Abstract
A leveling loop for initialization of an inertial navigation system mounted on a moving platform is considered. The leveling loop is designed by exact modeling of the sensors errors as state-multiplicative noise processes. Such modeling allows application of a State Multiplicative Kalman Filter and is shown to outperform the standard Kalman filter based on ad-hoc analysis ignoring the state-multiplicative noise. The design considerations include both estimation error covariance minimization and error decay rate. Both design goals are integrated into a single design, using a trade-off parameter. A couple of numerical examples illustrate the benefits of the State Multiplicative Kalman Filter with and without the decay rate requirement. The first example which deals with a leveling loop focuses on the decay rate parameter effect, whereas the second example deals with a more standard inertial navigation and demonstrates the benefits of incorporating the state-multiplicative noise effect, rather than neglecting it.
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Yaesh, I., Stoica, AM. (2015). Leveling Loop Design and State Multiplicative Noise Kalman Filtering. In: Choukroun, D., Oshman, Y., Thienel, J., Idan, M. (eds) Advances in Estimation, Navigation, and Spacecraft Control. ENCS 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44785-7_14
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DOI: https://doi.org/10.1007/978-3-662-44785-7_14
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