System state estimation method based on state augmentation iterated extended Kalman filter

An extended Kalman and system state technology, applied in the field of communication, can solve the problems of reducing filtering accuracy, system state and measurement noise no longer satisfy the mutual orthogonal relationship, and achieve the effect of high filtering accuracy and fast convergence speed

Inactive Publication Date: 2018-03-06
TAIYUAN UNIV OF TECH
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Problems solved by technology

However, the latter modified iterative algorithm (Modified Iterated Extended Kalman Filter-Modified IEKF) has the following disadvantages: In the process of filtering measurement update, after the first iteration,

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  • System state estimation method based on state augmentation iterated extended Kalman filter
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  • System state estimation method based on state augmentation iterated extended Kalman filter

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[0011] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention can be implemented in many other ways different from those described here, and those skilled in the art can make similar extensions without violating the connotation of the present invention, so the present invention is not limited by the specific implementations disclosed below.

[0012] Secondly, the present invention is described in detail by means of schematic diagrams. When describing the embodiments of the present invention in detail, for convenience of explanation, the schematic diagrams are only examples, which should not limit the protection scope of the present invention.

[0013] refer to figure 1 , figure 1 It is a schematic flowchart of a system state estimation method based on the state augmentation iterative extended Kalman filter algorithm provided by the present invention.

[0014] ...

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Abstract

The invention discloses a system state estimation method based on a state augmentation iterated extended Kalman filter algorithm. The method adopts an accurate formula to calculate, measure and predicate a covariance matrix; and compared with an existing EKF and Modified IEKF algorithm, the method based on the state augmentation iterated extended Kalman filter algorithm can meet mutually-orthogonal relation between system state and measurement noise, and has faster convergence rate and higher filtering precision after calibration of position, velocity and ballistic coefficient estimation errors.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a system state estimation method based on state augmentation iterative extended Kalman filter algorithm. Background technique [0002] In ballistic reentry target tracking applications, the most commonly used algorithm is Extended Kalman Filter (Extended KalmanFilter-EKF). For the strongly nonlinear measurement model, in order to improve the tracking accuracy, an iterative extended Kalman filter algorithm based on state augmentation can be used. This can not only improve the target tracking accuracy, but also has important practical significance in quick response and target interception. [0003] After searching the prior art literature, it was found that Bell Bradley M. and Cathey Frederick W. wrote the article "The Iterated Kalman Filter Update as a Gauss-Newton Method" [J] / / IEEETransactions on automatic control, Vol.38, No. 2, 1993, pp.294-297 and Yang Zhengbin, Zhong...

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Application Information

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IPC IPC(8): G01S13/72G01S13/00G06F17/11G06F17/18G06F17/16
CPCG01S13/006G01S13/72G06F17/11G06F17/16G06F17/18
Inventor 李伟柴晶
Owner TAIYUAN UNIV OF TECH
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