重力辅助导航联邦滤波算法仿真研究  

Research and Simulation of Federated Filter Algorithm in Gravity Aided Navigation System

作　　者：夏冰[1] 王浩[2] 

机构地区：[1]常熟理工学院,江苏常熟215500 [2]空军航空大学,吉林长春130033

出　　处：《计算机仿真》2010年第11期1-4,13,共5页Computer Simulation

摘　　要：研究舰船综合导航问题。为了进一步适应现代导航自主、精确、隐蔽、抗干扰的要求,重力辅助导航KALMAN滤波算法计算量大、容错性差的缺点,本文对重力辅助导航系统进行了深入的研究。通过对重力辅助导航系统原理和联邦滤波算法,对重力子系统各部分进行了系统建模,并在确定了重力子系统量测矩阵和量测值的基础上,构建了重力辅助导航联邦滤波算法。通过对重力辅助导航联邦滤波算法和重力辅助导航KALMAN滤波算法的仿真试验比较,证明了算法具有精度高、稳定性好,容错性好、算法灵活等特点,能较好的满足重力辅助导航的实际需要,可以为设计提供依据。In order to further adapt to the requirements of modern navigation technology which need autonomy,accuracy,hidden,anti-interference,and to avoid the shortcomings of the KALMAN filter algorithm of the gravity aided navigation,the paper studied the gravity aided navigation system deeply.The paper described the principles of gravity aided navigation and the federated filter theory,and modeled the gravity subsystem.On the basis of the measurement matrix and the measured values of gravity subsystem,the federated filter algorithm of the gravity aided navigation system is praised and the simulation of the KALMAN filtering algorithm and the federated filter algorithm is completed.Simulation results show that due to the secondary structure and information distribution factor,the gravity aided navigation federated filter algorithm has high accuracy,good stability,good fault tolerance and flexibility.The federated filter algorithm of the gravity aided navigation system will meet the actual needs of gravity aided navigation better.

关 键 词：重力辅助导航 联邦滤波 多传感器信息融合 

分 类 号：TP393.6[自动化与计算机技术—计算机应用技术] V249.31[自动化与计算机技术—计算机科学与技术]