摘要
针对平方根容积卡尔曼滤波器(SRCKF)在定位系统船舶模型不确定时存在滤波精度下降甚至发散的问题,提出了一种具有强跟踪性能的SRCKF算法。基于强跟踪滤波器(STF)的理论框架,采用三阶球面径向容积规则代替STF中的雅克比矩阵计算,结合渐消因子的等价表述,构建强跟踪SRCKF。基于滤波收敛判据和渐消记忆滤波思想,分析了强跟踪SRCKF的收敛性。强跟踪SRCKF兼具STF鲁棒性强、SRCKF滤波精度高和实现简单的优点,有效克服了STF的理论局限性及SRCKF在系统模型不确定时滤波性能下降的缺点。利用船舶陆上仿真系统进行试验,证明了强跟踪SRCKF的有效性。
Aiming at the problem that the filtering accuracy of square-root cubature Kalman filter （SRCKF） de- grades, even falls into divergence when vessel dynamic positioning system model has uncertainty, a SRCKF algorithm with strong tracking behavior is proposed. Based on the theoretical framework of strong tracking filter （ STF）, the third-order spherical-radial cubature rule is adopted to replace calculating the nonlinear function Jacobian matrix;and combining the equivalent description of the fading factor, the strong tracking SRCKF is constructed. The convergence of the proposed strong tracking SRCKF is analyzed based on the filtering convergence criterion and fading memory fil- ter theory. The proposed strong tracking SRCKF combines the strong robustness of STF with the high accuracy and easy implementation of SRCKF. It effectively overcomes the theoretical limitation of STF and filtering performance degradation of SRCKF while the system model is uncertain. The vessel land simulation test system was used to carry out experiments, and the simulation results verify the effectiveness of the strong tracking SRCKF.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2013年第6期1266-1272,共7页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(NSFC60775060)资助项目
