Maximum-likelihood estimator for dual phase extraction in holographic moire

A maximum-likelihood (ML) method based on spectral estimation theory for the extraction of dual phase distributions in holographic moire in the presence of nonsinusoidal waveforms, noise, and the miscalibration of piezoelectric (PZT) devices is proposed. The extraction of these phases requires incorporating two PZTs into the moire setup. ML estimators are asymptotically efficient for sufficient data samples. The approach presented uses a direct stochastic algorithm called probabilistic global search Lausanne for minimizing the ML function.     

A novel approach for characterizing the nonlinear phase steps of the PZT in interferometry

We propose a novel approach to estimate the phase distribution in the presence of nonlinear response of the PZT. The proposed method is an outcome of two different concepts based on the discrete chirp Fourier transform (DCFT) and the maximum-likelihood estimator for the estimation of nonlinear phase step. The robustness of the proposed method is tested for various magnitudes of nonlinearity and harmonics. Comparison of our proposed method with the bench marking algorithm by Hibino et al.'s six and nine sample algorithm in the presence of noise shows that our method is highly efficient.     

Generalized linear prediction method in phase-shifting interferometry in the presence of noise

The effectiveness of phase-shifting interferometry (PSI) techniques employing piezoelectric device PZT in the estimation of phase depends largely on the accuracy with which the phase shifts are imparted to the device and the noise influencing the measurement. Several effective algorithms have been proposed to compute the phase shifts imparted to the device and subsequently obtain the phase using least-squares estimation technique. In this paper, we propose a generalized approach, which accurately estimates the phase shifts in the presence of noise. The method is based on the idea of linear prediction and explores the fact that sampling more data frames yields a reliable phase step estimate in a least-squares sense. We also compare our method with a commonly used generalized phase-shifting method based on histogram analysis and show that our proposed approach is highly effective. We also present simulation and experimental validations of our proposed method.     

Phase-shifting interferometry in the presence of nonlinear phase steps, harmonics, and noise

A phase-shifting piezo device commonly employed in phase-shifting interferometry exhibits a nonlinear response to applied voltage. Hence, a method for estimation of phase distribution in the presence of nonlinear phase steps is presented. The proposed method compensates for the harmonics present in the intensity fringe, allows the use of arbitrary phase-step values between 0 and tau rad, and does not impose constraints on the selection of particular phase-step values for minimizing nonlinearity and compensating for the harmonics. The comparison of the proposed method with other well-known benchmarking algorithms shows that our method is highly efficient and also works well in the presence of noise.     

COmplex-Model-Based Estimation of thermal noise for fMRI data in the presence of artifacts

Due to the presence of artifacts induced by fast-imaging acquisition in functional magnetic resonance imaging (fMRI) studies, it is very difficult to estimate the variance of thermal noise by traditional methods in magnitude images. Moreover, the existence of incidental phase fluctuations impairs the validity of currently available solutions based on complex datasets. In this article, a time-domain model is proposed to generalize the analysis of complex datasets for nonbrain regions by incorporating artifacts and phase fluctuations. Based on this model, a novel estimation schema has been developed to find an appropriate set of voxels in nonbrain regions according to their levels of artifact and phase fluctuation. In addition, noise intensity from these voxels is estimated. The whole schema is named COmplex-Model-Based Estimation (COMBE). Theoretical and experimental results demonstrate that the proposed COMBE method provides a better estimation of thermal noise in fMRI studies compared with previously proposed methods and suggest that the new method can adapt to a broader range of applications, such as functional connectivity studies, evaluation of sequence designs and reconstruction schemas.     

Parameter estimation of optical fringes with quadratic phase using the fractional Fourier transform

Optical fringes with a quadratic phase are often encountered in optical metrology. Parameter estimation of such fringes plays an important role in interferometric measurements. A novel method is proposed for accurate and direct parameter estimation using the fractional Fourier transform (FRFT), even in the presence of noise and obstacles. We take Newton׳s rings fringe patterns and electronic speckle pattern interferometry (ESPI) interferograms as classic examples of optical fringes that have a quadratic phase and present simulation and experimental results demonstrating the performance of the proposed method.     

