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System state prediction device and method based on Kalman filter

A Kalman filter and system state technology, which is applied in the engineering field, can solve the problem that the Kalman filter cannot accurately track targets, and achieve the effect of accurate prediction

Active Publication Date: 2019-01-01
毫末智行科技有限公司
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Problems solved by technology

However, since the existing Kalman filter assumes that the noise in the target tracking process and the measurement noise satisfy the Gaussian distribution, therefore, in the case that the noise in the actual target tracking process and the measurement noise do not satisfy the Gaussian distribution, the Kalman filter Inability to track objects accurately

Method used

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  • System state prediction device and method based on Kalman filter

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Embodiment Construction

[0045] It should be noted that, in the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other.

[0046] Before describing in detail the Kalman filter-based system state prediction device and method according to the embodiments of the present disclosure, a basic model of the Kalman filter is briefly introduced first.

[0047] The basic model of the Kalman filter is as figure 1 shown. Among them, the basic equation of the Kalman filter can be expressed as:

[0048]

[0049]

[0050] in, Indicates the prior state estimate at time t+1 obtained from the measured values ​​from time 1 to time t, F t represents a linear model for time transformation, Denotes the posterior state estimate at time t estimated from the prior state estimate at time t and the measured value at time t, Denotes the prior state estimation value at time t obtained from the measured values ​​from time 1 to time t-1, K t repr...

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Abstract

The invention provides a system state prediction device and method based on a Kalman filter which relate to the technical field of engineering and can accurately predict system states. The system state prediction device based on the Kalman filter includes a priori state prediction module used for predicting a priori state estimation value at time t according to a measured value at time 1 to t-1; ameasured value acquiring module used for acquiring a measured value at the time t; a noise filtering module used for filtering non-Gaussian noise in the measured value obtained at the time t; and a posteriori state estimation module used for estimating a posterior state estimation value at the time based on the priori state estimation value predicted at the time t and the measured value at the time t after the non-Gaussian noise is filtered.

Description

technical field [0001] The present disclosure relates to the field of engineering technology, in particular to a system state prediction device and method based on a Kalman filter. Background technique [0002] At present, the Kalman filter is usually used for target tracking. However, since the existing Kalman filter assumes that the noise in the target tracking process and the measurement noise satisfy the Gaussian distribution, therefore, in the case that the noise in the actual target tracking process and the measurement noise do not satisfy the Gaussian distribution, the Kalman filter Target tracking cannot be performed accurately. Contents of the invention [0003] In view of this, the present disclosure aims to propose a system state prediction device based on a Kalman filter, so as to accurately predict the system state. [0004] In order to achieve the above object, the technical solution of the present disclosure is achieved in the following way: [0005] A sy...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/02G06F17/18
CPCG06F17/18G06Q10/02
Inventor 宫原俊二
Owner 毫末智行科技有限公司
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