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Unscented卡尔曼滤波具有精度高、稳定性好、实用性强等特点,因此UKF算法逐渐成为处理非线性滤波问题的有效方法和导航系统中数据处理与信息融合技术的研究热点。但是UKF具有计算量大、效率低等缺点,因此限制了UKF在实时导航中的应用。针对这一缺点,本文提出了一种改进的UKF算法,该算法可以减少UT变换中Sigma点的计算数量,从而提高运算效率;推导了改进的算法公式,给出了适合该算法的初始对准非线性模型,并分析了其精度,用实测数据进行了验证。结果显示,改进的UKF算法性能与传统UKF相当,但效率提升了40%左右。
Unscented Kalman filter has the characteristics of high precision, good stability and strong practicability. Therefore, the UKF algorithm has gradually become an effective method to deal with the nonlinear filtering problem and the data processing and information fusion technology in the navigation system. However, UKF has the disadvantages of large computational complexity and low efficiency, which limits the application of UKF in real-time navigation. In view of this shortcomings, an improved UKF algorithm is proposed in this paper. This algorithm can reduce the number of Sigma points in UT transform and improve the computational efficiency. The improved algorithm is deduced, and the initial alignment suitable for the algorithm is given Nonlinear model, and analyzed its accuracy, with the measured data was verified. The results show that the improved UKF algorithm is equivalent to the traditional UKF, but the efficiency is improved by about 40%.