改进的相位展开算法及其在瞬时频率估计中的应用

 研究了一种改进的相位展开算法及其在瞬时频率估计中的应用.首先讨论了噪声对相位展开的影响,发现当每个周期内的样本数为2个样本时相位展开具有最佳的性能;接着利用这个性质得到一种简单的相位展开算法,可以在较低信噪比条件下估计出信号的瞬时相位;随后把相位展开算法应用于正弦波频率估计,得到了改进的相位平均法,利用它可以在较低信噪比条件下得到宽带信号的瞬时频率曲线;最后通过MATLAB仿真对算法进行验证.     

采用基于多相滤波的数字正交变换技术提取信号瞬时特征的方法

本文研究了通信信号瞬时特征的提取方法。采用中频直接采样、抽取和滤波的方法完成信号的正交分解,从而提取信号的瞬时包络和相位主值序列。利用信号相位去卷叠算法和线性规划法估计信号的去卷叠瞬时非线性相位,利用傅里叶变换的微分特性估计信号的瞬时频率。通过文中的方法可以有效估计信号的瞬时特征,将其运用于信号调制体制识别取得了较好的效果。     

Phase unwrapping via graph cuts.

Phase unwrapping is the inference of absolute phase from modulo-2pi phase. This paper introduces a new energy minimization framework for phase unwrapping. The considered objective functions are first-order Markov random fields. We provide an exact energy minimization algorithm, whenever the corresponding clique potentials are convex, namely for the phase unwrapping classical Lp norm, with p > or = 1. Its complexity is KT (n, 3n), where K is the length of the absolute phase domain measured in 2pi units and T (n, m) is the complexity of a max-flow computation in a graph with n nodes and m edges. For nonconvex clique potentials, often used owing to their discontinuity preserving ability, we face an NP-hard problem for which we devise an approximate solution. Both algorithms solve integer optimization problems by computing a sequence of binary optimizations, each one solved by graph cut techniques. Accordingly, we name the two algorithms PUMA, for phase unwrappping max-flow/min-cut. A set of experimental results illustrates the effectiveness of the proposed approach and its competitiveness in comparison with state-of-the-art phase unwrapping algorithms.     

InSAR相位解缠最小二乘算法的研究

相位解缠是干涉合成孔径雷达（InSAR）测量地形高程的重要步骤之一。由噪声和欠采样导致的相位不一致性问题是相位解缠的难点。本文分析了相位解缠最小二乘算法的原理和性质,总结了算法的优缺点。最后采用加拿大RadarSatl数据进行实验,验证了分析的结果。     

Algebraic multidimensional phase unwrapping and zero distributionof complex polynomials-characterization of multivariate stablepolynomials

We define the multidimensional unwrapped phase for any finite extent multidimensional signal that may have its zero on the distinguished boundary of the unit polydisc. By using this definition, we deduce that multivariate stable polynomials can be simply characterized in terms of the proposed unwrapped phase. A rigorous symbolic algebraic solution to the exact phase unwrapping problem for multidimensional finite extent signals is also proposed. This solution is based on a newly developed general Sturm sequence and does not need any numerical root finding or numerical integration technique. Furthermore, it is shown that the proposed algebraic phase unwrapping algorithm can be used to determine the exact zero distribution of any univariate complex polynomial without suffering the so-called singular case problem     

一种基于UPF的干涉SAR相位展开方法

提出一种不敏粒子滤波的相位展开方法.该方法是不敏粒子滤波器与路径跟踪策略以及全方位的局部相位梯度估计相结合的结果,不受模型噪声统计特性和线性条件约束,同时完成噪声消除和相位展开;利用不敏卡尔曼滤波器来进行粒子更新,使重要密度函数能够融入最新观测信息和更加符合真实状态的后验概率分布,从而提高了相位展开精度与效率.仿真和实...     

基于k值取整的二向剪切相位解包裹算法的研究

针对已有的解包裹算法依旧不能对存在严重欠采样 和较强噪声的包裹相位进行精确解包裹,为了处理受 到噪声污染、严重欠采样的包裹相位图,本文提出了一种基于k值取整二向 剪切的新型相位解包裹算法。 将横向剪切干涉技术和迭代算法进行了改进,得到的新算法,一方面提高了对严重欠采样 包裹相位的处 理能力;另一方面加快了迭代的收敛速度,其所需时间和离散余弦变换(DC T)法接近。在新算法中,引入k值取 整,可以更加精确求解出真实相位,从而提高了新算法的抗噪性能。通过与改进的最小二乘 (LBS)算法进行对比, 新算法的性能优于其它算法。实验结果表明,本文提出的新算法,不仅可以处理严重欠采样 的包裹相位图,还具有很强的抗噪性。     

