[1]陈恩庆,相小强,穆晓敏..基于压缩感知的MIMO-OFDM系统稀疏信道估计算法[J].郑州大学学报(工学版),2013,34(06):6-9,19.[doi:10.3969/j.issn.1671-6833.2013.06.002]
　ZHANGZhen,LI Dan-dan.An Adaptive DoubleThresholds Algorithm of Detecting Moving Objects[J].Journal of Zhengzhou University (Engineering Science),2013,34(06):6-9,19.[doi:10.3969/j.issn.1671-6833.2013.06.002]

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基于压缩感知的MIMO-OFDM系统稀疏信道估计算法()

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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

34卷

期数:

2013年06期

页码:

6-9,19

栏目:

出版日期:

2013-12-30

文章信息/Info

Title:

An Adaptive DoubleThresholds Algorithm of Detecting Moving Objects

作者:

陈恩庆; 相小强; 穆晓敏.

郑州大学信息工程学院,河南郑州,450001, 郑州大学信息工程学院,河南郑州,450001, 郑州大学信息工程学院,河南郑州,450001

Author(s):

ZHANGZhen; LI Dan-dan

School of Electrical Engineering，Zhengzhou University，Zhengzhou 450001，China

关键词:

无线通信系统;  稀疏信道估计;  压缩感知;  多输入多输出;  正交频分复用

Keywords:

double thresholds; motion object mask; functional chain neural network; moving object detection

分类号:

TN911.23

DOI:

10.3969/j.issn.1671-6833.2013.06.002

文献标志码:

A

摘要:

传统的多输入多输出-正交频分复用(MIMO-OFDM)无线通信系统信道估计算法,没有充分利用无线信道时域的固有稀疏性,导致估计精度不高且频谱利用率低等问题,在信道时域稀疏的前提下,研究了基于压缩感知的MIMO-OFDM系统信道估计算法,详细介绍了正交匹配追踪(OMP)和子空间追踪(SP)两种压缩感知算法原理和步骤,并同其它常用信道估计算法进行了比较分析.理论分析与仿真表明,所提出的压缩感知信道估计算法在频谱利用率以及估计性能方面比传统方法有显著提高,更具有效性.

Abstract:

Due to the environmental change of the noise，different weather conditions andillumination，which influence the results of movingobject detection，thispaperproposed an adaptive double thresholds motionobiect mask algorithm．Toimprove the rate of motive vehicle recognition，this novel method first used multiple’ frame average algorithm to initialize the background，and adopted functional chain neural network method to uDdate thetwoof high andlow thresholds dynamically，which can adjust to changeable illumination automatic‘ 1y．According to the motion mask algorithm，the region of the foreground and background wasidentified and the currentbackgroundwasupdated．Then the region of the foreground object could be attained by dynamic double thresholds background difference method．Combined with the mathematical morphology method，much shadowwasdeleted and the foregroundobject wasrecognized correctly．The experimental results demonstrated that this detectingalgorithmwasmore accurate and robust．

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