THE METHOD OF SEPARATING HARMONIC SIGNALS FROM MULTIPLICATIVE AND ADDITIVE NOISES

This paper focuses on the extraction of a harmonic signal from multiplicative and additive noises. A method is proposed in two stages: (1) to square the original discrete time series, which in- cludes both signals and noises, and form a new time series. By this means, the multiplicative noise is converted to additive noise; and (2) to filter out the noise by using existing noise removal schemes. With a large amount of simulation, experimental results demonstrated the efficiency and effective- ness of this newly developed method in terms of Signal-to-Noise Ratio (SNR) and other criteria. From the experiment, it is also found that: the two kinds of noises affect the SNR differently. In gen- eral, the SNR is not influenced by multiplicative Gaussian noise regardless of its variance. However, if both kinds of noise exist, the SNR decreases with the incensement of the Variance of Additive Noise to Multiplicative Noise Ratio (VAMNR). This analysis is also supported by simulation work.     

Stochastic Resonance in Bistable System Subject to Multiplicative and Additive Noise

In this paper, a simulation model of bistable system subject to multiplicative and additive noise is built on the basis of the theory of stochastic resonance(SR). SR phenomenon appears in the system subject to multiplicative and additive noise when a single signal transmits in the system. The output waveforms and the power spectrums at different frequencies are compared. The impact of the intensity of multiplicative and additive noise on the bistable system is discussed. It is found that this simulation model can upgrade the quality of the signal processing and the noise intensity can be effectively used for improving the effect of SR.     

Passive localization of 3-D near-field sources in coexisted multiplicative noise and additive noise

By exploiting thvorable characteristics of a uniIbrm cross-array, a passive localization algorithm of narrowband sources in the spherical coordinates （azimuth, elevation and range） is proposed. Based on the properly chosen sensor outputs, we compute the third-order cyclic moment matrices, and exploit a pre-calibration technique to eliminate multiplicative noise. Then, we construct a parallel factor （PARAFAC） model, and adopt trilinear altemating least squares regression （TALS） to estimate three-dimensional （3-D） near-field parameters. The investigated algorithm is efficient in the sense that it can eliminate multiplicative noise and additive noise, provide the improved estimation accuracy, as well as avoid the parameter-pairing procedure. Simulation results are carried out to demonstrate the performance of the proposed algorithm.     

Adaptive Threshold Median Filter for Multiple-Impulse Noise

Attenuating the noises plays an essential role in the image processing. Almost all the traditional median filters concern the removal of impulse noise having a single layer, whose noise gray level value is constant. In this paper, a new adaptive median filter is proposed to handle those images corrupted not only by single layer noise. The adaptive threshold median filter （ATMF） has been developed by combining the adaptive median filter （AMF） and two dynamic thresholds. Because of the dynamic threshold being used, the ATMF is able to balance the removal of the multiple-impulse noise and the quality of image. Comparison of the proposed method with traditional median filters is provided. Some visual examples are given to demonstrate the performance of the proposed filter.     

CRAMER-RAO BOUNDS OF THE FREQUENCY ESTIMATION IN THE TIME SELECTIVE RADIO CHANNELS WITH DOPPLER SPREAD

The mobile channel is slow fading and time selective, thus the multiplicative and additive noise of the channel will smear the spectral line, or arouse Doppler spread. This spread will make the parameters estimation accuracy degrade. The goal of this paper is to analytically assess this degradation when Carrier Frequency Offset （CFO） and Doppler shift exist jointly. Then the finite-sample Cramer-Rao Lower Bound （CRLB） is derived and close-form asymptotical expression is given for large-sample CRLB. These expressions give insights into the performance room for frequency estimation. Also the variance of Doppler shift estimator is simulated to illustrate the theoretical results.     

New Feedback Architecture for VCO-Based Delta-Sigma ADCs Utilizing Phase Shifter

The voltage controlled oscillator-based （VCO-based） continuous-time delta-sigma （CTDS） analog to digital converter （ADC） suffers from nonlinearity and mismatch in its feedback network. A new feedback network consisting of a phase shifter is proposed. The phase shifter replaces the digital to analog converter （DAC） in the proposed architecture. Feasibility of the proposed idea is discussed and its higher performance is illustrated through a behavioral simulation approach （CppSim）. We have also developed the phase shifter as a variable all-pass filter in the C language. The nonlinearity and mismatch of the system caused by DAC is mitigated, resulting in higher signal to noise ratio （SNR） and signal to noise and distortion ratio （SNDR）, respectively.     

