Data Fusion Based on Interval Dempster-Shafer Theory for Emitter Platform Identification
Haijun Liu, Bo Wang, Zheng Liu, Yiyu Zhou · 2009
To deal with the problem of emitter platform identification caused by the feature measurement uncertainty of the platform from multi sensors, this paper proposes a new identification algorithm based on interval Dempster-Shafer theory (EDST), which models the identification output of each sensor as interval values and combines the interval outputs through interval evidence combination rules. A number of simulations are presented to demonstrate the identification capability based on the IDST algorithm. Simulation results show that the proposed algorithm can not only process the interval input data, but also can deal with scalar input data.