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Target tracking method based on distributed matrix weighted fusion Gaussian filtering

A matrix weighting and Gaussian filtering technology, which is applied in character and pattern recognition, complex mathematical operations, instruments, etc., can solve the problem of not being able to obtain local filter error covariance, and achieve the effect of improving target tracking accuracy and reducing performance loss

Pending Publication Date: 2021-05-14
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0004] In order to solve the problem that the error covariance between local filters cannot be obtained when the existing nonlinear moving target tracking method is fused, the present invention proposes a target tracking method based on distributed matrix weighted fusion Gaussian filtering, which improves the target tracking accuracy and robustness

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  • Target tracking method based on distributed matrix weighted fusion Gaussian filtering
  • Target tracking method based on distributed matrix weighted fusion Gaussian filtering
  • Target tracking method based on distributed matrix weighted fusion Gaussian filtering

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Embodiment Construction

[0051] The present invention will be further described below in conjunction with the accompanying drawings.

[0052] refer to Figure 1 to Figure 4 , a target tracking method based on distributed matrix weighted fusion Gaussian filtering, the method includes the following steps:

[0053] Step 1: Establish the state space model and measurement model of the nonlinear system, the process is as follows:

[0054] 1.1 Establish a system state model

[0055] x k+1 =f(x k )+w k (1)

[0056] where x k is the system state at time k, f(x k )∈R n is any nonlinear vector function, w k For the covariance is Q k Gaussian white noise;

[0057] 1.2 Establish system measurement model

[0058]

[0059] where i is the number of the observation station, is the measurement value of the i-th observation station at time k+1, is any nonlinear vector function, is the covariance of Gaussian white noise;

[0060] Step 2: Calculate local Gaussian filter estimation and covariance, ...

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Abstract

The invention discloses a target tracking method based on distributed matrix weighted fusion Gaussian filtering, and the method comprises the steps: firstly carrying out the local state estimation through Gaussian filtering, then approaching an error cross covariance between local estimation through employing a statistical linear regression method, and finally obtaining an optimal parameter under a maximum likelihood criterion through solving an optimization problem, and adjusting the error cross covariance matrix. According to the method, the performance loss caused by linearization errors in statistical linear regression is reduced, and the target tracking precision is improved.

Description

technical field [0001] The invention belongs to the field of moving target tracking, and in particular relates to a target tracking method based on distributed matrix weighted fusion Gaussian filtering. Background technique [0002] Target tracking is a basic problem in the military and civilian fields, and plays an important role in the fields of military defense, urban transportation, and home services. In recent years, with the rapid development of communication technology and microelectronics technology, wireless sensor networks have been widely used in the positioning and tracking of moving targets, and people have higher and higher requirements for the accuracy of target tracking. [0003] In moving target tracking, nonlinear filtering problems are usually involved. Gaussian filtering is a kind of nonlinear filtering method, which is widely used in practical systems. However, Gaussian filtering only considers a single sensor, and the estimation accuracy often cannot ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06F17/16
CPCG06F17/16G06F2218/00G06F18/25
Inventor 陈博鲍元康胡中尧李同祥
Owner ZHEJIANG UNIV OF TECH
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