期刊文献+

非高斯噪声下的信号检测算法与性能分析 被引量:1

Signal Detection Algorithm and Performance Analysis under Non-Gaussian Noise
下载PDF
导出
摘要 为改善非高斯背景噪声下的信号检测性能,提出了采用非线性阈值系统的信号检测算法。该算法首先利用阈值系统对接收信号进行预处理,其次采用最小平均错误概率准则对预处理后的信号进行检测,最后推导了所提检测算法的误码率解析表达式并给出仿真验证。理论分析和仿真结果表明:在高斯背景噪声下,线性最佳检测算法的检测性能优于所提检测算法;在非高斯背景噪声下,所提检测算法的检测性能较线性最佳检测算法有显著提升。 To improve the signal detection performance under non-Gaussian background noise, this paper presents a novel signal detection algorithm based on nonlinear threshold system (NTS). The algorithm firstly uses NTS to preprocess the received signal, then uses the minimum mean error probability rule to detect the preprocessed signals, finally deduces the analytical expression of the bit error ratio (BER) of proposed detection algorithm and gives the simulative validation. Theoreti- cal analysis and simulation results show:under the background of Gaussian noise,the detection per- formance of the linear optimal detection algorithm is better than that of the proposed detection al- gorithm;under the background of non-Gaussian noise,the detection performance of proposed algo- rithm is significantly improved compared with that of linear optimal detection algorithm.
作者 刘进
出处 《舰船电子对抗》 2016年第4期68-72,共5页 Shipboard Electronic Countermeasure
关键词 信号检测 非高斯背景噪声 非线性阈值系统 线性最佳检测算法 signal detection non-Gaussian background noise nonlinear threshold system linear optimal detection algorithm.
  • 相关文献

参考文献9

  • 1MOLISCH A F. Wireless communications[M]. Eng- land : Cambridge University, 2 011.
  • 2齐佩汉,司江勃,李赞,高锐.新型抗噪声不确定度谱分段对消频谱感知算法[J].西安电子科技大学学报,2013,40(6):19-24. 被引量:9
  • 3SHEPELAVEY B. Non-Gaussian atmospheric noise in binary-data, phase-coherent communication systems [J]. IEEE Transactions on Communications Systems, 1963,11(3) :280 - 284.
  • 4BANERJEE S, AGRAWAL M. Underwater acoustic noise with generalized Gaussian statistics: Effects on error performance [ C ]//2013 MTS/IEEE on OCEANS,2013: 1 - 8.
  • 5CHARTRAND R, STANEVA V. Total variation regu- larisation of images corrupted by non-Gaussian noise using a quasi-Newton method [J]. IET Image Process ing,2008,2(6) :295 - 303.
  • 6CHAINAIS P. Towards dictionary learning from ima- ges with non Gaussian noise[C]//2012 IEEE Interna- tional Workshop on Machine Learning for Signal Pro- cessing (MLSP) ,2012:1 - 6.
  • 7MILLER J H. Detectors for discrete-time signals in non Gaussian noise[J].lEEK Transactions on Infor marion Theory,1972,18(2) : 241 - 250.
  • 8SOURY H,YILMAZ F, ALOUINI M S. Average bit error probability of binary coherent signaling over gen- eralized fading channels subject to additive generalized gaussian noise [J]. IEEE Communications Letters, 2012,16 (6) :785 - 788.
  • 9SOURY H, YILMAZ F, ALOUINI M S. Error rates of M PAM and M-QAM in generalized fading and gener alized gaussian noise environments [J]. IEEE Commu- nications Letters,2013,17(10) : 1932 - 1935.

二级参考文献13

  • 1Haykin S. Cognitive Dynamic Systems: Radar, Control, and Radio[J]. Proceedings of the IEEE, 2012, 100(7): 2095- 2103.
  • 2Md Nasimus S. The Performance of an Optimum Digital Matched Filter Detector Using Structured Code Sequences for CDMA Applications[CJ / /Communications on the Move. New York: IEEE, 1992: 949-952.
  • 3Bkassiny M,Jayaweera S K, Li Yang, et al. Blind Cyclostationary Feature Detection Based Spectrum Sensing for Autonomous Self-learning Cognitive Radios[CJ / /IEEE International Conference on Communications. Piscataway: IEEE, 2012: 1507-15l1.
  • 4Zeng Yonghong , Liang Yingchang . Eigenvalue-based Spectrum Sensing Algorithms for Cognitive Radio Source[J] . IEEE Transactions on Communications, 2009, 57(6): 1784-1793.
  • 5Kim K, Xin Yan, Rangarajan S. Energy Detection Based Spectrum Sensing for Cognitive Radio: an Experimental Study[CJI/IEEE Global Telecommunications Conference. New York: IEEE, 2010: 1-5.
  • 6Olabiyi 0, Annamalai A. Analysis and New Implementations of Periodogram-based Spectrum Sensing[CJ 1135th IEEE Sarnoff Symposium. Piscataway: IEEE, 2012: 1-5.
  • 7Gismalla E H. Performance Analysis of the PeriodograrnBased Energy Detector in Fading Channels[J]. IEEE Transactions on Signal Processing, 2011, 59(8): 3712-372l.
  • 8Chen Zhe, Guo Nan, Qiu R C. Demonstration of Real-time Spectrum Sensing for Cognitive Radio[CJ IIProceedings of the IEEE Military Communications Conference. Piscataway: IEEE, 2010: 323-328.
  • 9Digharn F F. On the Energy Detection of Unknown Signals over Fading Channels[J]. IEEE Transactions on Communications, 2007, 55(1): 21-24.
  • 10Zhang Yalin, Zhang Qinyu , Melodia T. A Frequency-domain Entropy-based Detector for Robust Spectrum Sensing in Cognitive Radio Networks[J]. IEEE Communications Letters, 2010, 14(6): 533-535.

共引文献8

同被引文献2

引证文献1

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部