Parameter Estimation of Phase-Modulated Signals Using Bayesian Unwrapping

Parametric estimation of phase-modulated signals (PMS) in additive white Gaussian noise is considered. The prohibitive computational expense of maximum likelihood estimation for this problem has led to the development of many suboptimal estimators which are relatively inaccurate and cannot operate at low signal-to-noise ratios (SNRs). In this paper, a novel technique based on a probabilistic unwrapping of the phase of the observations is developed. The method is capable of more accurate estimation and operates effectively at much lower SNRs than existing algorithms. This is demonstrated in Monte Carlo simulations.     

On frequency-domain and time-domain phase unwrapping

Time-domain phase unwrapping of analytic or complex functions of time is an unavoidable operation when processing such signals within an FM-modeling framework or when attempting to establish the instantaneous frequency of such signals. With the help of an alternate derivation of his equations, Tribolet's frequency-domain phase unwrapping algorithm is easily rewritten for time-domain application. The time derivative of the argument of the signal, a quantity needed in these modified equations, is developed and furthermore recognized to be proportional to the instantaneous frequency of the signal.     

A novel phase unwrapping method based on network programming

Phase unwrapping is the reconstruction of a function on a grid given its values mod 2π. Phase unwrapping is a key problem in all quantitative applications of synthetic aperture radar (SAR) interferometry, but also in other fields. A new phase unwrapping method, which is a different approach from existing techniques, is described and tested. The method starts from the fact that the phase differences of neighboring pixels can be estimated with a potential error that is an integer multiple of 2π. This suggests the formulation of the phase unwrapping problem as a global minimization problem with integer variables. Recognizing the network structure underlying the problem makes for an efficient solution. In fact, it is possible to equate the phase unwrapping problem to the problem of finding the minimum cost flow on a network, for the solution of which there exist very efficient techniques. The tests performed on real and simulated interferometric SAR data confirm the validity of the approach     

Understanding phase maps in MRI: a new cutline phase unwrapping method

This paper describes phase maps. A review of the phase unwrapping problem is given. Different structures, in particular fringelines, cutlines, and poles, contained within a phase map are described and their origin and behavior investigated. The problem of phase unwrapping can then be addressed with a better understanding of the source of poles or inconsistencies. This understanding, along with some assumptions about what is being encoded in the phase of a magnetic resonance image, are used to derive a new method for phase unwrapping which relies only on the phase map. The method detects cutlines and distinguishes between noise-induced poles and signal undersampling poles based on the length of the fringelines. The method was shown to be robust to noise and successful in unwrapping challenging clinical cases.     

联合到达时间估计的长基线测向相位解模糊算法研究

基线长度是影响测向精度的重要因素.长基线测向精度高,但基线长度大于半波长时会出现相位模糊.现有的相位解模糊算法大多限制了基线长度.本文在多基线比值法解模糊的基础上结合到达时间估计,提出了一种减小了基线长度限制条件的相位解模糊算法来实现长基线窄带信号测向.仿真结果表明,本算法解模糊概率不受基线长度影响,并且针对不同入射角的信号解模糊能力相同,在适当信噪比条件下能通过设置基线长度达到较高的测向精度.     

基于连续干扰消除的毫米波MIMO系统混合预编码算法

该文研究多用户毫米波MIMO系统的混合模数预编码器和合并器设计。针对因信号传播漫散射造成的多用户间信号干扰问题,提出一种基于连续干扰消除(SIC)的鲁棒混合预编码算法。首先对信道矩阵进行正交分解,以消除来自已知用户信号的干扰,从而将含有非凸约束的多用户链路优化问题分解为多个单用户链路优化问题。然后采用相位提取算法逐个求解每个用户的最优传输链路,并结合最小均方误差(MMSE)准则求得多用户混合预编码矩阵。仿真结果表明,与现有的混合预编码算法相比,所提算法在强干扰环境下具有显著的性能优势。

     

Phase difference-based multichannel phase unwrapping.

This work addresses the derivation of the phase difference-based maximum likelihood (ML) phase unwrapping algorithm. To this end, we derive the joint statistics of the phase differences on a two-dimensional grid for the multichannel case, where several scaled wrapped phase values are available. Subsequently, we determine and study the structure of the phase difference-based ML estimator and compare it to known phase unwrapping techniques. This work allows us to frame single and multichannel algorithms in a common formulation. Moreover, among the known single-channel phase difference-based procedures, we identify those attaining an ML solution. We also show that multichannel phase difference-based and, recently proposed, phase-based ML algorithms achieve equivalent solutions.     

