Abstract
As the laser gyroscopes and accelerometers in a ring laser gyroscope Strapdown Inertial Navigation System(SINS) generate high noises by the dither motion of a base and a low pass fitering and a wavelet method can not suppress the noises in real time effectively, this paper presents a prefiltering method combining a low pass filtering and a Kalman filtering based on a hidden Markov model. Firstly, the output of a sensor is filtered by the lowpass filter, then it is filtered by the steady-state Kalman filter based on the hidden Markov model. By this way, the large sensor noise brought by the dither motion of the base can be lowed down to a very low level. Experiment results show that this prefiltering method can work efficiently with a low computational complexity. When the vehicle engine is on, the standard variances of the ring laser gyroscope and accelerometer are suppressed from 300°/h to 1°/h and from 11 mg to 40 μg, respectively. It is concluded that the proposed prefiltering can help SINS accomplish the initial alignment on a rocking base.
Original language | English |
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Pages (from-to) | 2520-2527 |
Number of pages | 8 |
Journal | Guangxue Jingmi Gongcheng/Optics and Precision Engineering |
Volume | 17 |
Issue number | 10 |
Publication status | Published - Oct 2009 |
Keywords
- Hidden Markov model
- Initial alignment
- Kalman filter
- Ring laser gyroscope
- Strapdown inertial navigation system