Gaussian filtering method based on multilayer importance sampling and Gaussian filter

A technology of importance sampling and Gaussian filtering, applied in the field of information fusion

Active Publication Date: 2016-06-22
CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0010] In view of the above-mentioned shortcoming of prior art, the object of the present invention is to provide a kind of Gaussian filter method and filter based on multilayer importance sampling, be used to solve the problem of stability, precision and the problem of nonlinear filter in practical application process. Computational Efficiency Issues

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  • Gaussian filtering method based on multilayer importance sampling and Gaussian filter
  • Gaussian filtering method based on multilayer importance sampling and Gaussian filter
  • Gaussian filtering method based on multilayer importance sampling and Gaussian filter

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Embodiment 1

[0072] In the process of target tracking, the observation station can obtain target orientation information containing noise, and the relationship between orientation information and target position information to be estimated is nonlinear, and EKF, second-order UKF, third-order CKF or fifth-order CKF nonlinearity are usually used Filtering method to obtain the motion state of the target. However, the above filtering methods cannot meet the requirements in the occasions where the target positioning requirements are high. The method provided by the invention has higher estimation accuracy than the existing methods, and can improve the accuracy of target tracking. The advantages of the present invention are illustrated below with specific implementation examples. See figure 1 , as follows:

[0073] S101: According to the pure orientation target tracking problem, establish the state equation and observation equation describing the target tracking system as follows:

[0074] ...

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Abstract

The invention provides a Gaussian filtering method based on multilayer importance sampling and a filter and belongs to the non-linear filtering technology field. The method comprises the following steps of step1, according to actual engineering application, establishing a state equation and a measurement equation of a non-linear system; step2, determining an original state of a system, wherein the original state of the system means a random distribution characteristic of the original state and includes a mean value, a covariance, a high order moment, a noise distribution characteristic and an initial measurement value; step3, according to a calculating complexity, filtering precision and a stability requirement, initializing a sample layer number and a sample type number and calculating a weight of each layer of sample points and a moment matching parameter; and then carrying out one step state prediction and one step measurement prediction, finally, carrying out state filtering updating, using Kaman gain fusion state prediction and measurement data to calculate a distribution characteristic of an optimal state so as to complete an one step estimation task of the non-linear system, and carrying out iteration and returning to a step4 so as to carry out an estimation task of a next moment. The method and the filter possess good performance and practicality.

Description

technical field [0001] The invention relates to the technical field of information fusion of nonlinear filtering, digital signal processing, target positioning and tracking, etc., in particular to a Gaussian filtering method and filter based on multi-layer importance sampling. Background technique [0002] Almost all real-world systems are nonlinear, especially in areas such as aircraft navigation, object tracking, and industrial control. For example: in the process of target positioning and tracking, when the radar is used to observe the air target, the radar can obtain the azimuth angle of the air target relative to itself, but this observation contains noise, and the azimuth observation of the radar in the observation equation is the target position parameter to be estimated Nonlinear functions cannot directly use the linear filtering method to obtain the motion state of the target. It is essentially a nonlinear filtering problem, which is a common problem in the research...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H03H17/02
CPCH03H17/02H03H2017/0205
Inventor 刘江叶松庆
Owner CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
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