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基于Bootstrap的正弦波频率估计可信性评估

Credibility Evaluation for Frequency Estimate of Sinusoid Based on Bootstrap Method
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摘要 研究了正弦波频率估计结果的可信性评估问题,提出一种基于Bootstrap非经典统计分析的评估算法。根据频率估计结果构造参考信号,并与观测信号作相关累加。以全长度相关累加模值与半长度相关累加模值的比作为检验统计量,基于Bootstrap方法确定相应的判决门限,完成对单次正弦波频率估计的可信性校验。仿真结果表明,本算法可在较低信噪比条件下对单次正弦波频率估计结果是否可靠进行评估和判决。 Based on Bootstrap technique,a reliability test method to evaluate the frequency estimation of the sinusoid is proposed in this paper. The reference signal is generated depending on the frequency estimation of the sinusoid at first. Then the correlations between the received signal and the reference signal were calculated. The test statistic is defined by the ratio of the correlation between the whole samples and the half size samples. The reliability test for frequency estimate of the sinusoid signal is performed by the proposed statistic and threshold based on Bootstrap technique. Simulafion results show that the proposed method can be used to verify the reliability for blind frequency estimation of the sinusoid at low signal-to-noise ratio.
出处 《电子器件》 CAS 北大核心 2016年第6期1375-1380,共6页 Chinese Journal of Electron Devices
基金 南京信息职业技术学院科研基金项目(YK20140103) 江苏省自然科学基金项目(BK20160114) 江苏省六大人才高峰第十二批次高层次人才项目(DZXX022) 江苏高校品牌专业建设工程项目(PPZY2015C242)
关键词 正弦波频率估计 可信性评估 BOOTSTRAP方法 相关累加 sinusoid frequency estimation credibility evaluation Bootstrap method correlation and accumulation
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  • 1邓振淼,刘渝,王志忠.正弦波频率估计的修正Rife算法[J].数据采集与处理,2006,21(4):473-477. 被引量:94
  • 2邓振淼,刘渝.正弦波频率估计的牛顿迭代方法初始值研究[J].电子学报,2007,35(1):104-107. 被引量:56
  • 3W Su J A K, Y Ming. Dual-use of modulation recognition tech- niques for digital communication signals[ A]. Systems, Applica- tions and Technology Conference [ C ]. Long Island, NY: IEEE Press, 2006.1 - 6.
  • 4Pucker L. Review of contemporary spectrum sensing technolo- gies ( IEEFSA P1900. 6 Standards Group) [ OL ]. http:// grouper, ieee. org/groups/scc41/6/documents/white papers/ P1900.6 _ Sensor_ Survey. pdf, 2009.
  • 5Fehske A, Gaeddert J, Reed J H. A new approach to signal classification using spectral correlation and neural networks [ A]. 2005 First mEE International Symposium on New Fron- tiers in Dynamic Spectrum Access Networks [ C ]. Baltimore, MD: IEEE Press,2005. 144 - 150.
  • 6Lin W S, Liu K J R. Modulation forensics for wireless digital communications[ A]. IEEE International Conference on Acous- tics, Speech and Signal Processing [ C ]. Las Vegas, NV: IEEE Press,2008. 1789 - 1792.
  • 7Shimon Peleg, Porat B. Linear FM signal parameter estimation from discrete-time observations [ J ]. IEEE Transactions onAerospace and Electronic Systems, 1991,27(4) :607 - 616.
  • 8Whalen A D. Detection of Signals in Noise[ M]. New York: A- cademic Press, 1971.
  • 9Wilfried Gappmai, Roberto L6pez-Valcarce, Mosquera C. Cram6r-Rao lower bound and EM algorithm for envelope- based SNR estimation of noncomtant modulus comtellatiom [ J ]. IEEE Transactions on Communications, 2009, 57 (6) : 1622- 1627.
  • 10Abatzoglou T J. A fast maximum likelihood algorithm for fre- quency estimation of a sinusoid based on Newton "s method [J]. IEEE Transactions on Acoustics, Speech and Signal Processing, 1985,33( 1 ) : 77-89.

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