A UAV cluster cooperative reconnaissance method based on cross mutation pigeon population optimization

Abstract

The invention discloses an unmanned aerial vehicle cluster cooperative reconnaissance method based on crossover and variation pigeon flock optimization, which comprises the implementation steps of: S1: initialization of a reconnaissance environment; S2: initialization of a multi-dimensional vector diagram and strategy updating; S3: method design based on crossover and variation pigeon flock optimization; S4: receding horizon control based on crossover and variation pigeon flock optimization; and S5: construction of a target function of crossover and variation pigeon flock optimization. Simulation of unmanned aerial vehicle cluster cooperative reconnaissance is carried out in a three-dimensional space. The main advantages of the method are mainly shown in two aspects that: in one aspect, the method is short in used time, can be used for dynamic planning, and compared to common methods, such as a Vorono graph, a game theory and the like, is high in convergence rate; and in the other aspect, reconnaissance efficiency is high, and in a case that a coverage region is not large, a target point can still be effectively reconnoitered.

Description

technical field [0001] The invention relates to a research method for unmanned aerial vehicle reconnaissance based on biological intelligence optimization, in particular to an unmanned aerial vehicle group cooperative reconnaissance method based on cross-mutation pigeon group optimization, which belongs to the field of autonomous control of unmanned aerial vehicles. Background technique [0002] UAV swarm wide-area target reconnaissance has received more and more attention in many fields, such as reconnaissance and surveillance of targets in enemy areas, search and rescue in mountainous areas, and resource exploration of mineral deposits. Due to the low cost of unmanned aerial vehicles (UAVs), zero casualties, high mobility, and good stealth performance, they are widely used. Due to the limitations of a single UAV in information collection, it is a necessary trend for UAV clusters to perform complex reconnaissance missions collaboratively. [0003] In order to enable the UA...

AI Technical Summary

Problems solved by technology

The second key issue is how to describe the reconnaissance environment and how to use the detected information to update the reconnaissance environment

[0006] Although the above reconnaissance methods have enabled the UAV cluster to have the ability of cooperative reconnaissance to a certain extent, there are still problems of low ability to search and capture targets and low search efficiency.

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