Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211000109-4.doi: 10.11896/jsjkx.211000109

• Interdiscipline & Application • Previous Articles     Next Articles

Testing System of Target Recognition Method of Array Screen

PAN Deng, CAI Meng-yun, WANG Zhen-yu, LV Jia-liang   

  1. Heze Branch,Qilu University of Technology(Shandong Academy of Sciences),Biological Engineering Technology Innovation Center of Shandong Province,Heze,Shandong 274000,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:PAN Deng,born in 1988,postgraduate,research assistant.His main research interests include signal detection and processing.
    LYU Jia-liang,born in 1982,Ph.D,associate researcher.His main research interests include network security,big data and artificial intelligence.

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Abstract: In order to solve the problem that the existing array screen test system cannot judge and recognize multiple continuous target signals and the unit detection screen is susceptible to external interference,the principle of using the method of similarity coefficient is proposed.To distinguish the real target signal and interference signal of each unit detection screen output,based on the D-S evidence theory,a method to identify the real target signals and eliminate the false targets in the test system of multi photoelectric detection sensors is established.The characteristics of the output target signal which pass through the array screen test system are studied,and the distribution of the reliability function of the output signal target type under the evidence body of four unit detection screens in the array screen test system is given,and then the target recognition result is obtained through fusion processing.So this paper can achieve the goal of eliminating the false targets and signal recognition.

Key words: Array screen, Target recognition, Data fusion, Belief function

CLC Number: 

  • TP301
[1]HAN S L,LEI Z Y,WANG Z M.The intersection of vertical target accuracy measurement system for a new sky screen [J].Optics &control,2007,14(5):153-154.
[2]LU L P,ZHANG X Q.Data Fusion Method of Multi-Sensor Target Recognition in Complex Environment[J].Journal of Xi-dian University,2020,47(4):31-38.
[3]QI Y J,WANG Q.Review of Multi-Source Data Fusion Algo-rithm[J].Aerospace Electronic Warfare,2017,33(6):37-41.
[4]SHI H H,JIANG W B.Overview on D-S Evidence Theory[J].Information Construction,2015(11):331.
[5]LUO J H,YANG Y.An Overview of Target Detection Methods Based on Data Fusion[J].Control and Decision,2020,35(1):1-15.
[6]LI J,HUANG L W.Mass Function Construction Method Based on Objective Characteristics[J].Application research of Computers,2017,34(8):2312-2314.
[7]LU Y L,LEI Y J,WANG J J.Identity Fusion Method Based on Rough Sets and D-S Theory[J].Systems Engineering and Electronics,2007,29(10):1749-1752.
[8]CHEN Y F.Research on Multi-Source Data Fusion for Marine Target Recognition Based on Evidence Theory[D].Harbin:Harbin Engineering University,2015.
[9]YANG F B,WANG X X.Combination Method Conflictive Evidences in D-S Evidence Theory[M].Beijing:National Defense Industry Press,2010:65-72.
[10]FANG Y,WANG X Q,LI J,et al.Application of Target Recognition Fusion Based on D-S Evidence Theory[J].Computer Knowledge and Technology,2020,16(12):190-192.
[11]ZHANG Y.Research on Perceived Target Classification Based on Decision Fusion in Wireless Sensor Networks[D].Beijing:Beijing Jiaotong University,2019.
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