Design and Analysis of Descent-to-Landing Navigation Incorporating Terrain Effects

Abstract

This study investigated the ability of a navigation filter to process multiple terrain-based sensors, such as slant-range, slant-speed, and terrain relative navigation sensors, during a descent-to-landing scenario to estimate the state of a landing vehicle. The filtering technique leveraged was based upon a factorized form of the multiplicative extended Kalman filter, and terrain-based measurements were fused with star camera and inertial measurement unit sensor returns to estimate the position, velocity, and attitude of the landing vehicle. Monte Carlo simulations were carried out to assess the performance of the navigation filter along a lunar descent trajectory, as well as the consistency of the filtering solutions. A comprehensive error budget was constructed, followed by a sensitivity analysis, to investigate the behavior of the filter uncertainty with respect to specific error sources. A final analysis was performed, in which the filter was subjected to terrain model mismatch.