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非合作通信下弱突发信号的双重检测算法 被引量:3

A Dual Detection Algorithm for Weak Burst Signals in Non-cooperative Communication
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摘要 在现代无线通信系统中,通常采用突发通信方式来提高系统抗干扰能力。非合作通信条件下,接收信号的信号类型未知和信噪较低导致检测性能较差。为了改善非合作突发信号检测性能,提出了一种结合双滑窗和延时自相关的双重检测算法,先用能量检测法对序列进行粗检,再用延时自相关进行精检。该能量检测算法是在经典双滑窗能量检测基础上,增加了一个对检测序列进行了延时相加的预处理来提高阈值。实验仿真证实了改进后的检测算法在-7 d B信噪比以上都具有很好的检测性能,并且在噪声数据占比高的突发通信中,运行速度是延时自相关检测的好几倍。因此,在非合作通信中算法具有较好的性能和较高的效率。 In modern wireless communication systems,burst communication is usually used to improve system anti-interference ability.In non-cooperative communication,the unknown signal type of the signal received and the low signal-to-noise ratio(SNR)lead to poor detection performance.In order to improve the performance of non-cooperative burst signal detection,this paper proposes a dual detection algorithm combining double sliding window and delayed self-correlation.The algorithm first uses energy detection method to perform simple detection on the sequence,and then uses delayed self-correlation for detailed examination.Based on the classic double sliding window energy detection,the energy detection algorithm adds a pretreatment which delays and adds the detection sequence to increase the threshold.The experimental simulation shows that the improved detection algorithm has good detection performance above-7 dB SNR,and in burst communication with large amount of noise data,the running speed is several times that of delayed self-correlation detection.Therefore,this algorithm has better performance and higher efficiency in non-cooperative communication.
作者 郭婷莺 陈永锋 刘凯 GUO Tingying;CHEN Yongfeng;LIU Kai(Key Laboratory of Specialty Fiber Optics and Optical Access Networks,Shanghai University,Shanghai 200444,China;Shanghai Branch of Southwest Electronics and Telecommunication Technology Research Institute,Shanghai 200434,China)
出处 《电讯技术》 北大核心 2018年第11期1290-1295,共6页 Telecommunication Engineering
基金 国家自然科学基金资助项目(61501288)
关键词 非合作通信 突发信号 低信噪比 双滑窗能量检测 自相关检测 non-cooperative communication burst signal low SNR double sliding windows energy detection self-correlation detection
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