Situation estimation method based on improved D-S evidence theory

A kind of evidence theory, D-S technology, applied in the field of situation estimation based on improved D-S evidence theory, can solve the problem of inaccurate and unreasonable conflict measurement

Pending Publication Date: 2021-04-30
DALIAN UNIVERSITY
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  • Application Information

AI Technical Summary

Problems solved by technology

General conflict problem: When the basic probability assignment reported by the sensor is seriously contradictory, the result after fusion will be obviously unreasonable
[0007] Although the above improved methods have been improved to a certain extent, at the same time, the measurement of conflicts is not accurate enough

Method used

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  • Situation estimation method based on improved D-S evidence theory
  • Situation estimation method based on improved D-S evidence theory
  • Situation estimation method based on improved D-S evidence theory

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Embodiment 1

[0072] For battlefield situation estimation, it is necessary to predict the possible situation of the enemy based on knowledge in the military field under a specific combat mission. figure 1 The general process of applying the D-S evidence theory to fuse battlefield situation information is given. Suppose the identification framework contains a total of n propositions. In the figure, m 1 (A i ), m 2 (A i ),…, m q (A i ), i=1,2,...,n is the obtained q evidences for proposition A i The basic probability distribution of m(A i ) represents the new basic probability distribution obtained through evidence fusion.

[0073] for figure 1The content in the middle dotted line box is the evidence fusion part. Since the fusion process between multiple evidences has nothing to do with the sequence, it is equivalent to the recursive process of two evidence fusion calculations. The equivalent diagram is as follows: figure 2 shown.

[0074] Depend on figure 2 It can be seen that th...

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Abstract

The invention provides a situation estimation method based on an improved D-S evidence theory. The situation estimation method comprises the following steps: setting an identification framework; constructing a basic probability distribution function; setting a reliability function; and setting a likelihood function, and finally outputting a result through fusion. The invention aims at solving the problem that Dempster fusion rules in the D-S evidence theory cannot effectively process fusion between high-conflict evidences. A fusion rule is improved, and the conflict between evidences is mainly generated due to the fact that the basic probability distribution of the same focal element in the evidences has a large difference. Considering that the variance is just used for describing the fluctuation degree of a group of data, the larger the basic probability distribution variance of the same focal element of different evidences is, the larger the conflict of the evidences with the focal element is; otherwise, the smaller the variance is, the different evidences basically keep the same attitude relative to the focal element, that is, the smaller the conflict is.

Description

technical field [0001] The present invention relates to the technical field of data fusion algorithms, in particular to a situation estimation method based on improved D-S evidence theory. Background technique [0002] Information has become a key factor in determining the outcome of a war. Whoever can fully obtain and utilize effective information will have an advantage in the battle. According to the definition of JDL, the joint laboratory of the US Department of Defense: Situation estimation is at the second level of data fusion. According to the results of the first level of fusion, it can extract as accurate and complete perception of the current battlefield situation as possible, so as to gradually understand local intentions and combat plans. To provide direct support for the commander's decision-making, the research methods related to situation estimation mainly include template matching method, fuzzy set method, D-S (Dempster-Shafer) evidence theory and Bayesian net...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F17/18
CPCG06F17/18G06F18/25
Inventor 杜秀丽邱少明聂彦刚王健吕亚娜
Owner DALIAN UNIVERSITY
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