Abstract
Transfer alignment on a moving base under a complex dynamic environment is one of the toughest challenges in a strapdown inertial navigation system (SINS). With the aim of improving rapidity and accuracy, velocity plus attitude matching is applied in the transfer alignment model. Meanwhile, the error compensation model is established to calibrate and compensate the errors of inertial sensors online. To suppress the filtering divergence during the process of transfer alignment, this paper proposes an improved adaptive compensation H∞ filtering method. The cause of filtering divergence has been analyzed carefully and the corresponding adjustment and optimization have been made in the proposed adaptive compensation H∞ filter. In order to balance accuracy and robustness of the transfer alignment system, the robustness factor of the adaptive compensation H∞ filter can be dynamically adjusted according to the complex external environment. The aerial transfer alignment experiments illustrate that the adaptive compensation H∞ filter can effectively improve the transfer alignment accuracy and the pure inertial navigation accuracy under a complex dynamic environment, which verifies the advantage of the proposed method.
Highlights
Initial alignment is vital to a strapdown inertial navigation system (SINS) as its performance is largely decided by the accuracy and rapidity of the alignment process [1,2,3]
The aerial experiment was conducted the airborne position and orientation systemtransfer (POS), alignment experiment was conducted airborne position and orientation system which depends on transfer alignmentfor to the obtain high distributed accuracy motion parameters of slave SINS (S-SINS) by (POS), which depends on transfer alignment to obtain high accuracy motion parameters of
In order to effectively suppress the filtering divergence when conducting transfer alignment, the cause of filtering divergence was analyzed in detail and the mean square error matrix was dynamically modified and optimized to satisfy the convergence condition in the adaptive compensation H∞ filter
Summary
Initial alignment is vital to a strapdown inertial navigation system (SINS) as its performance is largely decided by the accuracy and rapidity of the alignment process [1,2,3]. According to different alignment modes, the initial alignment methods can be categorized into self-alignment, combination alignment, and transfer alignment. Compared with self-alignment and combination alignment, transfer alignment is more rapid, and alignment time can be greatly shortened [2,6,7]. Based on the above advantages, transfer alignment has been widely used in various applications, such as aircraft and ships [1,2,3,4,5,6,7,8,9,10,11]. In the transfer alignment of airborne distributed position and orientation systems (DPOS), Gong et al [9] utilized an unscented Kalman filter (UKF) to estimate the flexural angles and flexural lever arm variations.
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