Microwave Oscillator Phase Noise Requirement for TD-SCDM A Wireless Communication Systems

In time division synchronous code division multiple access （TD-SCDMA） wireless communication systems, QPSK or 8PSK has been employed to support high data rate services and high efficiency in available bandwidth. The performance of such systems is affected by the phase noise of the microwave local oscillator. The phase noise model of synthesizer and the RF transceiver model for the phase noise effect are proposed for applications of TD-SCDMA systems. The relationship between the power spectral density （PSD） and root mean square （RMS） phase error is given. Then, the error vector magnitude （EVM） performance is analytically evaluated by using the single side band （SSB） phase noise. Theoretical results show agreement with those obtained by measurement data and therefore can be used to derive the TD-SCDMA system performance.     

Improved Parameter Estimation for Chirp Signals Based on Cyclostationarity

The problem of concern here is parameter estimation of chirp signals in the presence of multiplicative and additive noise. An improved cyclostationarity based algorithm is proposed to estimate the phase parameters. The novelty of the proposed algorithm lies in the iterative estimation of the second-order parameters. The main characteristics of the method include reduction in error propagation effect, increase in estimation accuracy, and operation over a wider range of phase parameter values. Simulation results demonstrate that the proposed algorithm has better performance than the conventional cyclostationary estimation method.     

The Euclidean Distance Spectra of FDMA-CPM： Algorithms and Applications

The performance of multiuser Continuous phase modulation（CPM） over the additive white Gaussian noise channel with coherent maximum likelihood detection is considered. Algorithms are developed to calculate the Euclidean distance spectra employing tree-search and Astar algorithm. The complexity of proposed algorithms are further reduced using trellis minimization. The distance spectrum is then used to evaluate the performance of mul- tiuser CPM systems, which reveals that the performance of multiuser CPM can be significantly improved by using op- timized parameters. Both equally-powered and non-equally powered systems are considered. Numerical and simulated results confirm that the proposed algorithms can generate the distance spectra of all systems with lower complexity relative to previous methods and are particularly suited for multi user CPM systems.     

Simple intra-signal-interference removing detector for HE-DCSK

In this paper, a novel simple detector is designed to remove the intra-signal interference in high efficiency differential chaos shift keying （HE-DCSK） modulation scheme. With the help of data bit estimated before correlation detection, this new detector could remove the modulated chaotic segment that would form intra-signal interference component in the correlator output from every received information-bearing signal in HE-DCSK, leading to greatly and effectively improved system bit error rate （BER） performance. The effectiveness of this proposed detector is studied analytically based on the numerical integration method and evaluated by computer simulation in additive-white-Gaussian- noise （AWGN） channel. Simulation results reveal that the proposed detector can dramatically improve the overall BER performance of HE-DCSK even at relatively low signal noise ratio （SNR） levels.     

Unbiased homomorphic system and its application in reducing multiplicative noise

The problem of reducing the multiplicative noise corrupting a signal is discussed. A generalisation of the existing sampled function weighted order (SFWO) filter is proposed by relaxing the symmetry condition on the probability density function (PDF) of the noise. This generalised SFWO filter is then used within a homomorphic system to reduce the multiplicative noise. It is shown that the output from such a system is biased, and hence, a suitable bias compensation technique is suggested. An unbiased homomorphic system, whose design is based on the PDF of the corrupting multiplicative noise, is proposed to reduce the noise. Images generated by coherent imaging systems are always corrupted by speckle, a kind of multiplicative noise having a lognormal distribution. A filter called the mean median filter, to reduce additive white Gaussian noise, is first proposed and then used within the unbiased homomorphic system to reduce the speckle in images. The effectiveness of the various proposed algorithms is demonstrated and compared with that of some of the existing schemes through extensive simulations     

Two-dimensional adaptive block Kalman filtering of SAR imagery

A method for removing speckle from synthetic aperture radar (SAR) imagery by using 2-D adaptive block Kalman filtering is introduced. The image process is represented by an autoregressive model with a nonsymmetric half-plane (NSHP) region of support. New 2-D Kalman filtering equations are derived which taken into account not only the effect of speckles as multiplicative noise but also the effects of the additive receiver thermal noise and the blur. This method assumes local stationarity within a processing window, whereas the image can be assumed to be globally nonstationary. A recursive identification process using the stochastic Newton approach is also proposed which can be used on-line to estimate the filter parameters based upon the information within each new block of the image. Simulation results on several images are provided to indicate the effectiveness of the proposed method when used to remove the effects of speckle noise as well as those of the additive noise     

