A drifting ensemble prediction method for targets in distress at sea considering feedback information

Abstract

The invention provides a maritime distress target drift set prediction method considering feedback information. The method comprises the steps of establishing a maritime search and rescue emergency guarantee database; establishing a maritime distress target drift trajectory prediction model which comprehensively considers the combined action of wind, wave and current; performing full-dimensional disturbance on the wind field, the flow field, the wave field, the distress place, the distress time, the wind-induced drift coefficient, the wave-induced drift coefficient and the flow-induced drift coefficient, constructing set members, and performing offshore distress target drift track set prediction; on the basis of the maritime distress target drift trajectory prediction model, maritime distress target drift trajectory set prediction is carried out, a search and rescue range is further calculated, and a maritime distress target drift set prediction result is obtained; in the process of searching the distress target, performing matching analysis on the set prediction result according to feedback information received in real time; optimizing and adjusting the disturbance vector according to an analysis result, and re-carrying out offshore distress target drift trajectory set prediction until a distress target is found.

Description

technical field [0001] The invention relates to the technical field of maritime search and rescue, in particular to a drift set prediction method for targets in distress at sea considering feedback information. Background technique [0002] In recent years, maritime activities such as maritime trade and resource development have become increasingly frequent, and the risk of maritime accidents has also increased. The issue of maritime security has received increasing public and political attention. The research on the drift prediction of targets in distress at sea can mobilize search and rescue forces more effectively in the case of limited input, reduce the blindness of search and rescue work, provide decision support for maritime search and rescue work, and provide support for minimizing personal and property losses. Scientific method and technical support. Therefore, in order to improve the efficiency and accuracy of maritime search and rescue command and coordination, t...

AI Technical Summary

Problems solved by technology

At present, the common drift prediction models only consider one or several components when using the Monte Carlo method to perturb the above factors. However, this method is often difficult to simulate the real systematic error of the forecast field

In addition, there is no effective feedback mechanism established between the existing drift prediction model and search and rescue operations, resulting in the model not being able to update the prediction results synchronously with real-time feedback of search and rescue information

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