Using Time-Varying AR (TVAR) model and adaptive notch filter is a new method for the non-stationary jammer suppression in Direct Sequence Spread Spectrum (DSSS). The performance of TVAR model for Instantaneous Frequen...Using Time-Varying AR (TVAR) model and adaptive notch filter is a new method for the non-stationary jammer suppression in Direct Sequence Spread Spectrum (DSSS). The performance of TVAR model for Instantaneous Frequency (IF) estimation will be affected by some factors such as basis functions. Focusing on this problem, the optimal basis function of TVAR model for the IF estimation of the LFM signal is obtained in this paper. Besides the depth and width of notching, the phase properties of notch filter affect the Signal-to-Interference plus-Noise Ratio (SINR) of correlation output to the narrowband jammer suppression in DSSS, in response to the problem the closed solution of correlation output SINR improvement has been derived when a single frequency jammer passes through direct IIR notch filter, and its performance has been compared with those of five coefficient FIR filters. Later, a novel method for LFM jammer suppression based on Fourier basis TVAR model and direct IIR notch filter is proposed. The simulation results show the effectiveness of the proposed method.展开更多
针对现有的时变自回归(Time-Varying Autoregressive,TVAR)模型应用于滚动轴承故障诊断中的问题,提出一种前向估计与后向估计相结合的改进模型。该模型在引入时变遗忘因子的基础上,定义了前后向联合估计的均方误差并对基函数的加权系数...针对现有的时变自回归(Time-Varying Autoregressive,TVAR)模型应用于滚动轴承故障诊断中的问题,提出一种前向估计与后向估计相结合的改进模型。该模型在引入时变遗忘因子的基础上,定义了前后向联合估计的均方误差并对基函数的加权系数求偏导,得到加权系数的计算公式,然后利用递推最小二乘(Recursive Least Squares,RLS)方法推导了该计算公式的递推形式。针对滚动轴承内圈故障的仿真和实验信号,使用改进前后的模型进行时频分析。仿真和实验结果表明,改进后的模型有效地克服了现有模型无法获得初始时刻频率估计的缺点,具有更高的时频估计精度、更强的抗噪声能力,能够更加有效地提取滚动轴承的故障特征频率。展开更多
基金Supported by the Natural Science Foundation of Hebei Province (F2010000442)
文摘Using Time-Varying AR (TVAR) model and adaptive notch filter is a new method for the non-stationary jammer suppression in Direct Sequence Spread Spectrum (DSSS). The performance of TVAR model for Instantaneous Frequency (IF) estimation will be affected by some factors such as basis functions. Focusing on this problem, the optimal basis function of TVAR model for the IF estimation of the LFM signal is obtained in this paper. Besides the depth and width of notching, the phase properties of notch filter affect the Signal-to-Interference plus-Noise Ratio (SINR) of correlation output to the narrowband jammer suppression in DSSS, in response to the problem the closed solution of correlation output SINR improvement has been derived when a single frequency jammer passes through direct IIR notch filter, and its performance has been compared with those of five coefficient FIR filters. Later, a novel method for LFM jammer suppression based on Fourier basis TVAR model and direct IIR notch filter is proposed. The simulation results show the effectiveness of the proposed method.
文摘针对现有的时变自回归(Time-Varying Autoregressive,TVAR)模型应用于滚动轴承故障诊断中的问题,提出一种前向估计与后向估计相结合的改进模型。该模型在引入时变遗忘因子的基础上,定义了前后向联合估计的均方误差并对基函数的加权系数求偏导,得到加权系数的计算公式,然后利用递推最小二乘(Recursive Least Squares,RLS)方法推导了该计算公式的递推形式。针对滚动轴承内圈故障的仿真和实验信号,使用改进前后的模型进行时频分析。仿真和实验结果表明,改进后的模型有效地克服了现有模型无法获得初始时刻频率估计的缺点,具有更高的时频估计精度、更强的抗噪声能力,能够更加有效地提取滚动轴承的故障特征频率。
