-to-drag ratio (LDR) percentage are modeled. Sensitivity matrices are defined to character the parameter uncertainties, and corresponding perturbation matrices are proposed to describe the navigation errors respected to the parameter uncertainties. The numerical simulation results show that the robust integrated navigation algorithm based on the robust ADEKF effectively reduces the negative effects of the two parameter uncertainties and has good consistency during the Mars entry.