摘要
高精度的组合导航数据事后融合处理算法是多传感器信息融合处理的重要环节,是对导航系统性能进行评估分析的关键。研究了一种分两步进行的惯性/卫星组合导航信息事后高精度融合算法,在惯性/卫星组合导航卡尔曼滤波算法的基础上,利用最优固定区间平滑滤波算法对惯性/卫星组合导航信息进行再次平滑滤波融合,可以提高组合导航数据事后处理的精度。设计了仿真验证平台,对所提出的融合算法进行了仿真验证。仿真结果表明:基于卡尔曼滤波与固定区间平滑滤波实现的惯性/卫星信息事后融合算法有效、可行,可作为试飞性能评估中确定参考基准的方法。
High precision integrated navigation data off-line processing algorithm was a important part of multi-sensor data fusion technology. It was the key component of navigation system performance analysis and evaluation. A two-step high precision INS/GPS integrated navigation off-line fusion algorithm has been investigated in this paper. Based on Kalman filter algorithm of INS/GPS integrated navigation information, RTS fixed-interval smoothing algorithm was used to further smooth and fusion of INS/GPS integrated navigation information which could improve the accuracy of navigation. A simulation platform has been designed in this paper to test the fusion algorithm. The simulation results show that INS/GPS data off-line fusion algorithm based on Kalman filter and RTS fixed-interval smoothing was effective and feasible. It could used as a basic method to serve as the reference in performance evaluations of flight-test.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2010年第A01期75-78,共4页
Journal of System Simulation
基金
国家自然科学基金(60804058)
航空科学基金(20080852012)
