A uuv dynamic threat situation assessment method

Abstract

The invention belongs to the technical field of UUV autonomous control, and in particular relates to a UUV dynamic threat situation assessment method. The present invention can effectively solve the dynamic threat situation assessment problem of UUV under water, accurately evaluate the threat situation at the current moment and a continuous period of time, and obtain the threat degree ranking of various current threats through sensitivity analysis. The present invention does not simply use a static Bayesian network or a dynamic Bayesian network for evaluation, but uses the two in combination, and uses a three-level evaluation network of environment, platform, and task, which is convenient for the evaluator to understand the status of each part of the current UUV system , and at the same time, the threat mode of each threat can be deduced; finally, starting from the whole, the static network is used to conduct sensitivity analysis on the entire network, and the online quantitative and qualitative evaluation results are given for the on-site perceived environmental, platform health, and task threats. Provide input information for the subsequent autonomous control of UUV, and determine the most urgent threat problems to be solved at present.

Description

technical field [0001] The invention belongs to the technical field of UUV autonomous control, and in particular relates to a UUV dynamic threat situation assessment method. Background technique [0002] At present, there are many literatures on threat situation assessment of unmanned systems, but most of them are aimed at unmanned aerial vehicles. A representative example is the literature "Johan Ivansson. Situation Assessment in a Stochastic Environment using Bayesian Networks [D]. Master Thesis University, 2002.", used the fuzzy Bayesian network to make the assessment when the aerial vehicle faces dynamic environment changes. The basic idea is to classify and distinguish different objects, and divide them into non-enemy and enemy according to the different threat degree. The enemy is also distinguished according to different threat degrees. The document "Liang Hongquan. The application of dynamic Bayesian network in the threat assessment of battlefield target situation [...

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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

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