Maximum likelihood estimation of direction of arrival using an acoustic vector-sensor

A vector-sensor consisting of a monopole sensor collocated with orthogonally oriented dipole sensors is used for direction of arrival (DOA) estimation in the presence of an isotropic noise-field or internal device noise. A maximum likelihood (ML) DOA estimator is derived and subsequently shown to be a special case of DOA estimation by means of a search for the direction of maximum steered response power (SRP). The problem of SRP maximization with respect to a vector-sensor can be solved with a computationally inexpensive algorithm. The ML estimator achieves asymptotic efficiency and thus outperforms existing estimators with respect to the mean square angular error (MSAE) measure. The beampattern associated with the ML estimator is shown to be identical to that used by the minimum power distortionless response beamformer for the purpose of signal enhancement.     

Resolution-enhanced Fourier transform method for the estimation of multiple phases in interferometry

A phase shifting method based on high-resolution frequency estimation and Fourier transform technique is introduced. This method, also referred to as the eigenvector method, draws on the complementary strengths of both these methods. The salient feature of the method lies in its ability to handle nonsinusoidal wave-forms, multiple piezoelectric transducers, and arbitrary phase steps in an optical configuration. The method does not need the addition of carrier fringes to separate the spectral contents in the intensity fringes. The proposed concept thus overcomes the limitations of methods based on Fourier transform techniques. The robustness of the proposed method is studied in the presence of noise.     

多谐波脉冲星信号时延估计方法

针对脉冲星导航技术中延时估计这一关键问题, 提出了频域上直接使用脉冲星信号测量到达时间集合进行时延估计的方法——多谐波脉冲星信号时延估计(MHSPE)方法. 该方法建立在频域上相位时延的极大似然估计的基础上, 通过高次谐波对脉冲星观测信号提取出各谐波相位的极大似然估计, 然后取频谱上各谐波的幅值进行归一化作为各谐波相位的权值, 最后取各谐波相位的加权平均作为该时刻的相位估计. 理论上证得MHSPE算法对相位的估计是无偏、一致的, 相比于频域上一次谐波的极大似然估计, MHSPE方法的信噪比随谐波数m的增加而增加, 当各谐波幅值相同时, 信噪比可提高m_1/2倍; 与脉冲星信号时延的克拉美罗界比较, 脉冲星信号时域的导数在频域上的反映就是各谐波分量的数量, 因此随着谐波次数的增加脉冲星信号时延估计可极大趋近克拉美罗界. 采用RXTE航天器对Crab脉冲星的实测数据检验MHSPE方法的性能, 实验结果表明, 针对低信噪比的脉冲星信号, MHSPE可获得高精度的相位估计, 随观测时间增加, 估计精度快速收敛于克拉美罗界.     

An adaptive time delay estimati on algorithm based onquadratic weighting of the frequency domain

Time delay estimation (TDE) plays an important role in many engineering appli-cations. A new time delay estimation configuration, the quadratic weighting of the frequency domain adaptive TDE model, is put forward. The quadratic weighting of the frequency domainSCOT (Smoothed Coherence Transform) and ML (Maximum Likelihood) adaptive TDE algo-rithms are presented, respectively. The variance of the quadratic weighting of the frequency domain SCOT algorithm is derived. Then the proposed algorithms are applied in the TDE of helicopter passive acoustic location. The simulation results are presented which verify that the proposed algorithm has better performance in the low signal to noise ratio.     

Improved robustness of target location in nonhomogeneous backgrounds by use of the maximum-likelihood ratio test location algorithm

We address the problem of localizing small targets with random gray levels that appear in random background clutter. We consider the recently proposed maximum-likelihood ratio test (MLRT) algorithm, which scans the observed scene with an estimation window in which the local statistics are estimated. In the presence of a spatially homogeneous background, we show that if the estimation window is a few times larger than the target itself, the MLRT is quasi-equivalent to the optimal maximum-likelihood (ML) algorithm, which uses the whole scene for estimating the background statistics. The MLRT thus constitutes an efficient alternative to the ML algorithm and is more robust in dealing with spatially nonhomogeneous clutter since it utilizes a small estimation window.     

