Cubature Kalman filtering (CKF) method applied to high-dimensional GNSS/INS deep coupling

A Kalman filter, deep coupling technology, applied in the field of filtering, can solve the problem of difficult nonlinear filtering methods

Active Publication Date: 2017-01-04
SOUTHEAST UNIV
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  • Application Information

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Problems solved by technology

Taking the conventional 4 visible satellites as an example, the state quantity dimension of the added tracking loop is 12 dimensions, so the existing nonlinear filtering method is difficult to apply to the high-dimensional GNSS / INS deep coupling state estimation problem

Method used

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  • Cubature Kalman filtering (CKF) method applied to high-dimensional GNSS/INS deep coupling
  • Cubature Kalman filtering (CKF) method applied to high-dimensional GNSS/INS deep coupling
  • Cubature Kalman filtering (CKF) method applied to high-dimensional GNSS/INS deep coupling

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Embodiment Construction

[0068] Such as figure 1 As shown, the volumetric Kalman filtering method suitable for high-dimensional GNSS / INS deep coupling of the present embodiment includes the following steps:

[0069] S1. Construct a high-dimensional GNSS / INS deep coupling filtering model, such as figure 2 shown.

[0070] Step S1 specifically includes:

[0071] S11, respectively setting the INS state quantity of the INS and GNSS subsystems to be x I , GNSS state quantity is x G ,in,

[0072] x I =[δP δV ψ k a b a k ω b ω ]

[0073] x G =[b c d c δρ dll δφ pll δf pll ]

[0074] where [δP δV ψ k a b a k ω b ω ] are 3D position error, velocity error, attitude error, accelerometer coefficient error, accelerometer coefficient zero bias, gyroscope coefficient error and constant value drift respectively; [b c d c δρ dll δφ pll δf pll ] are the receiver clock offset, clock drift, phase detection pseudorange error of the code tracking loop, phase error of the carrier trac...

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Abstract

The invention discloses a cubature Kalman filtering (CKF) method applied to high-dimensional GNSS/INS deep coupling. The method comprises steps: S1, a high-dimensional GNSS/INS deep coupling filtering model is built; S2, a standard cubature rule is adopted for the built filtering model to generate an initial cubature point; and S3, the novel cubature point is adopted to update the rule for CKF. The method of the invention is applied to high-dimensional GNSS/INS deep coupling, and has the advantages of high stability and high precision.

Description

technical field [0001] The invention relates to filtering technology, in particular to a volumetric Kalman filtering method suitable for high-dimensional GNSS / INS deep coupling. Background technique [0002] Nonlinear filtering is a commonly used information fusion technology in the field of integrated navigation and target tracking. Unlike the significant nonlinearity in the target tracking model, the nonlinearity error in integrated navigation is generally weak, but it is affected by factors such as filter structure, sensor sampling rate, measurement quality, and filter update rate. time-varying properties. Especially when the initial error of the system is large, the measurement noise is large, and the system carrier is highly mobile, the nonlinear state estimation based on Kalman filter (KF) is often difficult to work stably. The Extended Kalman Filter (EKF) is widely used in the engineering field. It is based on the Jacobian matrix to solve the nonlinear problem of th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S19/47G01C21/16G01C21/20
CPCG01C21/165G01C21/20G01S19/47G01C21/188G01S5/0294
Inventor 陈熙源崔冰波王威赵正扬方琳
Owner SOUTHEAST UNIV
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