基于扩展H∞滤波的SINS/AMM机载组合导航技术

系统工程与电子技术

基于扩展H∞滤波的SINS/AMM机载组合导航技术

申杰亮, 王宇, 朱欣华, 苏岩

(南京理工大学机械工程学院, 江苏南京 210094)

出版日期:2016-11-29 发布日期:2010-01-03
基金资助:
aircraft motion model (AMM); strapdown inertial navigation system (SINS); uncertainty of the system and the noise; extended H∞ filter

Airborne integrated navigation technology of SINS/AMM based on extended H∞ filter

SHEN Jieliang, WANG Yu, ZHU Xinhua, SU Yan

(School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China)

Online:2016-11-29 Published:2010-01-03

摘要/Abstract

摘要：

研究了飞机运动模型(aircraft motion model, AMM)与中、低精度捷联惯导系统(strapdown inertial navigation system, SINS)相融合的组合导航技术。针对由于气动系数的不准确所导致的系统方程的不确定性以及观测方程和噪声的不确定性问题,提出采用基于极小极大准则的扩展H∞滤波(extended H∞ filter, EHF)方法用于组合导航系统的数据融合。以某小型固定翼无人机为研究对象,分别从时域、频域的角度进行仿真实验的验证与分析。实验结果表明,在SINS/AMM组合导航过程中,与扩展卡尔曼滤波(extended Kalman filter, EKF)相比,EHF具有更好的鲁棒性,并且可以提高35%左右的导航精度。

Abstract:

The integrated navigation technology of aircraft motion model (AMM) with medium and low accuracy strapdown inertial navigation system (SINS) is studied. Considering the uncertainty of the system equation caused by inaccurate aerodynamic coefficient and the uncertainty of the observation equation as well as the noise, the extended H∞ filter (EHF) algorithm is proposed, which is abided by the minmax principle. The simulation, which is tested on a small fixedwing UAV in both time and frequency domain, shows that for the SINS/AMM integrated navigation system, EHF performs better than the extended Kalman filter (EKF) in robustness and EHF brings approximately a 35% increasing in precision.

申杰亮, 王宇, 朱欣华, 苏岩. 基于扩展H∞滤波的SINS/AMM机载组合导航技术[J]. 系统工程与电子技术.

SHEN Jieliang, WANG Yu, ZHU Xinhua, SU Yan. Airborne integrated navigation technology of SINS/AMM based on extended H∞ filter[J]. Systems Engineering and Electronics.