IEEE Xplore Abstract – Modified 2-sample rotation vector algorithm and its performance analysis

The golden section method is utilized to improve attitude updating algorithm. The performance of the modified 2-sample rotation vector algorithm under coning motion is validated. By contrast with algorithms proposed by Jordan, Miller, Lee, and Savage, under different coning frequence and coning angle, the modified algorithm's precision turns out to be about 1 magnitude higher than the traditional algorithms'. Moreover, the performance of modified algorithm under different measurement error is testified. The results show that, the modified algorithm is visably better than traditional algorithms, when the measurement error is not so large. Therefore, the modified 2 sample rotation vector algorithm is suitable for high-precision strapdown inertial navigation system. subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses. The golden section method is utilized to improve attitude updating algorithm. The performance of the modified 2-sample rotation vector algorithm under coning motion is validated. By contrast with algorithms proposed by Jordan, Miller, Lee, and Savage, under different coning frequence and coning angle, the modified algorithm's precision turns out to be about 1 magnitude higher than the traditional algorithms'. Moreover, the performance of modified algorithm under different measurement error is testified. The results show that, the modified algorithm is visably better than traditional algorithms, when the measurement error is not so large. Therefore, the modified 2 sample rotation vector algorithm is suitable for high-precision strapdown inertial navigation system. Source.


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Last Modified: April 18, 2016 @ 9:06 pm