Method, device and system for merging information from several sensors
AssigneesThales & Universite de Technologie, DE Compiegne -UMRCNRS
InventorsFrédéric Pichon, Thierry Denoeux
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Abstract
The invention relates to a method, a device and a system for merging information originating from several non-independent sensors. This invention makes it possible to prevent the same item of information from being reckoned twice during merging. The solution afforded consists of the creation of a new combination operator applying to latent belief structures. Said latent belief structures are obtained previously from conventional belief functions. These conventional belief functions are produced directly on the basis, for example, of the sensors of the system. The invention also proposes a means of transforming these latent belief structures into a probability distribution useful for decision taking.
Claims8
A method for merging information originating from several sensors c1, c2, . . . , cn, n being the number of sensors, said method comprising the following steps:
- the acquisition of belief functions m1, m2, . . . , mn arising from the sensors c1, c2, . . . , cn, said belief functions m1, m2, . . . , mn being defined on a set of proposals Ω, wherein Ω is a space of possible worlds with finite cardinality and wherein Ø is the empty set,
- the calculation of latent belief structures LBS1, LBS2, . . . , LBSn for each belief function m1, m2, . . . , mn, said latent belief structures LBS1, LBS2, . . . , LBSn each comprising pairs of confidence and distrust functions (w1c, w1d), (w2c, w2d), . . . , (wnc, wnd),
- wherein said sensors c1, c2, . . . , cn are non-independent and wherein it furthermore comprises the following steps:
- the calculation of a merged latent belief structure LBSm, said merged latent belief structure LBSm comprising a pair of functions wmc and wmd calculated by applying a so-called weak-rule function to the confidence and distrust functions (w1c, w1d), (w2c, w2d), . . . , (wnc, wnd):
- wmc(A)=w1c(A)w2c(A) . . . wnc(A), A⊂Ω
- wmd(A)=w1d(A)w2d(A) . . . wnd(A), A⊂Ω
- wmc and wmd being defined on all the subsets A of Ω,
- the calculation of a probability distribution Pm on the basis of the functions wmc and wmd,
- the calculation of commonality functions qmc and qmd on the basis of the functions wmc and wmd,
- the calculation of plausibility functions plmc and plmd on the basis of the commonality functions qmc and qmd, by using the following equations:
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- wherein A and B are subsets of Ω,
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A device for merging information comprising:
- a computer processor configured to apply belief functions m1, m2, . . . , mn to information from sensors coupled to the processor,
- wherein the processor is also configured to merge results from the belief functions m1 . . . mn,
- and wherein the processor is further configured to determine the probability distribution based on calculating plausibility functions plmc and plmd on the basis of the commonality functions qmc and qmd, by using the following equations:
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A system for merging information comprising:
- at least two sensors collecting data and providing information,
- a computer processor linked to the sensors for merging information originating from said sensors,
- wherein said sensors are non-independent and wherein the processor for merging information is configured to:
- apply belief functions m1, m2, . . . , mn to information from sensors coupled to the processor,
- wherein the processor is also configured to merge results from the belief functions m1 . . . mn,
- and wherein, the processor is further configured to determine the probability distribution based on calculating plausibility functions plmc and plmd on the basis of the commonality functions qmc and qmd, by using the following equations:
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Dependencies are inferred from the claim text.