A multi-target threat assessment method suitable for highly dynamic environment

Abstract

The invention discloses a multi-target threat assessment method suitable for a high dynamic environment, which relates to high-level information fusion and decision problems of a sensor network. Basedon the entropy measurement method and dynamic intuitionistic fuzzy method, the attributes of battlefield targets are reasonably weighted, and attribute information of multiple successive time of eachtarget is selected, according to the importance of target information in threat assessment, the time series weights of target information are calculated by the normal distribution method, and the target information at multiple times is weighted synthetically according to the time series weights; on the basis, the dynamic intuitionistic fuzzy multi-target threat estimation model is established, and the final dynamic threat assessment result, i.e., the threat degree ranking of multi-targets, is calculated. The method not only considers the current time target information, but also can effectively fuse the preorder time target related information, so it can dynamically reflect the continuously changing battlefield situation, and make the multi-target threat assessment effect more scientificand reasonable under the highly dynamic environment.

Description

technical field [0001] The invention relates to a sensor network high-level information fusion system, in particular to a multi-target threat assessment method suitable for high dynamic environments, suitable for various sensor network fusion and decision-making systems. Background technique [0002] Modern warfare is mostly group operations, which requires our commanders to make timely and reasonable assessments of the threat of enemy targets based on the real-time changing battlefield situation in the face of enemy multi-platform attacks, and improve the effectiveness of multi-target enemy attacks. Attack combat efficiency and own survival probability. [0003] Currently commonly used threat assessment methods include multi-attribute decision-making theory, fuzzy reasoning, Bayesian reasoning, cloud models, expert systems, etc., but these methods basically use the target information collected at the current moment for evaluation, that is, static evaluation. However, swarm...

AI Technical Summary

Problems solved by technology

However, swarm networked combat is a highly dynamic and continuous process. The use of static assessment methods will lead to the loss of battlefield situation information before the current moment. It is difficult to make an objective and comprehensive analysis of the battlefield situation in a highly dynamic environment, which will lead to threats The plausibility of the evaluation results is greatly reduced

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