针对载频重频联合捷变体制雷达目标参数估计问题,提出了一种新的基于多重信号分类(multiple signal classification,MUSIC)算法的载频重频联合捷变雷达目标参数估计方法。通过信号模型的空时等效,将时域信号的处理等效成空域阵列信号的...针对载频重频联合捷变体制雷达目标参数估计问题,提出了一种新的基于多重信号分类(multiple signal classification,MUSIC)算法的载频重频联合捷变雷达目标参数估计方法。通过信号模型的空时等效,将时域信号的处理等效成空域阵列信号的处理,并将超分辨阵列信号处理方法应用到目标的参数估计中,从而把目标距离和速度的估计等效成阵列中二维参数的估计,解决了由于载频重频联合捷变所带来的目标参数估计难题。仿真实验表明,所提方法能有效实现对目标距离和速度的超分辨估计。展开更多
将最小方差无畸变响应(minimum variance distortionless response,MVDR)自适应波束形成方法拓展到一类非平稳脉冲信号,利用时域MVDR(time-domain MVDR,TMVDR)实现了单Chirp脉冲信号的自适应波束形成,即CTMVDR(TMVDR on single Chirp pu...将最小方差无畸变响应(minimum variance distortionless response,MVDR)自适应波束形成方法拓展到一类非平稳脉冲信号,利用时域MVDR(time-domain MVDR,TMVDR)实现了单Chirp脉冲信号的自适应波束形成,即CTMVDR(TMVDR on single Chirp pulse signal,CTMVDR)。CTMVDR可估计具有常数幅值的未知Chirp脉冲信号的波达方向(direction of arrival,DOA)、信号功率和时间波形。理论分析结果表明,稳定估计自适应权向量的条件是稳定估计Chirp脉冲时间序列的自相关。数值仿真和海上实验结果表明,在采样频率不大于10倍Nyquist频率条件下,只需少于1 024个采样点,即可获得稳定的自适应权向量估计;和常规波束形成对比,CTMVDR有更好的波束响应、DOA估计、阵处理增益和Chirp脉冲信号的时间波形估计性能。展开更多
为了降低信号的采样速率,减少采集数据量,针对非严格有限新息率(Finite Rate of Innovation,FRI)信号,提出了一种基于Hilbert变换的超声脉冲信号FRI采样方法。将脉冲超声检测信号通过Hilbert变换解包络,形成具有有限新息率的脉冲信号,...为了降低信号的采样速率,减少采集数据量,针对非严格有限新息率(Finite Rate of Innovation,FRI)信号,提出了一种基于Hilbert变换的超声脉冲信号FRI采样方法。将脉冲超声检测信号通过Hilbert变换解包络,形成具有有限新息率的脉冲信号,利用低速采样系统实现了脉冲超声检测信号的低速采样。通过零化滤波器方法从低速采样信号中解算出了脉冲超声检测信号的峰值时刻点,实现了对检测信号的参数估计。通过加入加性高斯白噪声验证了该采样方法对噪声的适应能力。试验结果表明,该低速采样方法可减少信号的采集数据量,并准确估计出峰值到达时刻点。展开更多
The machinery fault signal is a typical non-Gaussian and non-stationary process. The fault signal can be described by SaS distribution model because of the presence of impulses.Time-frequency distribution is a useful ...The machinery fault signal is a typical non-Gaussian and non-stationary process. The fault signal can be described by SaS distribution model because of the presence of impulses.Time-frequency distribution is a useful tool to extract helpful information of the machinery fault signal. Various fractional lower order(FLO) time-frequency distribution methods have been proposed based on fractional lower order statistics, which include fractional lower order short time Fourier transform(FLO-STFT), fractional lower order Wigner-Ville distributions(FLO-WVDs), fractional lower order Cohen class time-frequency distributions(FLO-CDs), fractional lower order adaptive kernel time-frequency distributions(FLO-AKDs) and adaptive fractional lower order time-frequency auto-regressive moving average(FLO-TFARMA) model time-frequency representation method.The methods and the exiting methods based on second order statistics in SaS distribution environments are compared, simulation results show that the new methods have better performances than the existing methods. The advantages and disadvantages of the improved time-frequency methods have been summarized.Last, the new methods are applied to analyze the outer race fault signals, the results illustrate their good performances.展开更多
