TemporalSpatial Sequential Fusion Recognition Method of
 Ballistic Missile Target Based on MIMOFNN Model

doi:10.16183/j.cnki.jsjtu.2017.09.018

Abstract

Abstract: In traditional temporalspatial sequential fusion recognition method of ballistic missile (BM) target, there always exits the problem that the efficiency is low and the antinoise performance is bad. In order to solve these difficulties, this paper proposed a fusion recognition method which is called temporalspatial sequential fusion recognition method of BM target based on multiple input multiple output and fuzzy neural network (MIMOFNN) model. In this model, firstly, we use the idea of multi layer fusion, combine with neural network and fuzzy theory, and put forward the MIMOFNN model with multi sensors of multi features. And then, we reintegrate the results of present moment and next moment to get the fusion results. Meanwhile, we compare with recognition threshold, until the fusion results match the recognition threshold, and the process of fusion ends. Finally, the experiment validates the effectiveness and antinoise performance of this model.

Key words: , multiple input multiple output (MIMO), fuzzy neural network (FNN), ballistic missile (BM), temporalspatial sequential fusion, target recognition

CLC Number:

TN 95

LI Changxi1,2,ZHOU Yan1,LIN Han3,LI Lingzhi1,GUO Ge1. TemporalSpatial Sequential Fusion Recognition Method of
Ballistic Missile Target Based on MIMOFNN Model[J]. Journal of Shanghai Jiaotong University, 2017, 51(9): 1138-.

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