D-S evidence theory based multi-sensor information fusion method

A kind of evidence theory and multi-sensor technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of large amount of calculation, uncertainty of synthesis results, etc., and achieve the effect of reducing the amount of calculation

Inactive Publication Date: 2015-03-11
YUNNAN NORMAL UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] In order to solve the problem of large amount of calculation in the traditional evidence fusion method in evidence synthesis, the problem of one-vote veto and the uncertainty of synthesis results, the present invention further proposes a multi-sensor information fusion method based on D-S evidence theory

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  • D-S evidence theory based multi-sensor information fusion method
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  • D-S evidence theory based multi-sensor information fusion method

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specific Embodiment approach 1

[0037] Specific implementation mode one: combine figure 1 and figure 2 Describe this embodiment, the multi-sensor information fusion method based on D-S evidence theory, comprises the following steps:

[0038] Step 1. Acquisition of original evidence:

[0039] Take each sensor source of l sensors (from the perspective of data acquisition, the sensor is called a sensor source) as an evidence source, and obtain l pieces of evidence e i The evidence set E={e i , i=1, 2,...,l}; According to the set identification frame Θ={θ 1 , θ 2 ,...,θ n} put evidence e i Organized as evidence data m i (A), i=1, 2, ..., l;

[0040] Θ={θ 1 , θ 2 ,...,θ n} is a mutually exclusive and complete set of propositions called the identification frame, n is the number of propositions in the identification frame, Indicates the event or object to which the evidence data points;

[0041] Step 2. Extraction and sorting of focal element sets:

[0042] In the evidence set E, all satisfying evid...

specific Embodiment approach 2

[0056] Specific implementation mode two: the fusion weight function w described in step four i (C j ) should meet the following conditions:

[0057] (1) Fusion weight function w i (C j ) should satisfy non-negativity, that is, w i (C j )≥0, j=1,2,...,J;

[0058] (2) Fusion weight function w i (C j ) should satisfy boundedness, that is, w i (C j )≤1, j=1, 2, ..., J;

[0059] (3) Fusion weight function w i (C j ) should embody Proposition C j The degree of certainty for the focal element C in the original evidence j and C q , if C j The degree of certainty is higher than that of focal element C q , then there should be w i (C j )≥w i (C q ), wherein q is the index of focal element counting, and the meaning is the same as j, that is, q=1, 2, ..., J; w i (C q ) for C q Fusion weight function.

[0060] Other steps and parameters are the same as in the first embodiment.

specific Embodiment approach 3

[0061] Specific embodiment three: the fusion weight function w described in step four i (C j )The following conditions:

[0062] when m' i (C j ) = m i (C j ), w i (C j )=1;

[0063] when m i (C j )=0 and m' i (C j )=1,w i (C j )=0.

[0064] Fusion weight function w i (C j ) effectively reflects the reliability of the evidence.

[0065] Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.

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Abstract

The invention discloses a D-S evidence theory based multi-sensor information fusion method, relates to an evidence theory based multi-sensor information fusion method and belongs to the field of information fusion. The D-S evidence theory based multi-sensor information fusion method aims at solving the problem that a traditional evidence fusion method is large in calculated quantity and is uncertain in combination result and has one-ballot-veto problem during evidence combination. The D-S evidence theory based multi-sensor information fusion method comprises the steps of obtaining an evidence set E={ei, i=1, 2, ..., 1}; disposing the evidence ei into evidence data mi(A) according to a set identification frame theta={theta1, theta2, ..., theta n}; performing sorting from small to large according to cardinal number of the A to form an order focal element set K={C1, C2, ..., CJ}, and conducting BPA determination on evidence data mi(Cj) to obtain m'i(Cj); obtaining a fusion weighting function wi(Cj) according to wi(Cj)=1- m'i(Cj) - mi(Cj); performing evidence combination (as shown in the description) to obtain a combination result of all evidence sets and using the combination result as an output decision of a sensor. The D-S evidence theory based multi-sensor information fusion method is suitable for multi-sensor information fusion.

Description

technical field [0001] The invention relates to a multi-sensor information fusion method based on evidence theory and belongs to the field of information fusion. Background technique [0002] Multi-sensor information fusion is to synthesize and process the information obtained by different data sources or different sensors, eliminate or constrain the redundant and contradictory information that may exist between multi-sensor information, reduce the uncertainty of original information, and form a system A relatively complete and consistent description or judgment of the environment. This plays a decisive role in improving the scientific decision-making of intelligent systems, the correctness of responses, the accuracy of target positioning, and the accuracy of information positioning, thereby reducing the decision-making risk of the entire system. Multi-sensor information fusion has a wide range of applications in automatic target recognition, aircraft navigation, tactical s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G06F17/30
Inventor 王保云王婷杨昆
Owner YUNNAN NORMAL UNIV
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