Exponential correlation dynamic threat assessment under multi-type heterogeneous data

In view of the existing air combat target threat assessment methods mainly deal with data of the same structure type, the discrimination of target threat value is not high, and the time weight allocation is not rigorous in the process of dynamic assessment, this paper proposes an exponential correlation dynamic threat assessment method for multi-type heterogeneous data. First, the heterogeneous data is mapped to D-U space to obtain the isomer data, then the attribute weight is solved based on the index correlation degree, and the time weight is solved based on the deviation and grey entropy method. Finally, the comprehensive evaluation value and relative proximity of the target are obtained according to the above calculation to complete the threat ranking. Experimental analysis shows that this method can improve the problem of small distinction between feature attributes, assign time weight more reasonably, and make isomerization of heterogeneous data, effectively deal with uncertain information, adapt to battlefield dynamics, and provide a new solution for air combat decision.