Analysis and order reduction of an autonomous lunar lander navigation system
A navigation system for precision lunar descent and landing is presented and analyzed. The navigation algorithm is based upon the extended Kalman Filter and employs measurements from an inertial measurement unit to propagate the vehicle position, velocity, and attitude forward in time. External measurements from an altimeter, star camera, terrain camera, and velocimeter are utilized in state estimate updates. The navigation algorithm also attempts to estimate the values of uncertain parameters associated with the sensors. The navigation algorithm also estimates the map-tie angle of the landing site which is a measure of the misalignment of the actual landing site location on the surface of the Moon versus the estimated position of the landing site.
The navigation algorithm is subject to a sensitivity analysis which investigates the contribution of each error source to the total estimation performance of the navigation system. Per the results of the sensitivity analysis, it is found that certain error sources need not be actively estimated to achieve similar estimation performance at a reduced computational burden. A new, reduced-order system is presented and tested through covariance analysis and a monte carlo analysis. The new system is shown to have comparable estimation performance at a fraction of the computer run-time, making it more suitable for a real-time implementation.