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A new combination method for multisensor conflict information

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Abstract

Information fusion is a very important technology which can use multisensor network data to get a better performance than single one; therefore, it is widely used in the filed of target recognition, target tracking, automatic control, decision making and so on. However, because of noise and interference, sometimes the sensors may obtain erroneous, inaccurate or heterogeneous data, which will produce the conflict information among different sensors and get the wrong result after information fusion. In this paper, based on the Dempster–Shafer (D–S) theory, we introduce how to set up the model of multisensor network information fusion. And then, we discuss the problem of conflict information fusion in the framework of evidence and several improved methods are introduced. Finally, based on Mahalanobis distance, an improved solution method is presented. The numerical simulation results prove that this new improved method can get the same result as traditional methods, beyond which it can make a reasonable decision with high conflict information. Therefore, this new improved method can be used in the filed of high noise and interference.

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Acknowledgments

This work was supported by the Key Development Program of Basic Research of China (JCKY2013604B001), the Nation Nature Science Foundation of China (No. 61301095 and No. 61201237), Nature Science Foundation of Heilongjiang Province of China (No. QC2012C069, F201408 and F201407) and the Fundamental Research Funds for the Central Universities (No. HEUCF1508).

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Authors and Affiliations

  1. College of Information and Communication Engineering, Harbin Engineering University, No. 145-1, Nantong Street, Nangang District, Harbin, 150001, Heilongjiang, People’s Republic of China

    Yun Lin, Can Wang & Zheng Dou

  2. College of Computer Science and Technology, Harbin Engineering University, No. 145-1, Nantong Street, Nangang District, Harbin, 150001, Heilongjiang, People’s Republic of China

    Yun Lin & Chunguang Ma

  3. National Key Laboratory of Underwater Acoustic Science and Technology, Harbin Engineering University, No. 145-1, Nantong Street, Nangang District, Harbin, 150001, Heilongjiang, People’s Republic of China

    Xuefei Ma

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  1. Yun Lin
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  2. Can Wang
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  3. Chunguang Ma
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  4. Zheng Dou
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  5. Xuefei Ma
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Correspondence to Xuefei Ma.

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Meantime, all the authors declare that there is no conflict of interests regarding the publication of this article.

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Lin, Y., Wang, C., Ma, C. et al. A new combination method for multisensor conflict information. J Supercomput 72, 2874–2890 (2016). https://doi.org/10.1007/s11227-016-1681-3

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