Multi-model self-correcting unscented Kalman Filter method

A technology of unscented Kalman and Kalman filtering, which is applied in the field of robust Kalman filtering and can solve problems such as inapplicability

Inactive Publication Date: 2018-03-09
BEIHANG UNIV
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Problems solved by technology

In addition, by linearizing the nonlinear system, a multiple-model self-calibration extended Kalman filter method (Multiple-model Self-calibration Extended Kalman Filter, MSEKF) was developed, which can solve the weak no

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  • Multi-model self-correcting unscented Kalman Filter method
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  • Multi-model self-correcting unscented Kalman Filter method

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[0117] The present invention will be described in detail below in conjunction with the drawings.

[0118] The present invention provides a multi-model self-calibration unscented Kalman filter method, and its flow chart is as follows figure 1 As shown, the time update flowchart is as figure 2 As shown, it includes the following six steps:

[0119] Step 1: Establish the basic equation of the system

[0120]

[0121]

[0122] Z k =h k (X k )+V k (43)

[0123] Where X k Represents the state vector of the system, with Corresponding to the kinetic model with unknown input and the standard kinetic model, Z k Represents the system measurement vector, f k (·) and h k (·) are the nonlinear state recurrence equation and the measurement equation, b k Represents unknown input, W k With V k Are the system noise vector and the measurement noise vector, and the variance matrix is ​​Q k And R k And meet

[0124]

[0125] In the formula, Cov[·] is the covariance, E[·] is the mathematical expectatio...

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Abstract

The present invention provides a multi-model self-calibration unscented Kalman filter method, the steps are as follows: 1: establish the basic equation of the system; 2: perform filtering initialization on the system; 3: perform time update on the system; 4: perform iterative variable update; 5 : perform measurement update; six: perform iterative calculation; through steps one to six, the present invention makes full use of the calculation results of the two methods of unscented Kalman filter and self-calibration unscented Kalman filter, relying on the Bayesian principle The multi-model estimation theory can automatically distinguish the unknown input as zero segment and non-zero segment, so that the most suitable result can be accurately selected as its prior estimate; the most important point is that the present invention is developed for strong nonlinear systems It is more widely used in engineering practical applications and has very positive application value.

Description

【Technical field】 [0001] The invention provides a multi-model self-calibration unscented Kalman filter method, which belongs to the technical field of robust Kalman filter. 【Background technique】 [0002] The problem that the system state equation is affected by unknown input is a common problem in engineering. The traditional Kalman filtering method requires the system equations to be accurate no matter for the linear system or the nonlinear system, so it cannot solve the above difficulties. The literature "Self-calibration Kalman filter method [J]. Aerodynamics Acta. 2014, 29 (06): 1363-1368" proposes a self-calibration Kalman filter method (Self-calibration Kalman Filter, SKF), which is based on While the original state equation is performing iterative operations, the unknown input items are estimated, so that the influence of the unknown input is automatically compensated. On this basis, researchers have successively developed the Self-calibration Extended Kalman Filte...

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Application Information

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IPC IPC(8): G06F17/18G06F17/11G06F17/16
CPCG06F17/18G06F17/11G06F17/16
Inventor 杨海峰傅惠民张勇波王治华肖梦丽崔轶
Owner BEIHANG UNIV
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