摘要
针对稀疏高斯厄米特积分滤波(SGHQF)中积分点利用效率不高的问题,提出一种基于状态分量可观测度分析的自适应各向异性SGHQF(AASGHQF).给出了利用状态分量可观测度和各向异性权重向量来控制各维通道积分精度等级的方法,进而对各变量通道的积分点数目进行合理分配.以CNS/SAR/SINS非线性组合导航为应用背景,对UKF、SGHQF和AASGHQF进行了仿真对比分析.仿真结果表明,AASGHQF与SGHQF的滤波估计精度相当,均高于UKF;AASGHQF比SGHQF需要更少的积分点,提高了计算效率.
In view of the problem that the utilization efficiency of points is low in sparse Gauss-Hermite quadrature filter（SGHQF）, an adaptive anisotropic SGHQF（AASGHQF） based on observable degree analysis of state parameters is proposed. A mechanism for controlling accuracy level of each dimension is presented by utilizing the state parameters’ observable degree and the anisotropic importance vector, which can distribute the quadrature points nonuniformly and reasonably. The AASGHQF is applied to the CNS/SAR/SINS nonlinear integrated navigation system and compared with the UKF and the SGHQF. Simulation results show that the AASGHQF is more accurate than the UKF and has very close performance with the SGHQF. In addition, the AASGHQ points are decreased substantially and the computation efficiency is higher compared with the SGHQF.
出处
《控制与决策》
EI
CSCD
北大核心
2015年第7期1195-1200,共6页
Control and Decision
基金
武器装备预研项目(103010205)
国家863计划项目(2013AA7021004)