文摘针对载频重频联合捷变体制雷达目标参数估计问题,提出了一种新的基于多重信号分类(multiple signal classification,MUSIC)算法的载频重频联合捷变雷达目标参数估计方法。通过信号模型的空时等效,将时域信号的处理等效成空域阵列信号的处理,并将超分辨阵列信号处理方法应用到目标的参数估计中,从而把目标距离和速度的估计等效成阵列中二维参数的估计,解决了由于载频重频联合捷变所带来的目标参数估计难题。仿真实验表明,所提方法能有效实现对目标距离和速度的超分辨估计。
文摘将最小方差无畸变响应(minimum variance distortionless response,MVDR)自适应波束形成方法拓展到一类非平稳脉冲信号,利用时域MVDR(time-domain MVDR,TMVDR)实现了单Chirp脉冲信号的自适应波束形成,即CTMVDR(TMVDR on single Chirp pulse signal,CTMVDR)。CTMVDR可估计具有常数幅值的未知Chirp脉冲信号的波达方向(direction of arrival,DOA)、信号功率和时间波形。理论分析结果表明,稳定估计自适应权向量的条件是稳定估计Chirp脉冲时间序列的自相关。数值仿真和海上实验结果表明,在采样频率不大于10倍Nyquist频率条件下,只需少于1 024个采样点,即可获得稳定的自适应权向量估计;和常规波束形成对比,CTMVDR有更好的波束响应、DOA估计、阵处理增益和Chirp脉冲信号的时间波形估计性能。
文摘为了降低信号的采样速率,减少采集数据量,针对非严格有限新息率(Finite Rate of Innovation,FRI)信号,提出了一种基于Hilbert变换的超声脉冲信号FRI采样方法。将脉冲超声检测信号通过Hilbert变换解包络,形成具有有限新息率的脉冲信号,利用低速采样系统实现了脉冲超声检测信号的低速采样。通过零化滤波器方法从低速采样信号中解算出了脉冲超声检测信号的峰值时刻点,实现了对检测信号的参数估计。通过加入加性高斯白噪声验证了该采样方法对噪声的适应能力。试验结果表明,该低速采样方法可减少信号的采集数据量,并准确估计出峰值到达时刻点。
基金supported by the National Natural Science Foundation of China(61261046,61362038)the Natural Science Foundation of Jiangxi Province(20142BAB207006,20151BAB207013)+2 种基金the Science and Technology Project of Provincial Education Department of Jiangxi Province(GJJ14738,GJJ14739)the Research Foundation of Health Department of Jiangxi Province(20175561)the Science and Technology Project of Jiujiang University(2016KJ001,2016KJ002)
文摘The machinery fault signal is a typical non-Gaussian and non-stationary process. The fault signal can be described by SaS distribution model because of the presence of impulses.Time-frequency distribution is a useful tool to extract helpful information of the machinery fault signal. Various fractional lower order(FLO) time-frequency distribution methods have been proposed based on fractional lower order statistics, which include fractional lower order short time Fourier transform(FLO-STFT), fractional lower order Wigner-Ville distributions(FLO-WVDs), fractional lower order Cohen class time-frequency distributions(FLO-CDs), fractional lower order adaptive kernel time-frequency distributions(FLO-AKDs) and adaptive fractional lower order time-frequency auto-regressive moving average(FLO-TFARMA) model time-frequency representation method.The methods and the exiting methods based on second order statistics in SaS distribution environments are compared, simulation results show that the new methods have better performances than the existing methods. The advantages and disadvantages of the improved time-frequency methods have been summarized.Last, the new methods are applied to analyze the outer race fault signals, the results illustrate their good performances.
