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将可以估计系统参数、噪声统计特性和修正滤波增益的自适应估计方法引入到CDKF算法中,并将其应用到SINS大方位失准角初始对准中,实现SINS大方位失准角初始对准,解决了噪声特性不准确的非线性问题,避免了线性化误差对滤波精度的影响,克服了噪声统计特性不准确的局限性,进一步提高了导航精度.采用自适应中心差分卡尔曼滤波(ACDKF)进行初始对准,提高了CDKF算法的收敛性和系统的稳定性.仿真结果表明:ACDKF能够克服噪声统计模型不准确对滤波结果的影响,对失准角的估计精度优于CDKF,进一步提高了系统的精度和可靠性.
The adaptive estimation method which can estimate the system parameters, the statistical properties of noise and the correction filtering gain is introduced into the CDKF algorithm and applied to the initial alignment of the large azimuth misalignment angle of SINS to realize the initial alignment of the large azimuth misalignment angle of SINS , Which solves the nonlinear problem of inaccurate noise characteristics and avoids the influence of linearization error on the filtering accuracy and overcomes the inaccurate limitations of the statistical characteristics of noise to further improve the navigation accuracy.Adaptive center differential Kalman filter (ACDKF ) To improve the convergence of CDKF algorithm and the stability of the system.The simulation results show that ACDKF can overcome the impact of inaccurate noise statistical model on the filtering results and the estimation accuracy of misalignment angle is better than that of CDKF The system accuracy and reliability.