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- W2374921103 abstract "Aiming at improving the instantaneity of detecting slowly growing errors with the autonomous integrity monitored extrapolation(AIME) method in the INS/GNSS tightly-coupled navigation system,this paper presented a new method based on least squares support vector machine(LS-SVM) combined with AIME.The method replaces the innovation of Kalman filter by the forecasted innovation of the Least squares support vector machine regression,which is used for the test statistics.The new method presented in this paper could reduce the influence of fault tracking caused by Kalman filter,so the real-time ability of slowly growing errors detection can be improved.Simulation results show that,the delay time of slowly growing errors detection is reduced by 1.3 times.The method based on Least squares support vector machine has better detection ability than traditional autonomous integrity monitored extrapolation method when detecting slowly growing errors." @default.
- W2374921103 created "2016-06-24" @default.
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- W2374921103 date "2012-01-01" @default.
- W2374921103 modified "2023-09-28" @default.
- W2374921103 title "Approach for detection of slowly growing errors in INS/GNSS tightly-coupled system based on LS-SVM" @default.
- W2374921103 hasPublicationYear "2012" @default.
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