Meteorological threat assessment method based on discrete dynamic Bayesian network

Abstract

The invention discloses a meteorological threat assessment method based on a discrete dynamic Bayesian network. The method comprises the following steps: collecting an observed weather type, intensity information and UAV (Unmanned Aerial Vehicle) position and attitude information; performing a quantization treatment according to a divided quantization level, and establishing an observation evidence list; using expert knowledge or experience to establish a conditional probability transfer matrix between states, and determining a state transfer matrix between time slices; establishing a discrete dynamic Bayesian network model between a meteorological threat level, a meteorological factor and the UAV; and using a Hidden Markov Model reasoning algorithm to calculate the final meteorological threat level. The meteorological threat assessment method based on the discrete dynamic Bayesian network provided by the invention realizes the organic combination of a continuous observation value and the discrete dynamic Bayesian network, and reasons out the probability distribution of a meteorological threat degree in combination with the HMM (Hidden Markov Model) reasoning algorithm, so that the effectiveness, the practicability and the accuracy of meteorological assessment can be greatly improved.

Description

technical field [0001] The invention belongs to the field of meteorological evaluation, in particular to a method for evaluating meteorological threats based on a discrete dynamic Bayesian network. Background technique [0002] Among the problems of UAV route planning, the threat caused by meteorological factors has an important impact on the flight safety of UAVs when they perform reconnaissance operations. In order to minimize the loss of UAVs due to meteorological factors while flying, and to plan a safer route under existing constraints, it is an urgent need to study how to make a more accurate quantitative assessment of meteorological threats. Meteorological threats have their unique characteristics, such as ambiguity, uncertainty, and timeliness, so conventional methods, such as function methods, cannot be used to quantitatively analyze meteorological threats. In some foreign studies, such as the man-machine meteorological evaluation method and the engineering mathema...

AI Technical Summary

Problems solved by technology

[0004] The object of the present invention is to provide a kind of meteorological threat assessment method based on discrete dynamic Bayesian network, aiming

Images