A UUV dynamic threat situation assessment method

Abstract

The invention belongs to the technical field of UUV autonomous control, and particularly relates to a UUV dynamic threat situation assessment method. The method can effectively solve the underwater dynamic threat situation assessment problem of the UUV, accurately assesses the threat situation at the current moment and within a period of continuous time, and can obtain the threat degree sequence of various current threats through sensitivity analysis. According to the method, a static Bayesian network or a dynamic Bayesian network is not singly used for evaluation, but the static Bayesian network and the dynamic Bayesian network are combined for use, and an environment, platform and task three-level evaluation network is used, so that an evaluator can conveniently know the conditions of all parts of the current UUV system, and meanwhile, a threat mode of each threat can be reasoned out; and finally, starting from the whole, a static network is used for carrying out sensitivity analysison the whole network, an online quantitative qualitative evaluation result is given for threats of an environment type, a platform health type and a task type sensed on site, input information is provided for subsequent autonomous control of the UUV, and the most urgent threat problem to be solved at present is decided.

Description

Technical field [0001] The invention belongs to the technical field of UUV autonomous control, and specifically relates to a UUV dynamic threat situation assessment method. Background technique [0002] There are many documents on threat situation assessment of unmanned systems, but most of them are for unmanned aerial vehicles, such as the document "Johan Ivansson.Situation Assessment in a Stochastic Environment using Bayesian Networks[D].Master Thesis University, 2002.", used fuzzy Bayesian network to make the assessment of aerial vehicles facing dynamic environment changes. The basic idea is to classify different objects, and divide them into non-enemy and enemy according to the different threats. Enemies are also distinguished according to different threat levels. The literature "Liang Hongquan. The application of dynamic Bayesian network in the threat assessment of battlefield target situation [D]. Master's thesis of Beijing University of Posts and Telecommunications, 2007."...

AI Technical Summary

Problems solved by technology

[0003] Threat Situation Assessment Method for Underwater Unmanned Vehicles (UUV), "Hong Wei, Li Changjun, Li Zhuo. UUV Threat Assessment Based on Bayesian Networks [J]. Ordnance Equipment Engineering Journal, 2009, 30(3) :89-91.” proposed a method to assess threat types, counter-threat capabilities, and navigation status based on the current UUV threat level, but this method lacks sources for the assessment of the UUV’s current threat level and needs to be artificially set. Doing this unattended makes the method much less useful

Images