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Research on safety modeling and analysis in information fusion system

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Abstract

Avionics system integration is a prominent trend in research and development of civil airplane. It can improve task effectiveness, function efficiency, and resource utilization of system. Information fusion, which includes function information fusion, processing information fusion, and sensor input fusion, is a core process of avionics system integration. Some researches about the impact of information fusion on system safety are done in avionics system which is shown as follows: (1) the concept of Mishap Dilution, Mishap Implication and Mishap Confusion (MD–MI–MC) is first defined in function information fusion of avionics system. (2) The model of multi-source MD–MI–MC is established based on hazard theory. (3) The function fusion of Automatic-Dependent Surveillance–Broadcast (ADS–B) and Traffic Collision Avoidance System (TCAS) is used as a typical example to analyze fusion system during the aircraft climbing or landing state. In this paper, the concept and model of multi-source MD–MI–MC are proposed for safety analysis of integrated avionics system. A fusion model with a variable sampling Variational Bayesian–Interacting Multiple Model (VSVB–IMM) algorithm is used to analyze. At last, a set of theory system and evaluation standards including the positive and negative earning analyses are built based on the presented MD–MI–MC theory and mechanism of integrated avionics.

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References

  1. Wang G, Gu Q, Wang M, Wang Y (2014) Research on integrated technology and model in avionics system. In: Digital avionics systems conference, pp 4A2-1–4A2-11

  2. Mahler RP (2014) Advances in statistical multisource-multitarget information fusion. Artech House, Norwood

    MATH  Google Scholar 

  3. Wang G (2012) Integration technology for avionics system. In: Digital avionics systems conference, pp 7C6-1–7C6-9

  4. Badache N, Jaffres-Runser K, Scharbarg JL, Fraboul C (2013) End-to-end delay analysis in an integrated modular avionics architecture. In: Emerging technologies and factory automation, pp 1–4

  5. Wu J, Yue T, Ali S, Zhang H (2013) Ensuring safety of avionics software at the architecture design level: an industrial case study. In: International conference on quality software, pp 55–64

  6. Luo RC, Ying CC, Chen O (2002) Multisensor fusion and integration: algorithms, applications, and future research directions. IEEE Sens J 2(2):107–119

    Article  Google Scholar 

  7. Kunzi F (2011) ADS-B benefits to general aviation and barriers to implementation. Massachusetts Institute of Technology, Cambridge

    Google Scholar 

  8. Kuchar JE, Drumm AC (2007) The traffic alert and collision avoidance system. Linc Lab J 16(2):277

    Google Scholar 

  9. Wang Y, Xiao G, Dai Z (2017) Integrated display and simulation for automatic dependent surveillance-broadcast and traffic collision avoidance system data fusion. Sensors 17(11):2611

    Article  Google Scholar 

  10. Ding C, Xu J, Xu L (2013) ISHM-based intelligent fusion prognostics for space avionics. Dialogues Cardiovasc Med Dcm 29(1):200–205

    Google Scholar 

  11. Shen X, Bai Y (2014) Architectural considerations in integrated modular avionics (IMA) system safety case construction. IEEE Aerosp Electron Syst Mag 29(10):26–33

    Article  Google Scholar 

  12. An X (2012) Safety-centered architecture design method for IMA software. Comput Sci 39(3):128

    Google Scholar 

  13. Cai Y, Wang Z, Ou X, Zhu L (2011) Approach civil integrated modular avionics airworthiness certification by iterative incremental certification process. In: International conference on information science and engineering, pp 148–151

  14. Ericson CA (2005) Hazard analysis techniques for system safety. Wiley, Hoboken

    Book  Google Scholar 

  15. Deng Zili (2005) Optimal estimation theory with application: modeling, filtering, information fusion estimation, Chap. 6. Harbin Institute of Technology Press, Harbin, pp 377–385

    Google Scholar 

Download references

Acknowledgements

This paper is sponsored by National Program on Key Basic Research Project (2014CB744903), National Natural Science Foundation of China (61673270), Shanghai Pujiang Program (16PJD028), Shanghai Industrial Strengthening Project (GYQJ-2017-5-08), Shanghai Science and Technology Committee Research Project (17DZ1204304) and Shanghai Engineering Research Center of Civil Aircraft Flight Testing.

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Correspondence to Yanran Wang.

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Xiao, G., Wang, Y. & He, F. Research on safety modeling and analysis in information fusion system. AS 2, 51–60 (2019). https://doi.org/10.1007/s42401-018-0011-2

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  • DOI: https://doi.org/10.1007/s42401-018-0011-2

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