Abstract
The uncertainty of navigation system model will lead to model identification errors. A DR/INS redundant integrated navigation system is proposed basing on multi-model adaptive estimation method to merge models constructed in different considerations and view angles, and formed a practical adaptive estimation algorithm using autoregressive model and hypothesis tests. The redundant integrated navigation system, which acquires information primarily from DR and INS, and TAN information as secondary sources, calculates the fusion information by federal Kalman filter. Simulations are performed and the results show that proposed system can overcome the uncertainty of system modeling, and high precision, fault-tolerance, anti- interference and stability can be obtained.
This paper is funded by the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation.
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Yuan, K., Yuan, G., Zhang, H. (2011). DR/INS Redundant Integrated Navigation System Based on Multi-model Adaptive Estimation Method. In: Zhang, J. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23223-7_39
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DOI: https://doi.org/10.1007/978-3-642-23223-7_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23222-0
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