[1]邵堃,雷迎科.基于相关滤波和离散度分析的帧同步识别[J].探测与控制学报,2019,41(04):78.[doi:.]
 SHAO Kun,LEI Yingke.Frame Synchronization Recognition Based on Relativity Filter and Dispersion Analysis[J].,2019,41(04):78.[doi:.]
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基于相关滤波和离散度分析的帧同步识别()
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《探测与控制学报》[ISSN:1008-1194/CN:61-1316/TJ]

卷:
41
期数:
2019年04
页码:
78
栏目:
出版日期:
2019-08-26

文章信息/Info

Title:
Frame Synchronization Recognition Based on Relativity Filter and Dispersion Analysis
文章编号:
1008-1194(2019)04-0078-06
作者:
邵堃雷迎科
国防科技大学电子对抗学院, 安徽 合肥 230037
Author(s):
SHAO Kun LEI Yingke
Electronic Countermeasure Institute,National University of Defense Technology, Hefei 230037, China
关键词:
信息处理技术帧同步码识别相关滤波离散度分析
Keywords:
information processing frame synchronization codes recognition relativity filtering dispersion analysis
分类号:
TN911
DOI:
.
文献标志码:
A
摘要:
针对帧同步识别方法中门限选择难度大的问题和对与固定字段直接相连的同步码识别精度低的问题,提出了基于相关滤波和离散度分析的帧同步识别方法。该方法首先通过构造填充矩阵,初步消除冗余数据对帧长识别的影响;然后利用三次相关滤波自适应地调整门限值,完成帧长的识别;之后利用相关值提取关键字段;最后通过离散度分析方法将同步码与固定字段分割开,完成对同步码的精确识别。仿真结果表明,该方法在保证较高的检测概率的同时可以降低门限选择的要求,并且可以准确识别与固定字段连接的同步码。
Abstract:
To solve the problem of difficult threshold selection in the frame synchronization recognition method and the problem of low accuracy in the frame synchronization recognition when the frame synchronization code is directly connected to the fixed word, a frame synchronization recognition based on relativity filter and dispersion analysis was proposed. Firstly, the interference of redundant data on frame length recognition was eliminated by constructing a filling matrix. Then the threshold value was adjusted adaptively by the third relativity filter to realize the recognition of frame length. After that, key word were extracted with relevant values. Finally, the synchronization code was separated from the fixed word by the method of dispersion analysis to realize the accurate identification of the synchronization code. The simulation results showed that this method could reduce the requirement of threshold selection while ensuring a high detection probability, and could accurately identify the synchronization codes connected with fixed word.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-02-27
作者简介:邵堃(1994—),男,山东海阳人,硕士研究生,研究方向:新型数据链通信。E-mail:602212601@qq.com。
更新日期/Last Update: 2019-09-12