传统的线性主动噪声控制算法在噪声信号或噪声通道呈现非线性特性的情况下控制效果不佳。核-滤波最小均方误差算法(Kernel Filtered x Least Mean Square,KFxLMS)通过将输入噪声信号映射到高维再生核希尔伯特空间,再用线性方法在高维空...传统的线性主动噪声控制算法在噪声信号或噪声通道呈现非线性特性的情况下控制效果不佳。核-滤波最小均方误差算法(Kernel Filtered x Least Mean Square,KFxLMS)通过将输入噪声信号映射到高维再生核希尔伯特空间,再用线性方法在高维空间中进行处理。然而,随着新噪声信号的输入,KFxLMS算法递增的核函数运算需要较高的成本。为进一步改进KFxLMS算法,本文提出了随机傅里叶特征核滤波最小均方误差算法(Random Fourier Feature-Kernel Filtered x Least Mean Square,RFF-KFxLMS)。在仿真实验部分讨论了算法的参数选择,给出了算法的计算耗时,并验证了提出的RFF-KFxLMS算法在非线性噪声通道情况下,针对不同频率分量的正弦噪声都能够达到理想的性能。展开更多
当MIMO-OFDM(Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing)系统工作于频率选择性快衰落信道时,子载波正交性会受到破坏从而引入子载波间干扰(Inter-Carrier Interference:ICI).ICI的存在将严重降低那...当MIMO-OFDM(Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing)系统工作于频率选择性快衰落信道时,子载波正交性会受到破坏从而引入子载波间干扰(Inter-Carrier Interference:ICI).ICI的存在将严重降低那些传统的用于检测准静止频率选择性衰落信道下MIMO-OFDM的检测算法的性能.本文将Schniter针对SISO (Single Input Single Output)OFDM系统提出的最优线性预处理扩展到MIMO-OFDM系统,基于这个信号模型推广了基于最小均方误差滤波的迭代软判决干扰抵消(Minimum Mean Square Error filtering based Iterative Soft'Decision Interference Can- cellation:MMSE-ISDIC)逐符号检测算法,同时提出一种基于准最大后验概率准则的迭代软判决干扰抵消(quasi-maximum A posteriori probability based ISDIC:quasi-MAP-ISDIC)联合检测算法.仿真结果表明在本文考虑的系统参数设定下这两种检测算法的性能均优于文献[8]中算法的性能,其中quasi-MAP-ISDIC检测算法能够获得接近基于理想ICI抵消的MAP检测算法的性能.展开更多
New sigma point filtering algorithms, including the unscented Kalman filter （UKF） and the divided difference filter （DDF）, are designed to solve the nonlinear filtering problem under the condition of correlated no...New sigma point filtering algorithms, including the unscented Kalman filter （UKF） and the divided difference filter （DDF）, are designed to solve the nonlinear filtering problem under the condition of correlated noises. Based on the minimum mean square error estimation theory, the nonlinear optimal predictive and correction recursive formulas under the hypothesis that the input noise is correlated with the measurement noise are derived and can be described in a unified framework. Then, UKF and DDF with correlated noises are proposed on the basis of approximation of the posterior mean and covariance in the unified framework by using unscented transformation and second order Stirling＇s interpolation. The proposed UKF and DDF with correlated noises break through the limitation that input noise and measurement noise must be assumed to be uneorrelated in standard UKF and DDF. Two simulation examples show the effectiveness and feasibility of new algorithms for dealing with nonlinear filtering issue with correlated noises.展开更多
文摘传统的线性主动噪声控制算法在噪声信号或噪声通道呈现非线性特性的情况下控制效果不佳。核-滤波最小均方误差算法(Kernel Filtered x Least Mean Square,KFxLMS)通过将输入噪声信号映射到高维再生核希尔伯特空间,再用线性方法在高维空间中进行处理。然而,随着新噪声信号的输入,KFxLMS算法递增的核函数运算需要较高的成本。为进一步改进KFxLMS算法,本文提出了随机傅里叶特征核滤波最小均方误差算法(Random Fourier Feature-Kernel Filtered x Least Mean Square,RFF-KFxLMS)。在仿真实验部分讨论了算法的参数选择,给出了算法的计算耗时,并验证了提出的RFF-KFxLMS算法在非线性噪声通道情况下,针对不同频率分量的正弦噪声都能够达到理想的性能。
文摘当MIMO-OFDM(Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing)系统工作于频率选择性快衰落信道时,子载波正交性会受到破坏从而引入子载波间干扰(Inter-Carrier Interference:ICI).ICI的存在将严重降低那些传统的用于检测准静止频率选择性衰落信道下MIMO-OFDM的检测算法的性能.本文将Schniter针对SISO (Single Input Single Output)OFDM系统提出的最优线性预处理扩展到MIMO-OFDM系统,基于这个信号模型推广了基于最小均方误差滤波的迭代软判决干扰抵消(Minimum Mean Square Error filtering based Iterative Soft'Decision Interference Can- cellation:MMSE-ISDIC)逐符号检测算法,同时提出一种基于准最大后验概率准则的迭代软判决干扰抵消(quasi-maximum A posteriori probability based ISDIC:quasi-MAP-ISDIC)联合检测算法.仿真结果表明在本文考虑的系统参数设定下这两种检测算法的性能均优于文献[8]中算法的性能,其中quasi-MAP-ISDIC检测算法能够获得接近基于理想ICI抵消的MAP检测算法的性能.
基金Projects(61135001, 61075029, 61074155) supported by the National Natural Science Foundation of ChinaProject(20110491690) supported by the Postdocteral Science Foundation of China
文摘New sigma point filtering algorithms, including the unscented Kalman filter （UKF） and the divided difference filter （DDF）, are designed to solve the nonlinear filtering problem under the condition of correlated noises. Based on the minimum mean square error estimation theory, the nonlinear optimal predictive and correction recursive formulas under the hypothesis that the input noise is correlated with the measurement noise are derived and can be described in a unified framework. Then, UKF and DDF with correlated noises are proposed on the basis of approximation of the posterior mean and covariance in the unified framework by using unscented transformation and second order Stirling＇s interpolation. The proposed UKF and DDF with correlated noises break through the limitation that input noise and measurement noise must be assumed to be uneorrelated in standard UKF and DDF. Two simulation examples show the effectiveness and feasibility of new algorithms for dealing with nonlinear filtering issue with correlated noises.
