摘要
针对组合导航系统中多传感器输出不同步的问题,提出一种基于矢量信息分配的异步联邦滤波算法的INS/GNSS/CNS组合方案,根据各子系统的工作特性,分析并设计了基于INS/GNSS位置组合以及INS/CNS姿态组合的联邦滤波模型,并采用矢量形式的信息分配方法提高了滤波器的精度.针对量测异步问题,设计了时间与量测更新分离的异步非等间隔算法.系统仿真实验表明,该算法可以有效地实现对INS、GNSS、CNS的多信息的异步融合,与常规异步滤波方法相比较,组合系统的滤波精度有明显提高,具有重要的实际应用价值.
To solve the problem of asynchronism of sensors′ outputs in integrated navigation systems a novel INS/GNSS/CNS integrated federated filtering algorithm based on dynamic vector formed information distribution is proposed. Based on the operating character of the subsystems, an INS/GNSS position integrated model and an INS/CNS velocity integrated model are analysed and designed as the federated filtering model. And the filtering accuracy is improved by using the dynamic vector formed information distribution algorithm. To solve the problem of asynchronism in measurement, an asynchronous incoordinate interval algorithm is proposed, and the filtering period is divided into time update period and measurement update period. Simulation results indicate that this algorithm can effectively implement the asynchronism fusion of the information from INS, GNSS and CNS. Comparing with the general asynchronism federated filter, the proposed algorithm has significant improvement in estimation accuracy and important application value.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2015年第4期99-103,共5页
Journal of Harbin Institute of Technology
基金
国家自然科学基金(61102107
61374208)
