Target task intention recognition method and device based on unit distribution thermal grid

Abstract

The invention relates to a target task intention recognition method and device based on a unit distribution thermal grid. The method comprises the steps of converting the task space longitude and latitude into longitude and latitude grids according to the task space longitude and latitude; according to the position of the flight target and the task radius, constructing an air unit distribution thermal grid in a task space; determining a suspected task formation in the task space according to the thermodynamic value of the grid and the associated flight target; and judging whether each task suspected formation is a target formation or not according to a space-time consistency principle, and determining the task intention of the target formation according to the obtained platform type of theflight target in the target formation and the task target type of the task target in the task area. By adopting the method, the formation, the task area and the task intention of the flight target can be directly identified according to the information which can be obtained in real time according to the platform type, the flight path, the task target position, the task target type and the like ofthe flight target, and the problem that a traditional mode needs priori knowledge support and algorithm training is avoided.

Description

technical field [0001] The present application relates to the technical field of target recognition, in particular to a method and device for target task intention recognition based on unit distribution thermal grid. Background technique [0002] When flying platforms such as reconnaissance planes, fighter jets, and UAVs perform missions, they usually choose different flight formations according to the type of mission, in order to ensure the coordinated command and control capabilities between platforms, so as to complete more complex missions in a larger area. task. Common formation methods include horizontal formation, arrow formation, diamond formation, etc. according to the formation form, and include basic formation, dense formation, and sparse formation according to the density of platform intervals, distances, and height differences. Formation, evacuation formation, etc. [0003] At present, the methods of identifying flight target formations and their intentions ar...

AI Technical Summary

Problems solved by technology

However, these methods require a large amount of prior knowledge as data support, and require a lot of time and energy to establish the situation template library in the early stage, expert system, Bayesian network, deep learning algorithm training, etc., and cannot rely on the platform of the flight target. real-time information such as type, flight trajectory, mission target location, and mission target type can directly identify the target formation, mission area, and mission intent of the flight target

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