Kalman filtering of the miniaturized inertial sensors' data for inertial navigation

@article{Raluca2011KalmanFO,
  title={Kalman filtering of the miniaturized inertial sensors' data for inertial navigation},
  author={Edu Ioana Raluca and Grigorie Teodor Lucian and Cepisca Costin},
  journal={2011 7TH INTERNATIONAL SYMPOSIUM ON ADVANCED TOPICS IN ELECTRICAL ENGINEERING (ATEE)},
  year={2011},
  pages={1-6}
}
The paper presents an adaptive algorithm for the statistical filtering of the miniaturized inertial sensors noise by building redundant networks of sensors in the same navigator, followed by each sensors network data fusion. The proposed method offers the advantage of having a redundant inertial navigator in terms of the detection unit. The sensors are disposed in linear redundant arrays. The novelty brought by the proposed algorithm consists in its adaptivity provided by the permanent update… CONTINUE READING
1 Citations
22 References
Similar Papers

Citations

Publications citing this paper.

References

Publications referenced by this paper.
Showing 1-10 of 22 references

INS/GPS Technology Trends”, NATO RTO Lecture Series, RTO-EN-SET-116, Low-Cost Navigation Sensors and Integration

  • G. Schmidt
  • 2010
Highly Influential
8 Excerpts

Integration of Skew-Redundant MEMS-IMU with GPS for Improved Navigation Performance

  • S. Guerrier
  • Master Project, Geodetic Engineering Laboratory…
  • 2008
Highly Influential
4 Excerpts

Applied Mathematics in Integrated Navigation Systems

  • R. Rogers
  • Third Edition, Published by AIAA
  • 2007
Highly Influential
4 Excerpts

Multi-sensor Data Fusion Architecture Based on Adaptive Kalman Filters and Fuzzy Logic Performance Assessment

  • P. Escamilla, N. Mort
  • The International Conference on Information…
  • 2002
Highly Influential
6 Excerpts

836-2009

  • IEEE Std
  • IEEE Recommended Practice for Precision…
  • 2009
1 Excerpt

Microelectromechnical Systems Inertial Measurement Unit Error Modelling and Error Analysis for Low-cost Strapdown Inertial Navigation System

  • R. Ramalingam, G. Anitha, J. Shanmugam
  • Defence Science Journal,
  • 2009
1 Excerpt

Similar Papers

Loading similar papers…