Centralized fault-tolerant Kalman filter for integrated navigation

被引：0
|
作者：
Zhao L. [1 ]
Kang Y. [1 ]
Cheng J. [1 ]
Wu M. [1 ]
机构：
[1] College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin
来源：
Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2021年 / 42卷 / 06期
关键词：
Adaptive factor; Adaptive filter; Centralized filter; Equivalent weight function; Fault-tolerant filter; Integrated navigation; Quality evaluation; Ramp errors;
D O I：
10.11990/jheu.201912061
中图分类号：
学科分类号：
摘要：
The traditional centralized Kalman filter employed by integrated navigation systems with multi-source information is unable to limit the ramp measurement error. In this paper, a fault-tolerant Kalman filter (FTKF), which takes the prior probability distribution into account, is proposed based on the maximum likelihood estimation to restrain step errors, impulse errors, and ramp errors. The quality evaluation method and function are designed to evaluate the measurement availability and the equivalent weight function and adaptive factor are constructed based on the quality evaluation information. By adjusting the weight of measurement information, the influence of gross measurement error including slope noise on the filtering accuracy and reliability is limited and fault-tolerant filtering is realized. The algorithm is applied to the multi-sensor integrated navigation system for simulation and verification. The simulation results show that, when employed by an integrated navigation system, the proposed FTKF can limit the measurement outliers, including step errors, impulse errors, and ramp errors, and improve the filter accuracy and reliability. Copyright ©2021 Journal of Harbin Engineering University.
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页码：845 / 850
页数：5
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