自适应正则化项去除乘性噪声

针对乘性噪声去噪算法研究,乘性噪声多出现在合成孔径雷达、超声波和激光等相干图像系统中,与标准高斯加性噪声不同,乘性噪声符合瑞利和伽马分布函数。文中通过:(1)取对数把乘性噪声模型转变成相加形模型;(2)改进正则化项成为自适应扩散模型;(3)将数学模型应用于图像处理的实践当中。在解决了阶梯效应的同时保持了图像的边缘。     

一种文本图像水印的算法研究

该文提出了一种文本图像水印的新算法。首先将文本中选定嵌入水印的区域视为一个彩色图像,对其进行离散余弦变换（DCT）,并将变换系数进行加密排序之后,则经典的乘性水印算法转变为加性算法。将排序之后的DCT系数视为分叉噪声,而水印信号为弱信号,那么利用加性噪声中弱信号榆测理论推导出一种水印检测器来检测水印信号,并对其检测性能进行了理论和实验分析。实验表明这种检测器对于高斯加性噪声、中值滤波、乘性噪音以及低通滤波等多种攻击手段都具有较好的抗攻击能力。     

Analytic behavior of the LMS adaptive line enhancer for sinusoidscorrupted by multiplicative and additive noise

The least mean squares adaptive line enhancer (LMS ALE) has been widely used for the enhancement of coherent sinusoids in additive wideband noise. This paper studies the behavior of the LMS ALE when applied to the enhancement of sinusoids that have been corrupted by both colored multiplicative and white additive noise. The multiplicative noise decorrelates the sinusoid, spreads its power spectrum, and acts as an additional corrupting noise. Closed-form expressions are derived for the optimum (Wiener filter) ALE output SNR as a function of the residual coherent sine wave power, the noncoherent sine wave power spectrum, and the background additive white noise. When the coherent to noncoherent sine wave power ratio is sufficiently small, it is shown that a nonlinear (e.g., square law) transformation of the ALE input results in a larger optimum ALE output SNR     

Robust NL-Means Filter With Optimal Pixel-Wise Smoothing Parameter for Statistical Image Denoising

Most denoising methods require that some smoothing parameters be set manually to optimize their performance. Among these methods, a new filter based on nonlocal weighting (NL-means filter) has been shown to have a very attractive denoising capacity. In this paper, we propose fixing the smoothing parameter of this filter automatically. The smoothing parameter corresponds to the bandwidth h of a local constant regression. We use the C_p statistic embedded in Newton's method to optimize h in a point-wise fashion. This statistic also has the advantage of being a reliable measure of the quality of the denoising process for each pixel. In addition, we introduce a robust regression in the NL-means filter designed to greatly reduce the blur yielded by the weighting. Finally, we show how the automatic denoising model can be extended to images degraded by multiplicative noise. Experiments conducted on images with additive and multiplicative noise demonstrate a high denoising power with a degree of detail preservation...     

乘性噪声环境下基于符号秩统计量的非参伪码捕获方法

扩频系统常常工作在多径环境中,伴随着加性噪声的同时往往还存在着乘性噪声.该文提出了一种乘性噪声环境下基于符号秩统计量的非参伪码捕获方法,将伪码捕获等价为假设检验问题,利用局部最佳检测算法推导出了乘性噪声环境下基于符号秩的检测统计量,通过简化记分函数进一步给出了局部次佳秩检测器.将局部次佳秩检测器与局部最佳检测器和平方和检测器的性能进行了仿真对比,结果表明该文所提出的捕获方法在乘性噪声环境下检测性能接近于乘性噪声环境下的局部最佳检测器,而较平方和检测器则有较大幅度的提高.     

基于均匀圆阵的信号二维方向角互相关估计

针对复值乘性和加性噪声同时存在的情况,提出一种基于均匀圆阵的信号二维方向角互相关估计方法.本文推导出互相关估计公式,分析了估计的统计性能,给出了最优参数选择原则.在不改变均匀圆阵阵列流形的情况下,此方法抑制了信号中的乘性和加性噪声,且计算量小.计算机仿真证明了此方法的有效性.     

乘性噪声环境下基于局部最佳检测器的伪码捕获方法

扩频系统常常工作在多径环境中，伴随着加性噪声的同时往往还存在着乘性噪声。该文提出了一种乘性噪声环境下伪码捕获方法，将伪码捕获等价为假设检验问题，利用局部最佳检测算法推导出乘性噪声环境下的伪码捕获检测统计量，文中给出了基于局部最佳检测算法的捕获结构，并与传统的平方和检测器进行了性能仿真对比，结果表明该文所提出的捕获方法在乘性噪声环境下检测性能较平方和检测器有较大幅度的提高，而在无乘性噪声的环境下检测性能只较传统的平方和检测器检测性能稍有降低。