结合幅度谱和功率谱字典的语音增强方法

从双路字典学习、噪声功率谱估计、语音幅度谱重构角度提出了一种改进的谱特征稀疏表示语音增强方法。在字典学习阶段,融合功率谱与幅度谱特征,采用区分性字典降低语音字典和噪声字典的相干性;在语音增强阶段,提出一种噪声功率谱估计方法对非平稳噪声进行跟踪估计;考虑到幅度谱和功率谱特征对不同噪声的适应程度不同,设计了语音重构权值表。对分别由幅度谱和功率谱恢复而来的两路信号进行自适应加权重构,结合相位补偿函数得到增强后的语音信号。实验结果表明,该方法在平稳、非平稳噪声环境下相比于单一谱特征的语音增强方法平均提高31.6%,改善了语音增强方法的性能。      

Channel-combination method for phase-based |B1+| mapping techniques

PurposeThe aim of this study was to propose a channel combination method for |B₁⁺| mapping methods using phase difference to reconstruct |B₁⁺| map.Theory and methodsPhase-based |B₁⁺| mapping methods commonly consider the phase difference of two scans to measure |B₁⁺|. Multiple receiver coils acquire a number of images and the phase difference at each channel is theoretically the same in the absence of noise. Affected by noise, phase difference is approximately governed by Gaussian distribution. Considering data from all channels as samples, estimation can be achieved by maximum likelihood method. With this method, all phase differences at each channel are combined into one. In this study, the proposed method is applied with Bloch-Siegert shift |B₁⁺| mapping method. Simulations are performed to illustrate the phase difference distribution and demonstrate the feasibility and facility of the proposed method. Phantom and vivo experiments are carried out at 1.5 T scanner equipped with 8-channel receiver coil. In all experiments, the proposed method is compared with weighted averaging (WA) method.ResultsSimulations revealed appropriateness of approximating the distribution of phase difference to Gaussian distribution. Compared with WA method, the proposed method reduces errors of |B₁⁺| calculation. Phantom and vivo experiments provide further validation.ConclusionConsidering phase noise distribution, the proposed method achieves channel combination by finding the estimation from data acquired by multiple receivers coil. The proposed method reduces |B₁⁺| reconstruction errors caused by noise.     

光纤干涉位移传感器相位估计的一种精确方法

应用信号处理有关技术提出了一种光纤干涉位移传感器相位估计的方法,可以解决很大范围的不等幅、周期非均匀、带噪干涉信号条纹的精确计数问题。分析了此方法的适用范围及估计精度。对于１０ｄＢ信噪比的系统来说,位移在０．３ｍｍ以内的测量精度可达到λ／１００。     

Chirp estimation in phase-shifting interferometry

We propose a new approach for estimating the phase in the presence of a nonlinear response of a phase-shifting device: a piezoelectric transducer (PZT). The method is complemented well by the high resolution and the maximum likelihood estimation techniques in the estimation of the phase step and the nonlinear coefficient. The advantage of the proposed method is that it can be extended to the extraction of multiple phases in configurations involving multiple PZTs in the presence of nonlinearity. Symmetricity in the phase steps is not required in this method. Hence hysteresis of the PZT does not have any influence on the accuracy of the phase estimation. The effectiveness of the method is shown by experimental results.     

Multiple trellis-coded modulation,per-survivor processing and Reed–Solomon coding in the presence of phase noise

The aim of this paper is to consider trellis coded modulation (TCM) in the presence of phase noise. The starting point is a two-dimensional 32 point cross (32-CR) signal set that has served as a benchmark for other power and bandwidth efficient modulation schemes. Per-survivor processing (PSP) is used for carrier phase estimation, and both the phase acquisition (transient state) and phase tracking (steady state) performances are considered in an additive white Gaussian noise (AWGN) channel, in which phase offset or time varying phase noise is introduced. Based on the theoretical and simulation results it can be said that the 32-CR constellation is itself more sensitive to a phase error rather than the PSP algorithm. Due to the phase error the TCM scheme becomes a catastrophic code. Possible solutions include stringent phase noise requirements for oscillators, multiple trellis-coded modulation (MTCM) and concatenated TCM and Reed–Solomon (RS) coding. Our simulation results show that a simple combined MTCM, PSP and RS scheme has around 3 dB advantage compared to the pure TCM and PSP in the presence of phase noise. A semianalytical approach is used for performance evaluation, and the method is a particularly convenient tool to determine the rate of RS coding in detail.     

