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A novel approximation of basic probability assignment based on rank-level fusion |
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| Authors: | Yang Yi Han Deqiang Han Chongzhao Cao Feng |
| Institution: | 1. State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi'an Jiaotong University,Xi'an 710049, China 2. Institute of Integrated Automation, MOE KLINNS Lab, School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China 3. School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China |
| Abstract: | Belief functions theory is an important tool in the field of information fusion. However, when the cardinality of the frame of discernment becomes large, the high computational cost of evidence combination will become the bottleneck of belief functions theory in real applications. The basic probability assignment (BPA) approximations, which can reduce the complexity of the BPAs, are always used to reduce the computational cost of evidence combination. In this paper, both the cardinalities and the mass assignment values of focal elements are used as the criteria of reduction. The two criteria are jointly used by using rank-level fusion. Some experiments and related analyses are provided to illustrate and justify the proposed new BPA approximation approach. |
| Keywords: | Belief approximation Distance of evidence Evidence combination Information fusion Rank-level fusion |
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