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A Robust Initial Alignment Method for Moving Base

A technology of initial alignment and moving base, applied in the field of strapdown inertial navigation system, which can solve the problem that the filter estimation cannot quickly track the system state, and the gain matrix cannot quickly control the system residual.

Inactive Publication Date: 2016-05-04
BEIJING INST OF SPACECRAFT SYST ENG +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0030] From the above analysis, it can be seen that the problem of the existing UKF algorithm is that the gain matrix cannot be quickly adjusted in time according to the filtering effect and the system residual, so that the estimation of the filter cannot quickly track the system state

Method used

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  • A Robust Initial Alignment Method for Moving Base
  • A Robust Initial Alignment Method for Moving Base
  • A Robust Initial Alignment Method for Moving Base

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Embodiment Construction

[0069] Embodiments of the present invention will be described in further detail below in conjunction with the accompanying drawings.

[0070] An initial alignment method for a moving base that improves robustness improves UKF from two aspects: model noise adaptation and observation interference adaptation, and forms a dual adaptive UKF algorithm to obtain more accurate filtering results. Include the following steps:

[0071] Step 1. Abstract the initial alignment model into the following system:

[0072] x k + 1 = f ( x k ) + w k y k ...

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Abstract

The invention relates to a moving base initial alignment method for improving robustness, which is technically characterized by comprising the following steps: abstracting an initial alignment model; comparing the innovation covariance P(img file=' DDA0000469718250000011.TIF' wi='50'he='66' / ) in the filtering algorithm with the calculated innovation covariance P(img file='DDA0000469718250000012.TIF' wi='53 he='50' / ) to obtain the change condition of the model noise variance, and adaptively scaling the model noise w; and adaptively judging the threshold of adaptive matrix traces after each filtering according to the residual between the observed value and the filtered value so as to correct the state estimation. According to the method provided by the invention, the design is reasonable, and the UKF (unscented Kalman filter) algorithm is improved from two aspects of model noise adaptation and observation interference adaptation; on one hand, an aim of stabilizing the model noise by use of a scaling factor is achieved by monitoring the predicted variance in UKF; and on the other hand, a more accurate filtering result can be obtained by monitoring the traces of the adaptive matrix based on the innovation feature and performing real-time correction to achieve an aim of inhibiting the observation interference; and the method has relatively high robustness and can realize quick stabilization.

Description

technical field [0001] The invention belongs to the technical field of strapdown inertial navigation systems, in particular to an initial alignment method for a movable base with improved robustness. Background technique [0002] Initial alignment is one of the key technologies of the strapdown inertial navigation system (Strapdown Inertial Navigation System, SINS), which directly affects the navigation performance of the strapdown inertial navigation system, that is, navigation accuracy and reaction time. According to the motion state of the inertial navigation system installation base, it can be divided into static base alignment and dynamic base alignment. When the static base is aligned, the initial position is usually known and the initial velocity is zero. It is only necessary to study how to orient the strapdown inertial navigation platform coordinate system according to the navigation coordinate system. However, the alignment environment for the alignment of the mov...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/16G01C25/00
CPCG01C21/16G01C25/005
Inventor 刘崇华杨波张弓姜竹青王宇鹏黄承恺王潇汉
Owner BEIJING INST OF SPACECRAFT SYST ENG