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- W2352457413 abstract "The observability of stationary alignment for PINS was analyzed systemically, and condition number of observable matrix was adopted to compute quantificationally the observability of stationary alignment for PINS. Three unobservable states with the least condition mumber were chosen in this condition, then both adaptive Kalman filter and general Kalman filter was employed to compare for simplified model. Simulation results showed the former was faster than later. Furthermore, a alignment method based on Elman neural network was proposed." @default.
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- W2352457413 date "2002-06-30" @default.
- W2352457413 modified "2023-09-25" @default.
- W2352457413 title "Study on Theory and Arithmetic of Stationary Alignment for PINS" @default.
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