Optimal Terrain-Aided Navigation Systems

摘要

The basic framework for applying Kalman filtering techniques to radar terrain-clearance data is investigated. By recursively Kalman processing each individual radar measurement separately, a whole new class of terrain-aided navigation schemes becomes available which in the past could not be developed using simple correlation algorithms. To diminish the effect of terrain nonlinearities, adaptive stochastic linearization techniques are utilized in a second-order filter formulation. As an application example results are presented indicating the performance improvements available through continuous terrain-aiding of an inertial, an air-data, and a velocity-sensing navigation system. (ERA citation 04:004080)