A sharp upper bound for the probability of error of the likelihoodratio test for detecting signals in white Gaussian noise

A new sharp upper bound for the probability of error of the likelihood ratio test is given for the detection in white Gaussian noise of any random vector whose norm is greater than, or equal to, a given value and whose probability of presence is less than, or equal to, one half. Also, a new test for the detection of such vectors is described. This test does not depend on the distribution of the signal vector but nevertheless its probability of error is less than, or equal to, the given upper bound     

On the asymptotic distribution of GLR for impropriety of complex signals

In this paper, the problem of testing impropriety (i.e., second-order noncircularity) of a sequence of complex-valued random variables (RVs) based on the generalized likelihood ratio test (GLRT) for Gaussian distributions is considered. Asymptotic (w.r.t. the data length) distributions of the GLR are given under the hypothesis that RVs are proper or improper, and under the true, not necessarily Gaussian distribution of the RVs. The considered RVs are independent but not necessarily identically distributed: assumption which has never been considered until now. This enables us to deal with the practical important situations of noncircular RVs disturbed by residual frequency offsets and additive circular noise. The receiver operating characteristic (ROC) of this test is derived as byproduct, an issue previously overlooked. Finally illustrative examples are presented in order to strengthen the obtained theoretical results.     

一种阵列互耦影响下的目标直接定位算法及其理论性能分析

相比传统的两步定位方法,以Weiss和Amar等人提出的目标位置直接确定方法具有定位精度高、目标分辨率高、可避免"目标-量测"匹配等优势.本文基于该类定位方法的思想,提出了一种利用单个运动天线阵列对目标辐射源的直接定位算法.与已有直接定位算法不同的是,文中新算法考虑了阵列互耦的影响,并且能够实现阵列互耦参量和目标位置参量的解耦合估计.此外,文中还基于矩阵特征值扰动理论,定量推导了新算法参数估计的理论方差（包括目标位置估计方差和互耦向量估计方差）,并且给出了全部参量估计方差的克拉美罗界.最后,该文通过仿真实验验证了新算法的优越性和理论分析的有效性.     

A statistical resolution theory of the beamformer-based spatialspectrum for determining the directions of signals in white noise

Due to its simplicity and ease of implementation, the beamformer-based spatial spectrum (BSS) is widely used in practice to determine the angles of arrival of signals in white noise in array processing. As the most important performance to this application, the resolution capability of the BSS is roughly assessed by a deterministic measure, borrowed from optics, which takes into account only the influence of the effective aperture of the linear array of sensors. For a linear array operating in a stochastic environment, resolving two incoming signals is essentially a random event, thereby demanding a probabilistic resolution measure. In the paper, the probabilistic performance of the BSS in resolving two incoming signals is studied. The author derives a simple expression, in a closed form, for its failure probability in distinguishing the two signals. The results reveal the way various parameters of signals, noise, and array of sensors affect the resolution performance. Computer simulations are also presented to confirm the validity of the theory     

On the Cramer-Rao lower bound for RSS-based positioning in wireless cellular networks

An accurate position of a mobile user's location is substantial in wireless cellular networks with respect to location based services (LBS) implementation. Among the available parameters used to estimate a desired location, low cost measurement of received signal strength (RSS) makes it suitable for outdoor and indoor positioning. Our aim here is to look at the performance of a theoretically optimal user's position estimator. We examine the Cramer-Rao lower bound (CRLB), which sets the lowest variance of any unbiased estimator. Due to the oversimplification with respect to reliance on detailed cognizance of environment, we deploy theoretical free-space and empirical COST-231-Hata, Stanford University Interim (SUI) and ECC-33 path loss models that are dominantly used in real scenarios aiming to form the system model equations. The findings show that the CRLB on estimation precision depends on the underlying path loss exponents (PLE) and the relative positions of the mobile and base stations. The calculated bounds provide a benchmark against which it is possible to evaluate different positioning algorithms, techniques and estimators relying on the specified path loss models.     

