Unmanned aerial vehicle cluster collaborative ground strike method based on improved wolf pack optimization algorithm

An optimization algorithm, UAV technology, applied in instruments, three-dimensional position/channel control, control/regulation systems, etc., can solve problems such as inapplicability, and achieve fast convergence speed, enhanced population diversity, and strong global search performance. Effect

Pending Publication Date: 2022-05-06
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

Therefore it is not suitable for complex mission planning problems

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  • Unmanned aerial vehicle cluster collaborative ground strike method based on improved wolf pack optimization algorithm
  • Unmanned aerial vehicle cluster collaborative ground strike method based on improved wolf pack optimization algorithm
  • Unmanned aerial vehicle cluster collaborative ground strike method based on improved wolf pack optimization algorithm

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Embodiment Construction

[0089] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0090] The present invention proposes a UAV cluster cooperative dynamic target search method based on improved pigeon group optimization, which specifically includes the following steps:

[0091] Step 1: Strike mission condition setting: including mission scenarios, UAV capabilities, and target quantity types, etc.

[0092] The embodiment of the present invention provides a schematic diagram of the task environment and the UAV state space, such as figure 1 As shown, there are N in the task scene T target to be executed, and the number of heterogeneous UAVs to execute the task is N M . There are 3 types of bases with a total of N M Heterogeneous UAVs, with collection It includes UAVs with only attack capabilities, UAVs with only evaluation capabilities, and UAVs with integrated attack and evaluation capabilities.

[0093] The target set is expressed as ...

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Abstract

The invention discloses an unmanned aerial vehicle cluster collaborative ground strike method based on an improved wolf pack optimization algorithm, and the method comprises the steps: firstly, building a task distribution model which comprehensively considers the performances of unmanned aerial vehicles, carrying reconnaissance resources, target information, time sequence constraints, balanced strike and other conditions; secondly, considering the problem that a traditional wolf pack algorithm is not suitable for task allocation, and redesigning a discrete wolf pack algorithm in order to improve the global optimization efficiency of the algorithm; and then, combining with a 2-opt reverse mutation algorithm and a new encoding and decoding mode, and providing an improved wolf pack optimization algorithm. The multi-constraint multi-task distribution model established by the invention and the improved wolf pack optimization algorithm successfully meet the effectiveness and superiority of the distribution scheme on the ground strike problem, and meanwhile, the task time sequence constraint is met after the decoding is completed.

Description

technical field [0001] The invention belongs to the field of unmanned aerial vehicle cluster task planning, and specifically discloses a coordinated ground strike method for unmanned aerial vehicle clusters based on an improved wolf pack optimization algorithm. Background technique [0002] With the rapid development of science and information technology, Unmanned Aerial Vehicle (UAV) has attracted the attention of scholars at home and abroad because of its simplicity, flexibility and low cost. The UAV industry is in the ascendant. It is a sunrise industry with rapid development and wide application for a long time now and in the future. Various types of UAVs are increasingly widely used in the military and people's livelihood fields. However, due to constraints such as endurance time, weapon load, and reconnaissance performance of a single UAV, combat missions in complex environments are becoming more and more difficult to achieve. However, due to the continuous progress o...

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Application Information

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IPC IPC(8): G05D1/10
CPCG05D1/101
Inventor 卢佳峰江驹余朝军韩冰张哲刘翔
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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