A new model for threat assessment in data fusion based on fuzzy evidence theory

Abstract

In this paper a new method for threat assessment is proposed based on Fuzzy Evidence Theory. The most widely classical and intelligent methods used for threat assessment systems will be Evidence or Dempster Shafer and Fuzzy Sets Theories. The disadvantage of both methods is failing to calculate of uncertainty in the data from the sensors and the poor reliability of system. To fix this flaw in the system of dynamic targets threat assessment is proposed fuzzy evidence theory as a combination of both Dempster- Shafer and Fuzzy Sets Theories. In this model, the uncertainty in input data from the sensors and the whole system is measured using the best measure of the uncertainty. Also, a comprehensive comparison is done between the uncertainty of fuzzy model and fuzzy- evidence model (proposed method). This method applied to a real time scenario for air threat assessment. The simulation results show that this method is reasonable, effective, accuracy and reliability.