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).
|Title of host publication||2017 IEEE 56th Annual Conference on Decision and Control (CDC)|
|Number of pages||6|
|ISBN (Electronic)||978-1-5090-2873-3, 978-1-5090-2872-6|
|Publication status||Published - 23 Jan 2018|
|Event||Annual Conference on Decision and Control - Melbourne, Australia|
Duration: 12 Dec 2017 → 15 Dec 2017
Conference number: 56
|Conference||Annual Conference on Decision and Control|
|Period||12/12/17 → 15/12/17|
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- Particle measurements
- Atmospheric measurements
- Measurement uncertainty
- Computer architecture
Merlinge, N. J. A., Brusey, J., Horri, N., Dahia, K., & Piet-Lahanier, H. (2018). Enhanced cooperative navigation by data fusion from IMU, ambiguous terrain navigation, and coarse relative states. In 2017 IEEE 56th Annual Conference on Decision and Control (CDC) (pp. 375-380). IEEE. https://doi.org/10.1109/CDC.2017.8263693