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[1]王海燕,陈 浩,张兴敢*.基于马尔可夫链的MIMO雷达信号融合检测方法[J].南京大学学报(自然科学),2016,52(5):918.[doi:10.13232/j.cnki.jnju.2016.05.018]
 Wang Haiyan,Chen Hao,Zhang Xinggan*.MIMO radar signal fusion detection method based on Markov chain[J].Journal of Nanjing University(Natural Sciences),2016,52(5):918.[doi:10.13232/j.cnki.jnju.2016.05.018]
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基于马尔可夫链的MIMO雷达信号融合检测方法()
     

《南京大学学报(自然科学)》[ISSN:0469-5097/CN:32-1169/N]

卷:
52
期数:
2016年第5期
页码:
918
栏目:
出版日期:
2016-10-01

文章信息/Info

Title:
MIMO radar signal fusion detection method based on Markov chain
作者:
王海燕陈 浩张兴敢*
南京大学电子科学与工程学院,南京,210023
Author(s):
Wang HaiyanChen HaoZhang Xinggan*
School of Electronics Science and Engineering,Nanjing University,Nanjing,210023,China
关键词:
MIMO雷达非相参积累分布式检测状态转移概率
Keywords:
MIMO radarnon­coherent accumulationdistributed detectionstate transition probability
分类号:
TN957.51
DOI:
10.13232/j.cnki.jnju.2016.05.018
文献标志码:
A
摘要:
MIMO(Multiple­Input Multiple­Output)雷达结合多信号技术和阵列技术的优点,利用空间分集对抗目标RCS闪烁,完成目标检测与跟踪.针对多站雷达信号检测,提出了基于马尔可夫链的非相参积累分布式融合检测方法.首先分析了恒虚警率检测的阈值计算原理,推导出多站数据融合后的二次检测阈值.为改善运用贝叶斯和纽曼-皮尔逊准则检测时运算量大的缺点,提出基于马尔可夫链法的算法.该方法对各站回波数据进行结构化处理,根据不同时刻状态间的统计联系,导入马尔可夫过程,计算出状态转移概率矩阵,逐帧搜索确定目标点迹.仿真实验表明,该算法能够在不提高虚警概率的条件下,明显地降低检测阈值,可以有效提高系统检测性能.
Abstract:
he MIMO radar system consists of a transmit array with widely spaced elements such that each element views a different aspect of the target.The array at the receiver is a conventional array used for direction finding.MIMO radars combine both the advantages of multiple signals technology and the array technology,so as to decrease the influence of target RCS(radar cross­section)scintillation owing to the space diversity when detecting and tracking targets.For target detection of MIMO radars,we put forward a distributed fusion detection method by non­coherent accumulation based on the Markov chain.Firstly,we analyze the calculation principle for the threshold of constant false alarm rate(CFAR)detection,then deduce secondary detection threshold after multiple station data fusion.A fusion detection method based on Markov chain is leveraged toreduce the calculation burden of Bayesian and Newman­Pearson detection,.The proposed method structuralizes the echo data and introduces Markov process to calculate the state transition probability matrix according to the state statistical relationship between the different time,then searches target position by calculating the echo data in sequence.The simulation results show that the proposed algorithm can distinctly improve the detection rate without increasing the false alarm probability.Thus the system detection performance can be effectively improved.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目:毫米波国家重点实验室开放课题(K201514)
收稿日期:2016-03-16
*通讯联系人,E­mail:zhxg@nju.edu.cn
更新日期/Last Update: 2016-09-25