Novel iteration-free blind phase noise estimation for coherent optical OFDM

We propose a novel iteration-free blind phase noise estimation scheme for coherent optical orthogonal frequency division multiplexing （CO-OFDM） systems. In the new algorithm, the cost function is selected as the similar expression with real and imaginary parts as that in the modified constant modulus algorithm, and the new cost function is derived under some assumptions, where it is infinitely approximated by the sine and cosine functions. By means of the analytical formula of the cost function, the initial coarse common phase error can be obtained with only some samples, where the algorithm avoids computational complexity of conventional blind phase noise compensation scheme. In CO-OFDM systems with high-order modulation format （32 quadrature amplitude modulation） and narrow linewidth lasers, it is proved by the simulation results that the nhase noise can be effectively compensated with the proposed blind estimation method.     

稳健的高精度单矢量传感器测向方法

针对单矢量传感器各通道之间的相位误差引起已有方法测向不准的问题,提出一种对相位误差稳健的高精度测向方法.该测向方法首先利用单矢量传感器接收信号协方差矩阵的主特征向量与其共轭向量做Hadamard积来构造空间谱,实现对水下目标的方位估计;由于Hadamard积消除了相位误差,此估计值与相位误差无关,但存在方位估计模糊。然后利用相位误差的估计值进行解模糊操作,从而得到正确的方位估计。该测向方法的测向性能独立于相位误差,估计精度高。仿真和试验数据处理结果验证了该测向方法对相位误差稳健;在相位误差条件下,其方位估计精度高于平均声强法、CAPON测向方法以及MUSIC测向方法。而且仿真结果表明,该测向方法的测向精度接近克拉美洛下界(CRB)。      

基于高斯-拉普拉斯-伽玛模型和人耳听觉掩蔽效应的信号子空间语音增强算法

针对信号子空间语音增强算法中的子空间选择和线性滤波器中噪声功率谱和拉格朗日乘子的估计问题,用高斯、拉普拉斯和伽玛模型描述了语音的分布,提出了利用目标语音概率最大化来确定信号子空间维度的方法。在噪声子空间上,利用条件概率估计出噪声功率谱。接着,为了合理地折中增强语音中的残余噪声和语音畸变,提出了一种基于人耳听觉掩蔽效应的拉格朗日乘子估计方法。实验证明,在多项语音质量评价指标上,所提算法都取得了更好的结果。所提的信号子空间算法比传统的信号子空间算法更有效地消除了噪声,使得恢复的语音具有更好的质量。      

Robust direction-of-arrival estimation method with high accuracy for single vector sensor

The phase errors among the components of a single acoustic vector sensor cause the direction-of-arrival(DOA) estimation error of the existing methods.In order to address this issue,a DOA estimation method is proposed,which is robust to the phase errors.The proposed method first utilizes the Hadamard product of the principal eigenvector of the covariance matrix of the received signal by the single vector sensor and its conjugate vector to construct the spatial spectrum in order to estimate the DOA of the underwater target.Since the Hadamard product eliminates the phase errors,this estimation is independent of the phase errors.However,it is ambiguous.Afterwards,the phase-error estimate is explored to eliminate the ambiguity and get the correct DOA estimate.The proposed method performs independently of the phase errors and obtains high accuracy.The simulation results and the experimental result demonstrate the proposed method is robust to the phase errors.Furthermore,in the presence of the phase errors,it performs better than the average acoustic intensity method,the CAPON method,and the MUSIC method,in terms of estimation accuracy.In addition,the simulation results indicate that the estimation accuracy of the proposed method approaches to the Cramer-Rao bound(CRB).