A Time Series Method for Anti-aircraft Missile IMU State Prediction
Inertial measurement unit(IMU)is an important component of anti-aircraft missiles and its state is mainly attained from periodical manual testing,which is not effcient.Aiming at reducing the dependence on periodical testing,time series prediction methods are developed to predict part of the states of IMU by pro-cessing existing data.Under the consideration of the small sample size,overlapping segmentation averaging is used for data processing to reduce feature dimension and training difficulty.Long short term memory net-work(LSTM)is used for subsequent time series prediction.The effect of the proposed model is validated through practical data,which attains a high prediction accuracy while taking little time consumption.
Anti-aircraft missileInertial measurement unitTime seriesOverlapped segmentation avera-gingLong short term memory
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