On the cramer-rao bound for carrier frequency estimation in the presence of phase noise

We consider the carrier frequency offset estimation in a digital burst-mode satellite transmission affected by phase noise. The corresponding Cramer-Rao lower bound is analyzed for linear modulations under a Wiener phase noise model and in the hypothesis of knowledge of the transmitted data. Even if we resort to a Monte Carlo average, from a computational point of view the evaluation of the Cramer-Rao bound is very hard. We introduce a simple but very accurate approximation that allows to carry out this task in a very easy way. As it will be shown, the presence of the phase noise produces a remarkable performance degradation of. the frequency estimation accuracy. In addition, we provide asymptotic expressions of the Cramer-Rao bound, from which the effect of the phase noise and the dependence on the system parameters of the frequency offset estimation accuracy clearly result. Finally, as a by-product of our derivations and approximations, we derive a couple of estimators specifically tailored for the phase noise channel that will be compared with the classical Rife and Boorstyn algorithm, gaining in this way some important hints on the estimators to be used in this scenario     

On the use of first-order autoregressive modeling for Rayleigh flat fading channel estimation with Kalman filter

This letter deals with the estimation of a flat fading Rayleigh channel with Jakes's spectrum. The channel is approximated by a first-order autoregressive (AR(1)) model and tracked by a Kalman filter (KF). The common method used in the literature to estimate the parameter of the AR(1) model is based on a correlation matching (CM) criterion. However, for slow fading variations, another criterion based on the minimization of the asymptotic variance (MAV) of the KF is more appropriate, as already observed in few works (Barbieri et al., 2009 [1]). This letter gives analytic justification by providing approximated closed-form expressions of the estimation variance for the CM and MAV criteria, and of the optimal AR(1) parameter.     

The use of BDS statistics for estimating the parameters of chaotic mappings and regular signals in the presence of noise

A new method has been proposed in this paper for estimating the parameters of chaotic and regular signals by their observation against the background of white noise under conditions of the a priori uncertainty about the distribution of its values. The method is based on using the nonparametric BDS statistic revealing the sensitivity toward topological properties of the attractors of chaotic, regular and random processes that are characterized by the correlation dimension. The results of numerical simulation of the method proposed for the estimation of parameters of one-dimensional and two-dimensional chaotic mappings and also the harmonic oscillation frequency for the noise with uniform and Gaussian distribution at different levels of its intensity have been presented. This study also includes the analysis of accuracy of estimating the harmonic oscillation frequency by the proposed method and its comparison with potentially attainable values.     

Rank-order statistics for optimum detection of binary signals in the presence of white noise and dc drift (Corresp.)

The well-known technique of detecting binary pulses in white noise and unknown dc drift by means of a high-pass filter followed by a bit-by-bit detector is not theoretically optimum. The optimum procedure is shown to require a rank-ordering operation on the received data.     

空间欠采样信号DOA估计的解模糊算法

讨论了一种主要针对机载宽段雷达侦察接收机的宽带天线阵列阵元间距配置方案及相应的空间信号到达角解模糊算法。文中以具有最小冗余度的一今天晨均匀性阵为例,给出可以实现信号到达角解模糊的天线阵元间距配置的一个必要条件,并通过一个简化的一维整数搜索算法实现了信号到达角的无模糊估计。     

A nonlinear filter for estimating a sinusoidal signal and itsparameters in white noise: on the case of a single sinusoid

A nonlinear filter is proposed for estimating a complex sinusoidal signal and its parameters (frequency, amplitude, and phase) from measurements corrupted by white noise. This filter is derived by applying an extended complex Kalman filter (ECKF) to a nonlinear stochastic system whose state variables are a function of its frequency and a sample of an original signal, and then, proof of the stability is given in the case of a single complex sinusoid. Simulations demonstrate that the proposed nonlinear filter is effective as a method for estimating a single complex sinusoid and its frequency under a low signal-to-noise ratio (SNR). In addition, the effect of the initial condition in the filter on frequency estimation is also discussed     

A technique for a substantial reduction of the quantization noise in the direct processing of delta-modulated signals

The quantization noise introduced by the direct arithmetic operations on delta modulated signals can be considerably reduced by a proposed technique. According to this technique, the arithmetic network of a digital filter is clocked at a rate higher than that of the delta modulation encoder. Thus, as it is proved, a considerable reduction of the maximum quantization error can be achieved. A simple network is properly used to restore the filter output rate to that of the delta modulation encoder. The experimental results prove that the output sequence quantization noise can be reduced so much that the remaining noise is very close to that of the input delta modulated signal of the filter.     

