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Lie group heavy-tail interference noise dynamic aircraft attitude estimation method based on variational iterative Kalman filtering

A Kalman filter and attitude estimation technology, which is applied in the field of attitude estimation of aerospace systems to achieve the effect of improving robustness

Pending Publication Date: 2021-11-19
BEWIS TECH
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Problems solved by technology

The method of the present invention improves the deficiency of the invariant Kalman filter, and solves the attitude estimation problem of the aircraft attitude model under heavy tail noise interference in aerospace engineering

Method used

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  • Lie group heavy-tail interference noise dynamic aircraft attitude estimation method based on variational iterative Kalman filtering
  • Lie group heavy-tail interference noise dynamic aircraft attitude estimation method based on variational iterative Kalman filtering
  • Lie group heavy-tail interference noise dynamic aircraft attitude estimation method based on variational iterative Kalman filtering

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Embodiment

[0150] Adopt a kind of Lie group heavy-tail interference noise dynamic aircraft attitude estimation method based on variational iterative Kalman filtering proposed by the present invention, given system parameter and initial value:

[0151] Σ 0|0 =0.5236 2 I 3×3 ,Σ w =0.01745 2 I 3×3 ,b'=[1,0,0] T ,b”=[0,1,0] T ,Σ v' =0.0873 2 I 3×3 ,Σ v” =0.0873 2 I 3×3 .

[0152] The filtering parameter is set to λ k =k+4,a k =2,b k =6,N=10.

[0153] The real attitude trajectory is 5000 seconds long, and the heavy-tailed process noise is generated together with heavy-tailed outliers:

[0154]

[0155] And to compare the theoretical performance, the root mean square error and average root mean square error after 5000s filtering are calculated using the error variable in the Lie algebra of 5000 random runs:

[0156]

[0157]

[0158] In this example, the two conditions of α=5, β=10 and α=20, β=10 are respectively used to simulate and compare the performance of differ...

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Abstract

The invention provides a Lie group heavy-tail interference noise dynamic aircraft attitude estimation method based on variational iterative Kalman filtering. The method comprises the following steps: 1 establishing an attitude dynamic model of a system on a Lie group special orthogonal group; 2 mapping the Lie group dynamic model of the system to an Euclidean geometric space; 3 defining a prior distribution function of each parameter in the heavy-tail noise based on the observation data; 4 carrying out variational Bayesian approximation on the probability density function of the heavy-tail noise; 5 solving distribution parameters of the system state and the probability density function through fixed-point iteration; and 6 substituting each parameter in the step 5 into the step 4 for calculation to obtain a posterior probability density function approximate value of the noise. According to the method, the Lie group attitude estimation problem of the system under the interference of the heavy-tail noise is well solved.

Description

technical field [0001] The invention belongs to the field of attitude estimation of aerospace systems, and relates to a dynamic aircraft attitude estimation method based on variational iterative Kalman filtering based on Lie group heavy-tail interference noise. Background technique [0002] In recent years, with the rapid development of aerospace system tasks, emerging new application scenarios and load tasks have put forward higher requirements for the dynamic estimation accuracy, real-time performance and adaptive ability of the attitude determination method of the aircraft body. Kalman filtering is an attitude estimation method widely used in the fields of aerospace and robotics. In the past ten years, researchers have proposed an invariant Kalman filtering method based on the symmetric and invariant characteristics of Lie group in aircraft dynamics and kinematics. Using Lie group Lie algebraic transformation simplifies the system model to improve the performance of aircr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20G06F17/15G06F17/16
CPCG01C21/20G06F17/15G06F17/16
Inventor 王蛟龙段一铭韩楚楚曲金慧
Owner BEWIS TECH
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