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Variational Bayesian (VB) volume strong-tracking information filtering based target tracking method

A variational Bayesian and information filtering technology, applied in the field of target tracking, can solve the problem of less application and achieve the effect of strong tracking ability

Active Publication Date: 2013-08-07
桐乡乐维新材料有限公司
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Problems solved by technology

However, the application of the VB method in nonlinear systems is still rare

Method used

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  • Variational Bayesian (VB) volume strong-tracking information filtering based target tracking method

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Experimental program
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Embodiment Construction

[0017] The following combination figure 1 The present invention is further described.

[0018] The following first establishes a model for the motion state of the tracking target, then provides the filtering formula of the volumetric strong tracking information filter, and finally introduces the implementation process of the present invention in detail based on the target model and the filtering formula of the volumetric strong tracking information filter.

[0019] 1 System Modeling

[0020] 1.1 Given the following nonlinear system dynamic model

[0021]

[0022] where is the time index, Indicates the system status ( for dimensional column vector set), is a column vector of measured values, as well as are differentiable functions. with are Gaussian white noise with zero mean, where:

[0023]

[0024] in For the averaging operation, is known, are unknown, respectively with Variance. The initial state is , the mean and variance of which are ...

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Abstract

The invention relates to a VB volume strong-tracking information filtering based target tracking method. The method comprises the steps of calculating and updating parameters in a VB method; setting an initial value of a loop control variable in the VB method to be zero, and giving a value of iterations; using the VB method to estimate an unknown variance of measurement noise; estimating a one-step prediction target state; and iteratively calculating a pseudo-observation matrix, an innovation matrix, an information matrix and an information state vector. According to the method, a self-adaptation strong-tracking information filtering method of the VB method is used, so that the strong-tracking ability is provided, the unknown variance of the measurement noise can be estimated, and the self-adaptation function is implemented. Simultaneously, an attenuation coefficient can be estimated through an iterative method, and a jacobian matrix is not required to be calculated.

Description

technical field [0001] The invention belongs to the field of target tracking of nonlinear systems, and in particular relates to an adaptive filtering method based on a volumetric strong tracking information filter. Background technique [0002] Nonlinear filtering is one of the hot topics in the field of signal processing, target tracking and control. In particular, the research on nonlinear filtering under the framework of Kalman filtering is still a very hot issue, which has received more and more attention in recent years. attention and research. [0003] The Kalman filter (KF) was originally proposed by R.E Kalman when dealing with the state estimation of linear dynamic systems. Subsequently, the Extended Kalman Filter (EKF) was proposed one after another to extend the application of KF to nonlinear systems. Because the original system is linearized using the Taylor expansion formula, the performance of EKF is not ideal, especially, the calculation of the Jacobian matr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 葛泉波姚树鹤文成林管冰蕾
Owner 桐乡乐维新材料有限公司
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