载噪比直接法测量地球站G/T值的精度研究

本文阐述了利用卫星信标或未调制的测试载波直接测量地球站G T值的原理和方法。研究了其测量精度 ,给出了载噪比修正的实验研究曲线 ,且对G T值的测量误差进行了分析和估计。分析结果表明 :G T值测量的均方根误差为± 0 55dB。最后 ,给出了利用载噪比直接法测量地球站G T值的实例 ,且同间接法测量结果进行了比较 ,二者吻合很好。     

An analytic expression for the magnitudes of the signal and intermodulation outputs of an ideal hard limiter,assuming n input signals plus gaussian noise

An expression is derived that gives the output fundamental and intermodulation product magnitudes for an ideal hard limiter, for the case of n input signals plus Gaussian noise. The expression is derived by building upon previous work by Shimbo⁴ to account for the Gaussian noise input. The expression is implemented in a computational tool. Results are generated and are compared with data generated by Jain⁵ for three-signal suppression, and by Blachman¹¹ for the functional relationship between the output and input SNR for a bandpass limiter. In all cases, the data generated agree extremely well with published results.     

On the resolution properties of an adaptive algorithm for maximum entropy spectrum analysis

The resolution properties of the adaptive mean squares algorithm when used for maximum entropy spectrum estimation are compared with those of Burg's algorithm and the standard periodogram method using the FFT algorithm.     

Retransmission strategies for an acceptable quality of HDTV in the wireless and wired home scenario

We evaluate the performance of various retransmission schemes to achieve the goal of less than one visible distortion in twelve hours for high definition television. The focus is on an indoor wireless link and a DSL link, and we consider systems where the packets are protected by means of retransmissions with and without forward error correcting (FEC) codes. In order to achieve a satisfactory performance with restricted latency, we propose an unconventional retransmission procedure. The overall conclusion is that retransmissions without FEC achieve the best performance with the lowest latency, lowest overhead and lowest complexity, both in the wireless and the wired home scenario. Copyright © 2006 John Wiley & Sons, Ltd.     

A two-stage shearlet-based approach for the removal of random-valued impulse noise in images

In this paper, we introduce a novel two-stage denoising method for the removal of random-valued impulse noise (RVIN) in images. The first stage of our algorithm applies an impulse-noise detection routine that is a refinement of the HEIND algorithm and is very accurate in identifying the location of the noisy pixels. The second stage is an image inpainting routine that is designed to restore the missing information at those pixels that have been identified during the first stage. One of the novelties of our approach is that our inpainting routine takes advantage of the shearlet representation to efficiently recover the geometry of the original image. This method is particularly effective to eliminate jagged edges and other visual artifacts that frequently affect many RVIN denoising algorithms, especially at higher noise levels. We present extensive numerical demonstrations to show that our approach is very effective to remove random-valued impulse noise without any significant loss of fine-scale detail. Our algorithm compares very favourably against state-of-the-art methods in terms of both visual quality and quantitative measurements.     

机载条带SAR图像经纬度的计算方法

在不考虑地形起伏的情况下,从机载合成孔径雷达数据采集几何关系和成像原理的角度,针对正侧视和小斜视情况提出了计算机载SAR图像像素点经纬度的一种准确而实用的方法,给出了从雷达图像上的像素点计算其经纬度的详细过程,并结合某实际机载SAR成像参数对影响定位精度的因素包括高度测量误差,航向角、俯仰角、横滚角误差和多普勒中心、多普勒调频率误差进行了详细的分析。     

空间光通信中应用于精密指向的面阵探测器的定位精度分析与验证

为了实现空间光通信中高精度的链路,本文重点研究了影响面阵探测器对于目标定位精度的关键因素。首先从机理上分析了质心算法的误差,并仿真验证了满足空间无损采样条件的必要性。我们定义了NU值并以此为指标来量化探测器的非均匀性,随着NU自0开始线性增长,质心的定位误差持续增长但是速度放缓。当NU值为0.005时,最大定位误差为0.043 像素。在目标入射到光学系统的光强不断改变的条件下,NU值越小,质心位置越接近光斑的真实位置。我们通过实验测试了某种典型的CMOS探测器在不同光照强度下的像元响应,建立了像元响应非均匀性的数理模型,计算出NU值于线性响应范围内在0.0045到0.0048范围内波动。光斑质心定位精度的实验结果表明,绝对定位误差小于0.05 像素,可以满足高精度链路的需求,验证了理论和仿真的有效性。