论文标题
使用子空间Nevanlinna Pick插值设计离散时间矩阵全通滤波器的设计
Design of Discrete-time Matrix All-Pass Filters Using Subspace Nevanlinna Pick Interpolation
论文作者
论文摘要
频率的单位矩阵值函数是矩阵全通系统,因为它们保留了输入矢量信号的标准。通常,使用其统一的矩阵值频域特征来表示和分析此类系统,尽管获得了矩阵全通系统的合理实现,可以实现紧凑的表示和有效的实现。但是,迄今尚不清楚,一种获得满足某些频率时满足相位约束的矩阵全通滤波器的方法。在本文中,我们提出了一种插值策略,以从离散时间矩阵全通系统的频域约束中获得有理矩阵值传输函数。使用子空间Nevanlinna挑选插值问题的扩展(SNIP),我们设计了一个满足所需相特征的离散时间矩阵全通系统的结构。使这是剪切到边界案例的延伸的创新,以获取矩阵全通滤波器的有效时间域实现,作为矩阵线性恒定系数差差方程,这是由有理(可实现的)矩阵传输函数促进的。我们还表明,可以优化与在插值点处的组延迟相关的矩阵相约束的导数,以在未指定的频率下控制全通传输矩阵。仿真表明,统一矩阵滤波器设计的提出的技术以及基于传统的DFT插值方法(包括地球插值)和流行的基于Givens旋转的基于Givens旋转的矩阵参数化。
Unitary matrix-valued functions of frequency are matrix all-pass systems, since they preserve the norm of the input vector signals. Typically, such systems are represented and analyzed using their unitary-matrix valued frequency domain characteristics, although obtaining rational realizations for matrix all-pass systems enables compact representations and efficient implementations. However, an approach to obtain matrix all-pass filters that satisfy phase constraints at certain frequencies was hitherto unknown. In this paper, we present an interpolation strategy to obtain a rational matrix-valued transfer function from frequency domain constraints for discrete-time matrix all-pass systems. Using an extension of the Subspace Nevanlinna Pick Interpolation Problem (SNIP), we design a construction for discrete-time matrix all-pass systems that satisfy the desired phase characteristics. An innovation that enables this is the extension of the SNIP to the boundary case to obtain efficient time-domain implementations of matrix all-pass filters as matrix linear constant coefficient difference equations, facilitated by a rational (realizable) matrix transfer function. We also show that the derivative of matrix phase constraints, related to the group delay at the interpolating points, can be optimized to control the all-pass transfer matrices at the unspecified frequencies. Simulations show that the proposed technique for unitary matrix filter design performs as well as traditional DFT based interpolation approaches, including Geodesic interpolation and the popular Givens rotation based matrix parameterization.