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Cyber-physical battlefield perception systems based on machine learning technology for data delivery

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Abstract

Data delivery in Cyber-Physical Battlefield Perception Systems(CPBPS) is a challenging task due to the ubiquity locations and the high mobility of node. Due to the special geographical circumstances, communication networks based on fixed infrastructure are unlikely to be established. This paper presents an air-ground coordination communication transmission network, which consists of Unmanned Aerial Vehicle (UAV) subnets and ground vehicle subnets. The UAVs exploit air-to-air (A2A) and air-to-ground (A2G) communication links to assist vehicle communications. However, overreliance on satellite positioning may cause military information to leak. Therefore, we proposed a K-Nearest Neighbor (KNN )combined with genetic algorithms and based on machine learning system (MLS) for data delivery for battlefield environment to realize the privacy protection and guarantee the security with better prediction. The proposed KNN machine learning system can estimate the movement and path of vehicles based on the mobile information obtained. Furthermore, in order to transmit data of UAVs more efficiently, the genetic algorithms (GA) is utilized to determine the relative location of UAVs. Simulation results verify the performance of proposed algorithm.

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Acknowledgments

This work was supported in part by Research Project for FY2017 of International Association of Maritime Universities, China Postdoctoral Science Foundation under Grant 2015T80238, Natural Science Foundation of China under Grant 61401057, Natural Science Foundation of Liaoning Province under Grant 201602083, Science and technology research program of Liaoning under Grant L2014213, Dalian science and technology project under Grant 2015A11GX018, Research Funds for the Central Universities 3132016007 and 01760325. Dalian high-level innovative talent project under Grant 2016RQ035.

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Authors and Affiliations

  1. Navigation College, Dalian Maritime University, 1 Linghai Road, Dalian, Liaoning, China

    Jian Zhao, Chengzhuo Han, Zhengqi Cui, Rui Wang & Tingting Yang

  2. School of Electrical Engineering, Intelligentization, Dongguan University of Technology, Dongguan, China

    Tingting Yang

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  1. Jian Zhao
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Correspondence to Tingting Yang.

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This article is part of the Topical Collection: Special Issue on Networked Cyber-Physical Systems

Guest Editors: Heng Zhang, Mohammed Chadli, Zhiguo Shi, Yanzheng Zhu, and Zhaojian Li

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Zhao, J., Han, C., Cui, Z. et al. Cyber-physical battlefield perception systems based on machine learning technology for data delivery. Peer-to-Peer Netw. Appl. 12, 1785–1798 (2019). https://doi.org/10.1007/s12083-019-00769-5

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