With three advantages of information sharing, system survival, and cost-effective exchange, Unmanned Aerial Vehicle (UAV) swarms can perform tasks at risk, such as emitter reconnaissance and positioning. Due to high risk, it’s impossible to maintain the expected effect of inter-individual cooperation among an UAV swarm. The loss of positioning UAVs and the spatiotemporal agility of a target model will also reduce the accuracy in positioning the target. Therefore, the reasonable and effective dynamic assignment of emitter reconnaissance and confrontation tasks has also become one new challenge. This paper proposes a dynamic swarm task assignment strategy to solve the above problem. For emitter reconnaissance and positioning, we study the multi-target cooperation among an UAV swarm, and take UAV relative position structure into consideration. This strategy uses the unique role conversion of the artificial bee colony algorithm to assign tasks. We also constructed a joint optimization model based on range difference and the Cramer-Rao Lower Bound with time, space and target adaptability. When the original flight trajectory does not change, the self-organizing and cooperative swarm can optimize positioning formation clustering. Simulation results show that this strategy can quickly achieve higher positioning accuracy and lower energy consumption with UAV loss rate of 8%. After 5 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$5$$\end{document} dynamic task assignments, the Root Mean Square Error is less than 50 m.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Dynamic Task Assignment Strategy for Emitter Reconnaissance and Positioning through Use of UAV Swarms


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Liu, Qi (editor) / Liu, Xiaodong (editor) / Chen, Bo (editor) / Zhang, Yiming (editor) / Peng, Jiansheng (editor) / Wang, Ruonan (author) / Gu, Yu (author) / Zhou, Zou (author) / Wang, Zhehao (author) / Xu, Fangwen (author)


    Publication date :

    2021-11-12


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Task Assignment of UAV Swarms Based on Deep Reinforcement Learning

    Bo Liu / Shulei Wang / Qinghua Li et al. | DOAJ | 2023

    Free access

    Hierarchical task assignment and path finding with limited communication for robot swarms

    Albani D. / Honig W. / Nardi D. et al. | BASE | 2021

    Free access

    Probabilistic Chain-Enhanced Parallel Genetic Algorithm for UAV Reconnaissance Task Assignment

    Jiaze Tang / Dan Liu / Qisong Wang et al. | DOAJ | 2024

    Free access

    Real-time reconnaissance task assignment of multi-UAV based on improved contract network

    Kewei, Zhang / Xiaolin, Zhao / Zongzhe, Li et al. | IEEE | 2020


    TOWARDS END TO END DESIGN OF SPACECRAFT SWARMS FOR SMALL-BODY RECONNAISSANCE

    Nallapu, Ravi / Thangavelautham, Jekanthan / Asphaug, Erik | TIBKAT | 2020