Adaptive transfer alignment method based on the observability analysis for airborne pod strapdown inertial navigation system (vol 12, 946, 2022)

被引:0
|
作者
Chen, Weina
Yang, Zhong
Gu, Shanshan
Wang, Yizhi
Tang, Yujuan
机构
[1] College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing
基金
中国国家自然科学基金;
关键词
D O I
10.1038/s41598-022-09223-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
For the airborne pod strapdown inertial navigation system, it is necessary to use the host aircraft's inertial navigation system for the transfer alignment as quickly and accurately as possible in the flight process of the aircraft. The purpose of this paper is to propose an adaptive transfer alignment method based on the observability analysis for the strapdown inertial navigation system, which is able to meet the practical need of maintaining the navigation accuracy of the airborne pod. The observability of each state variable is obtained by observability analysis of system state variables. According to the weight of the observability, a transfer alignment filter algorithm based on adaptive adjustment factor is constructed to reduce the influence of weak observability state variables on the whole filter, which can improve the estimation accuracy of transfer alignment. Simulations and experiment tests of the airborne pod and the master strapdown inertial navigation systems show that the adaptive transfer alignment method based on the observability analysis can overcome the shortage of the weak observability state variables, so as to improve the alignment and the navigation performance in practical applications, thus improving the adaptability of the airborne pod. © 2022, The Author(s).
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页数:1
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