Innovative Mars entry integrated navigation using modified multiple model adaptive estimation

Abstract A variety of anticipated missions to Mars, such as Mars base and sample return, will have to utilize precision navigation and guidance for their hypersonic entry to achieve the required landing accuracy. In order to effectively reduce the adverse impact of initial state errors and parameter uncertainties during Mars atmospheric entry and then improve entry navigation accuracy, an innovative high-precision integrated navigation algorithm for Mars entry is developed based on a modified multiple model adaptive estimation (MMAE) in this paper. First, a six degree-of-freedom (DOF) Mars entry dynamics model is derived based on the angular velocity outputs of a gyro, which can be more complete and accurate description of the state variables of an entry vehicle than the traditional three DOF dynamics models. Second, both the accelerometer outputs and radiometric measurements are adopted as the navigation observations embedded to Kalman filter bank to perform state estimation and suppress the measurement noise. Finally, a new modified multiple model adaptive estimation algorithm with exponential decay terms is proposed to overcome the inherent drawback of classical MMAE and then further improve navigation accuracy. The numerical simulation results show that the integrated navigation algorithm developed in this paper is able to accurately estimate the state variables of an entry vehicle, even in the case that the initial entry state errors and larger parameter uncertainties are taken into account.