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

被引：0
|
作者：
Li C. [1 ,2 ]
Zhou Y. [1 ]
Lin H. [3 ]
Li L. [1 ]
Guo G. [1 ]
机构：
[1] Air Force Early Warning Academy, Wuhan
[2] Unit No.66132 of PLA, Beijing
[3] Department of Computer Science, Dongfang College, Fujian Agriculture and Forestry University, Fuzhou
来源：
Zhou, Yan (zhouy@sina.com) | 2017年 / Shanghai Jiaotong University卷 / 51期
关键词：
Ballistic missile (BM); Fuzzy neural network (FNN); Multiple input multiple output (MIMO); Target recognition; Temporal-spatial sequential fusion;
D O I：
10.16183/j.cnki.jsjtu.2017.09.018
中图分类号：
学科分类号：
摘要：
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. © 2017, Shanghai Jiao Tong University Press. All right reserved.
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页码：1138 / 1144
页数：6
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