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A Robust Federal Filtering Method Based on Temporal Measured Noise

A federal filtering and noise technology, applied in the field of integrated navigation, to achieve the effect of improving estimation performance, improving performance, and eliminating the influence of sensitivity

Active Publication Date: 2015-08-19
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved in the present invention is the robustness of the federated filter fusion reset mode when the subsystem fails, and a robust federated filtering method based on time variable measurement noise is provided

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  • A Robust Federal Filtering Method Based on Temporal Measured Noise
  • A Robust Federal Filtering Method Based on Temporal Measured Noise
  • A Robust Federal Filtering Method Based on Temporal Measured Noise

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Embodiment Construction

[0024] Below in conjunction with accompanying drawing, the technical scheme of invention is described in detail:

[0025] Such as figure 1 As shown, the principle of the present invention is: starting from the perspective of navigation of the geographic system, according to the system state equation and the linearized measurement equation of each subsystem, a filtering subsystem is formed. The time variable measurement noise is constructed by using the federated filtering information distribution coefficient, and on this basis, the optimal residual detection quantity is selected, and the information distribution coefficient is designed by using the optimal residual detection quantity and chi-square fault detection threshold value, so as to further complete information distribution, Optimal fusion and other steps are used to realize the optimal estimation of the integrated navigation error state quantity. The specific implementation method is as follows:

[0026] (1) Establ...

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Abstract

The invention discloses a robust federated filtering method based on time-variable measurement noise, belonging to the technical field of aircraft combined navigation. The method comprises the following steps of: firstly, establishing a fused reset federated filter of an airborne inertial navigation system and other navigation systems; constructing the time-variable measurement noise of various sub-filters according to a federated filtering information distribution coefficient; defining an optimal residual detection amount in a federated filtering sub-filter residual-chi-square fault detection method; on the basis, designing a dynamic federated filtering information distribution coefficient by virtue of the optimal residual detection amount of each sub-filter and a residual-chi-square fault detection threshold value; and finally, carrying out optimal estimation on an error state of inertial navigation by a robust federated filtering method.

Description

technical field [0001] The invention discloses a robust federated filtering method based on time variable measurement noise, which belongs to the technical field of integrated navigation. Background technique [0002] With the development of aerospace technology, the performance requirements of navigation and guidance systems are getting higher and higher, and integrated navigation systems have become an important navigation system solution. In the field of multi-sensor information fusion for navigation, people pay more and more attention to decentralized filtering technology. The decentralized federated filter proposed by Carlson has attracted the attention of domestic and foreign navigation circles due to its advantages of design flexibility, small amount of calculation, and good fault tolerance. In the basic structure of federated filtering, the non-reset structure has good fault-tolerant performance because each sub-filter performs filtering independently, but because th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/20
Inventor 邵慧熊智华冰方峥杨镜许建新彭惠吴旋柏青青赵慧潘加亮
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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