An improved multi-source information fusion method for IMU compensation of missile

被引:2
|
作者
Shi, Chunfeng [1 ,2 ]
Chen, Xiyuan [1 ,2 ]
Wang, Junwei [1 ,2 ]
机构
[1] Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Peoples R China
[2] Southeast Univ, Key Lab Microinertial Instrument & Adv Nav Technol, Minist Educ, Nanjing 210096, Peoples R China
关键词
Multi-source information fusion; Kinematic constraint; SINS; CNS integrated navigation systems; Cubature Kalman filter; Maximum a posteriori; INTEGRATED NAVIGATION METHOD; SATELLITE NAVIGATION; KALMAN FILTER; ATMOSPHERIC REFRACTION; MODEL; SCHEME;
D O I
10.1186/s13634-023-01047-6
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The conventional SINS/CNS integrated navigation system equipped on ballistic missiles is typically equipped with attitude measurement, which can only estimate the gyro drift and has no effect on accelerometer bias. To address the issue, an improved multi-source information fusion method containing a new nonlinear framework called SINS/RKCNS with the indirect horizon reference and kinematic constraint is proposed, and a MAP-based modified iterated CKF is involved to increase positioning accuracy and system robustness. Furthermore, to reduce the influence of correlated noise, state augmentation is employed in the iterative process. Eventually, experiments are conducted, and the results confirm the effectiveness of the proposed approach.
引用
收藏
页数:18
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