Abstract
Precision-guided projectiles, which can significantly improve the accuracy and efficiency of fire strikes, are on the rise in current military engagements. The accurate measurement of roll angular rate is critical to guide a gun-launched projectile. However, Micro-Electro-Mechanical System (MEMS) gyroscope with low cost and large range cannot meet the requirement of high precision roll angular rate measurement due to the limitation by the current technology level. Aiming at the problem, the optimization-based angular rate estimation (OBARS) method specific for projectiles is proposed in this study. First, the output angular rate model of redundant gyroscope system based on the autoregressive integrated moving average (ARIMA) model is established, and then the conventional random error model is improved with the ARIMA model. After that, a Sage-Husa Adaptive Kalman Filter (SHAKF) algorithm that can suppress the time-varying process and measurement noise under the flight condition of the high dynamic of the projectile is designed for the fusion of dynamic data. Finally, simulations and experiments have been carried out to validate the performance of the method. The results demonstrate the proposed method can effectively improve the angular rate accuracy more than the related traditional methods for high spinning projectiles.
Highlights
As a means of improving the accuracy and efficiency of firepower strike, precision-guided munitions has attracted the attention of the Army [1,2,3]
The output angular rate model of redundant gyroscope system based on the autoregressive integrated moving average (ARIMA) model is established, and the conventional random error model is improved with the ARIMA model; (2) a Sage-Husa Adaptive Kalman Filter (SHAKF) algorithm that can suppress the time-varying process and measurement noise under the flight condition of the high dynamic of the projectile is designed for the fusion of dynamic data
The optimization-based angular rate estimation (OBARS) method for the high-spin projectile is proposed. This method falls into two portions—(1) improved random error model for high spinning projectiles based on the ARIMA model is established; (2) a Sage-Husa Adaptive Kalman Filter (SHAKF) algorithm that can suppress the time-varying process and measurement noise under the flight condition of the high dynamic of the projectile is designed for the fusion of dynamic data
Summary
As a means of improving the accuracy and efficiency of firepower strike, precision-guided munitions has attracted the attention of the Army [1,2,3]. When the projectile flies at high speed, the bias of the selected large-range gyroscopes will be accumulated rapidly over time and leads to large attitude errors [19] It is a challenging task for MEMS gyroscopes with the traditional configuration scheme to measure the angular rate of the high-spin projectile accurately. The main contributions of our research are twofold—(1) the gyroscopes geometry configuration of the inertial measurement unit (IMU) is designed according to the high dynamic characteristics of projectiles In this configuration method, the output angular rate model of redundant gyroscope system based on the autoregressive integrated moving average (ARIMA) model is established, and the conventional random error model is improved with the ARIMA model; (2) a Sage-Husa Adaptive Kalman Filter (SHAKF) algorithm that can suppress the time-varying process and measurement noise under the flight condition of the high dynamic of the projectile is designed for the fusion of dynamic data.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
