摘要
针对低信噪比环境下突发信号检测性能较差的问题,提出了一种基于功率谱倒谱的突发信号的检测方法.该方法首先采用倒谱的最大值作为检验统计量,并利用平滑窗对检验统计量进行平滑;然后,用K均值聚类算法对其分类判决,以区分出信号和噪声;最后,利用基于长度的三态转换给判定结果修正.仿真结果表明,在低信噪比环境下,所提方法具有较好的检测性能和较低的计算复杂度.
A detection method for the burst signal based on the eepstrum of the power spectrum is proposed to solve the problem of the poor burst signal detection performance in the low SNR environment. First, the maximum value of the spectrum is used as the test statistic and is smoothed by the smooth window. Then, the K-mean clustering algorithm is used to classify the decision to distinguish the signal and the noise. Finally, the detection of the burst signal is completed by the three-state transition based on the length. Simulation results show that the proposed method has a better detection performance and lower computational complexity in low SNR environments.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2016年第6期164-169,共6页
Journal of Xidian University
基金
陕西省工业科技攻关资助项目(2014K05-59)
中央高校基本科研业务费专项资金资助项目(2014G2320006
310832151089)
国家自然科学基金资助项目(61501348)
东南大学移动通信国家重点实验室开放课题资助项目(2015D01)
关键词
突发信号
信号检测
倒谱
K均值聚类
三态转换
burst signal
signal detection
cepstrum
K-mean clustering
tristate conversion
