计算机工程与应用2019，Vol.55Issue(18)：229-235,7.DOI:10.3778/j.issn.1002-8331.1901-0357
自适应混合阶SSRCKF及其在组合导航中的应用
Adaptive Mixed-Degree Spherical Simplex-Radial Cubature Kalman Filter and Its Application in Integrated Navigation System
摘要
Abstract
The traditional Cubature Kalman Filter(CKF)has problems of low accuracy and even divergence when deal-ing with highly nonlinear systems, and High-Degree Cubature Kalman Filter(HCKF)increases the accuracy while greatly increasing the computational complexity, at the same time, negative weight affects the stability of the algorithm in high-dimensional systems. In view of the above problems, this paper proposes an Adaptive Mixed-degree Spherical Simplex-Radial Cubature Kalman Filter(AMSSRCKF), which adopts Mixed-degree Spherical Simplex-Radia(l MSSR)sampling to obtain higher accuracy than CKF, and combines with the strong tracking filter algorithm of multiple fading factors to improve the robustness of the algorithm. The algorithm is applied to the simulation of the integrated navigation system, the results show that AMSSRCKF can effectively suppress the impact of the sudden change of the system state and improve the positioning accuracy and robustness of the integrated navigation system.关键词
容积卡尔曼滤波/混合阶/球面最简相径/自适应/多重渐消因子/组合导航Key words
Cubature Kalman Filter(CKF)/mix-degree/spherical simplex-radial/adaptive/suboptimal multiple fading factor/integrated navigation分类
信息技术与安全科学引用本文复制引用
黄国荣,许明琪,卢航,魏翔,彭志颖..自适应混合阶SSRCKF及其在组合导航中的应用[J].计算机工程与应用,2019,55(18):229-235,7.基金项目
国家自然科学基金面上项目(No.61573373) （No.61573373）
陕西省自然科学基金(No.2017JQ6034). （No.2017JQ6034）
