Data fusion method and device

Abstract

The invention discloses a data fusion method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: establishing an identification framework; Calculating a basic probability assignment, provided by any homogeneous data, of the to-be-identified object based on the identification framework by utilizing a preset basic probability distribution function; Performing orthogonal sum operation on the basic probability assignment provided by the homogeneous data acquired by any data acquisition system in a plurality of periods to obtain a time dimension probability assignment of the to-be-identified object in the data acquisition system; And performing orthogonal sum operation on the time dimension probability assignment of theto-be-identified object in the plurality of data acquisition systems to obtain the space-time dimension probability assignment of the to-be-identified object in the plurality of data acquisition systems and the plurality of periods, And determining an identification result of the to-be-identified object in the identification framework by utilizing the space-time dimension probability assignment.According to the embodiment, multi-source data can be effectively fused under the condition that the prior probability is not known, and a recognition result with high reliability is obtained.

Description

technical field [0001] The present invention relates to the field of computer technology, and in particular, to a data fusion method and device. Background technique [0002] With the rapid development of computer technology, multi-channel and various types of massive data are constantly emerging. How to analyze and integrate the available data to achieve the desired decision has become a problem that needs to be solved. For example, the fusion of data collected by multi-sensors in unmanned aerial vehicles, unmanned warehouses or unmanned vehicles, and the fusion of business data collected by multiple monitoring systems of the service provider all need to be realized by using effective data fusion methods. [0003] In the field of computer technology, data fusion refers to collecting, transmitting, synthesizing, filtering, correlating or synthesizing the available information provided by various information sources to realize decision, planning, detection, verification and d...

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Problems solved by technology

[0004] In the process of realizing the present invention, the inventor finds that the prior art has at least the following problems: Bayesian algorithm requires all assumptions to be independent, and needs to know prior probability and conditional probability in advance, which is difficult in practical application Realized, so its application value is low

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