Time series analysis-based variable proportion self-adaptive federal filtering method

A technology of time series analysis and federated filtering, applied in navigation computing tools and other directions, can solve problems such as the problem that the weight distribution of navigation sensor information cannot be accurately reflected

Inactive Publication Date: 2011-11-23
HARBIN ENG UNIV
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Problems solved by technology

[0004] Aiming at the problem that the information distribution proportion in the existing federated filtering method cannot accurately reflect the distribution of navigation sensor information weights with the determination of the structure, the present invention provides a variable ratio adaptiv

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  • Time series analysis-based variable proportion self-adaptive federal filtering method

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Embodiment Construction

[0043] The present invention will be further described in detail with reference to the accompanying drawings and embodiments.

[0044] The multi-sensor integrated navigation system applied in the embodiment of the present invention is an underwater multi-sensor integrated navigation system. ESGM), Global Positioning System (Global Positioning System, GPS for short) and Doppler Velocity Log (DVL for short).

[0045] INS is composed of a gyroscope and an accelerometer. It is an autonomous navigation system that does not rely on external information. It can provide various navigation parameters including speed, position and attitude. It has the advantages of anti-interference and all-weather, so it is suitable for underwater diving. base navigation system for the device. The accuracy of INS mainly depends on the inertial device, and the navigation accuracy error will increase with the accumulation of time, so it is necessary to consider the error stability of its long-term voyag...

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Abstract

The invention discloses a time series analysis-based variable proportion self-adaptive federal filtering method, and the method is utilized for underwater multi-sensor integrated navigation systems. The time series analysis-based variable proportion self-adaptive federal filtering method is characterized by establishing system state equations and measurement equations according to error equations belonging to all navigation sensor systems, carrying out discretization processing of the established equations, creating discrete state-space models respectively corresponding to the all navigation sensor systems, acquiring information weight of the navigation sensor systems through an autoregressive model according to historical data of the navigation sensor systems, acquiring an information distribution ratio according to the obtained information weight and a law of information conservation, realizing global optimal estimates, and resetting a filtering value and an evaluated error covariance matrix by the global optimal estimates. The time series analysis-based variable proportion self-adaptive federal filtering method improves system navigation precision, system stability and fault tolerance, and can satisfy requirements which belong to underwater navigation devices and comprise high precision and high reliability requirements.

Description

technical field [0001] The invention belongs to the technical field of multi-sensor integrated navigation systems, and relates to a filtering method for a multi-sensor integrated navigation system, in particular to a variable-scale adaptive federated filtering method based on time series analysis. Background technique [0002] With the advancement of navigation technology, the performance and application range of any single navigation device show obvious limitations, and cannot meet the increasing accuracy requirements of the carrier, nor can it adapt to complex application environments, and cannot fully meet the requirements of system reliability. . Horst Ahlers said: "The future belongs to multi-sensors." Multi-sensor integrated navigation systems have become an inevitable trend. With the improvement of hardware conditions, the fusion method has become an important factor restricting the performance of the combined system. The federated Kalman filter method developed by ...

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Application Information

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IPC IPC(8): G01C21/20
Inventor 李宁袁克非袁赣南刘利强张勇刚
Owner HARBIN ENG UNIV
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