摘要
为了提高捷联惯导(SINS)/天文导航(CNS)/合成孔径雷达(SAR)组合导航系统的定位精度,在吸收模型预测滤波和抗差自适应滤波算法优点的基础上,提出了一种新的抗差自适应模型预测滤波算法。该算法首先利用模型预测滤波估计出系统模型误差,并对其进行实时修正,以抑制系统模型误差对导航解算精度的影响;然后利用抗差自适应因子控制观测异常,抑制观测噪声对导航解算精度的影响。将提出的算法应用于SINS/CNS/SAR组合导航系统进行仿真验证,并与抗差自适应滤波进行比较,结果表明,提出的算法得到的姿态误差、速度误差和位置误差分别在[0.2,0.2]、[0.3m/s,0.3m/s]和[6 m,6 m]以内,滤波性能明显优于抗差自适应滤波算法,说明该算法能有效抑制系统模型误差及观测异常对导航解的影响,提高组合导航的解算精度。
In order to improve the navigation positioning accuracy of the strapdown inertial navigation system（SINS）/celestial navigation system（CNS）/synthetic aperture radar（SAR） integrated navigation systems,this paper presents a robust adaptive model predictive filtering algorithm based on the research of model predictive filtering and robust adaptive filtering.First,the algorithm estimates the model error in real-time to correct the system model by model predictive filtering to resist the effects of model errors on solution accuracy of navigation.Then,the algorithm controls the influences of abnormal observation on solution accuracy of navigation by the robust adaptive factor.The proposed algorithm is applied to SINS/CNS/SAR integrated navigation system and compared with the robust adaptive filter.Simulation results demonstrate that the attitude angle error,velocity error and position error obtained by the robust adaptive model predictive filtering are within,and respectively;and the filtering performance is significantly superior to that of the robust adaptive filter.The results show that the proposed filtering method can effectively inhibit the impacts of model errors and abnormal observation on the navigation solution,thus improving the precision of navigation system.
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2011年第6期701-705,共5页
Journal of Chinese Inertial Technology
基金
863计划项目(NADH0004)
陕西省自然科学基金(NBYU0004)
