Improvement of terrain-aided navigation via trajectory optimization

This paper proposes a novel method for improving the accuracy of terrain-aided (TA) navigation algorithms. The problem is designing airframe trajectories in a priori mission planning, so that navigation errors which propagate along with these algorithms are minimal. We analyze the terrain via information theory and the FFT (fast Fourier transform-spatial) algorithm; then we map it using a probabilistic variable, the entropy. The A* optimization algorithm is then applied to produce minimum-error TA-navigation trajectories. Finally, a posteriori superposition of the airframe maneuver constraints renders a suboptimal but implementable solution. The proposed method has been applied to terrains with different information-content levels. Its efficiency, as reflected in an entropy-based cost function, is demonstrated along optimal versus straight-line trajectories, down towards required destinations