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 of designing airframe trajectories in a priori mission planning, such that navigation errors which propagate along with these algorithms be minimal. We analyze the terrain via information theory and the fast Fourier transform algorithm; we then map it employing a probabilistic variable, the entropy. A derivative of the dynamic programing 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 linear trajectories, flown towards required destinations.<>