数字调制信号识别中的相位去卷叠门限研究

基于瞬时特征提取的数字信号自动识别方法具有重要的应用前景。采用此方法识别信号时,需要提取信号的瞬时幅度、瞬时相位、瞬时频率去计算分类特征参数。但提取信号瞬时相位时会出现相位卷叠现象。本文首先对相位卷叠和相位去卷叠进行了详细的分析,然后提出了一种估计相位去卷叠理论门限范围的方法。而其它相关文献都没对这个门限进行过深入的研究。MATLAB仿真结果表明,采用本文估计出的去卷叠门限范围,可以直接有效地提取信号的非线性瞬时相位。      

Two-Dimensional Polynomial Phase Signals: Parameter Estimation and Bounds

This paper considers the problem of parametric modeling and estimation of nonhomogeneous two-dimensional (2-D) signals. In particular, we focus our study on the class of constant modulus polynomial-phase 2-D nonhomogeneous signals. We present two different phase models and develop computationally efficient estimation algorithms for the parameters of these models. Both algorithms are based on phase differencing operators. The basic properties of the operators are analyzed and used to develop the estimation algorithms. The Cramer-Rao lower bound on the accuracy of jointly estimating the model parameters is derived, for both models. To get further insight on the problem we also derive the asymptotic Cramer-Rao bounds. The performance of the algorithms in the presence of additive white Gaussian noise is illustrated by numerical examples, and compared with the corresponding exact and asymptotic Cramer-Rao bounds. The algorithms are shown to be robust in the presence of noise, and their performance close to the CRB, even at moderate signal to noise ratios.     

精确最小二乘相位解包裹算法

路径无关算法是一类重要的相位解包裹算法,其中最常用的是各种最小二乘算法。由于最小二乘算法无法限制误差在空间中传播,因此不能直接获得精确的解包裹相位,其应用受到了限制。分析最小二乘相位解包裹算法误差的特点,提出了一种能得到精确解包裹相位的新算法,给出了相关的理论分析和具体算法,通过模拟计算和实验验证,证明了该新算法的可行性与有效性。     

The cross-bicepstrum: definition, properties, and application forsimultaneous reconstruction of three nonminimum phase signals

The recovery of three signals from their cross-bispectrum (or the identification of the impulse responses of three parallel linear time-invariant (LTI) systems from the cross-bispectrum of their system outputs) by computing the complex cepstrum of the cross-bispectrum, as long as the signals (or impulse responses) have no zeros on the unit circle, is discussed. It is shown that the three signals can be separated completely and (approximately) recovered in the cross-bicepstrum domain, except for their magnitude and linear phase factors. The computation of the cross-bicepstrum can be seen as a method for the simultaneous computation of the ordinary complex cepstra of three nonminimum-phase signals without the need for phase unwrapping. Both least-squares and fast Fourier-transform (FFT)-based methods for computing the bicepstral coefficients are presented. Simulation examples of signal reconstruction in Gaussian white and nonGaussian colored noise and of system identification are included. The results are extended to nth-order cross-spectra, and the factorization problem for these spectra is discussed     

2-D phase unwrapping and instantaneous frequency estimation

The phase of complex signals is wrapped since it can only be measured modulo-2π; unwrapping searches for the 2π-combinations that minimize the discontinuity of the unwrapped phase, as only the unwrapped phase can be analyzed and interpreted by further processing. Given an estimate of the phase gradient (i.e., of the instantaneous frequency), the 2-D unwrapped phase can be obtained as a solution of a variational problem. The analysis of unwrapping is done quite separately from instantaneous frequency estimation so that the reliability of both steps can be assessed independently. Various methods for evaluating 2-D instantaneous frequency are presented and compared in the presence of noise and amplitude variations. A study has also been made on aliasing arising in areas where, with respect to instantaneous frequency, spatial sampling is insufficient. The presence of noise in the data further complicates phase aliasing analysis since there is no way to distinguish between the aliasing due to noise or that due to steep phase slopes     

A Particle Filter Approach for InSAR Phase Filtering and Unwrapping

This paper presents a new phase-unwrapping (PU) algorithm for SAR interferometry that makes use of a particle filter (PF) to perform simultaneously noise filtering and PU. The formulation of this technique provides independence from noise statistics and is not constrained by the nonlinearity of the problem. In addition, an enhanced variant of this method combining a PF with artificial-intelligence search strategies and an omnidirectional local phase estimator, based on the mode of the power spectral density, is also presented. Results obtained with synthetic and real data show a significant improvement with respect to other conventional unwrapping algorithms in some situations.