Enhanced cooperative navigation by data fusion from IMU, ambiguous terrain navigation, and coarse relative states

Nicolas Merlinge, James Brusey, Nadjim M. Horri, Karim Dahia, Hélène Piet-Lahanier · 2017

GNSS denied IMU correction is a practical challenge in aerospace vehicle navigation. In the context of several vehicles flying in formation, navigation accuracy can be enhanced by communication between the vehicles. In this paper, a collaborative navigation strategy is presented to deal with coarse and ambiguous measurements. An absolute navigation filter provides a first estimate of the navigation solution, while a relative observer rebuilds the neighbors relative states from embedded seekers. A high-level Master Filter fuses information provided by those two low-level filters to enhance the navigation solution. Absolute navigation measurements are terrain elevation data correlated with a Digital Elevation Model map. Since they are highly ambiguous and nonlinear, they are processed by a Box Regularized Particle Filter. The relative measurements under consideration suffer a high level of uncertainty, especially on the relative distance between vehicles. By fusing all uncertain data, a complete and accurate navigation solution is obtained. Numerical results are presented and show an enhancement in navigation performance by exchanging information, in terms of RMS estimation error (63% more accurate in position), estimation confidence (78% more precise in position), and computational load (requires 83% less operations).

Read the paper · More papers on PaperTik