MIMO雷达DOA估计方法分析

在介绍多输入多输出（MIMO:Multiple-Input Multiple-Output）雷达的信号模型的基础上,给出了一种目标波达方向（DOA:Direction of Arrival）估计方法--多信号分类（MUSIC:Multiple Signal Classification）方法在MIMO雷达系统DOA估计中的应用。与传统相控阵雷达相比,在MIMO雷达系统中该方法可以分辨的信号源数目有较大增加。通过仿真实验,详细分析了在MIMO雷达系统DOA估计中,多种因素对MUSIC方法测角精度的影响。     

一种估计宽带信号源数目的新方法

信号源数目估计是波达方向（DOA）估计的基础。基于噪声特征值的统计特性，文章在宽带信号条件下，基于各个频率点下的阵列采样协方差矩阵的噪声特征值在平面直角坐标系中几乎处于同一条直线上这一统计特性，提出了一种新的估计宽带信号源数目的方法，该方法简单且易于实现。最后通过计算机仿真验证了此方法的有效性和优越性。     

对QIM水印滤波攻击的估计

提出一种基于量化水印的两频带幅值比例攻击的估计算法。基于量化的水印算法对线性时不变（LTI）滤波攻击没有顽健性。考虑一种使用滤波器组调整信号频谱的多频带幅值比例攻击。首先，给出受攻击信号的概率密度函数（PDF）模型。然后，使用这个PDF模型，给出两频带滤波攻击幅值比例因子的最大似然估计方法。最后，以合成的音频信号进行实验，结果显示出所提出的估计技术的有效性。     

有效的自适应波达方向盲估计算法

本文在分析自适应信号盲分离算法渐近稳定性基础上,提出了一种有效的自适应学习算法用于波达方向盲估计。研究了算法的有界性和渐近稳定性。以渐近稳定性为前提,给出了算法中非线性函数的适当选择。为了抑制噪声和估计信源数,在算法中还增加了白化过程。仿真研究表明,算法是有效的而鲁棒的,其能够从有操声的阵元信号中估计波达方向。     

信源数目估计方法的研究

盲信号处理（Blind Signal ProCessing）是近年来信号处理研究的热点之一,＂盲＂是指在没有任何先验信息或者先验信启、不足环境下的假设,因此,该处理方法对环境及信号的应用更加宽泛。盲信源数目是盲分离的首要前提,信源数目的确定更是直接关系到盲分离效果的正确性。本文主要研究了IAC准则,MDL准则和盖式圆准则的盲信源数目估计算法。在不同信噪比情况下,分别对噪声观测信号进行信源数目估计。通过实验证明,盖式圆在含有噪声的情况下,能够相对准确的估计出信源数目,IAC和MDL在低信噪比情况下,不能准确的估计出信源数目。     

有色噪声中一维谐波频率估计的稳健迭代算法

本文通过构造基于观测信号的统计量,采用三步迭代（TSI）算法来估计乘性和加性有色噪声中一维谐波信号频率参数,得到了最终估计量的渐近分布,证明了估计的一致性。TSI算法通过引入周期图估计作为初估计,从谐波模型内在特性出发构造统计量,采用迭代方式逐步提高初估计精度,仅需三次迭代就能达到加性噪声情形下最小二乘估计（LSE）的关于样本的收敛速度。由于只需要三次迭代就可以达到收敛,所以算法的计算量比较少。另外相比较传统的迭代算法而言,TSI算法能保证每次迭代后都能够提高估计的精度,从而克服了传统的迭代算法收敛不够稳定不足。仿真实验证实了估计的一致性以及估计的渐近分布,而且在较大噪声情形下该迭代算法依然可行。最后,由于TSI算法具备小的计算量以及高的估计精度,因而十分适合作为一维谐波参数估计的在线算法。      

用复信号处理方法研究二维复指数信号最小二乘估计的渐近性质

二维复指数信号广泛应用于许多实际场合，本文利用复随机信号处理方法研究其最小二乘估计的渐近性能，Ｄ．Ｋｕｎｄｕ等人（１９９６）是将复信号表为实部和虚部来讨论的，因而非常繁琐，用复信号处理方法将使讨论大大简化。     

相关Nakagami信道下信道估计器对RAKE接收机性能影响研究

在实际环境中RAKE接收机在接收信号时都要进行信道系数估计,以便进行相干合并。文章研究了不采用导频信号与采用导频信号两种估计器,具有估计误差情况下,在相关Nakagami信道下的RAKE接收机的性能,并且通过特征函数法得到了误码率公式的闭合表达式。比较了两种估计器对系统性能的影响,最后给出了数值结果,可以看出,当导频信号能量与信号能量相等,且导频数目比较多时（大于5）,采用导频信号的系统性能优于直接估计信道系数的系统。直接估计信道系数的系统性能在信噪比大于5dB后,其性能远远优于导频信号的估计系统。     

LTE—A基于DMRS的噪声估计算法研究

LTE—A上行参考信号主要包括DMRS（解调参考信号）和SRS（探测参考信号）,DMRS信号主要用于上行信道估计以及eNodeB端的相干检测和解调,以便接收端成功解调数据。信道估计的准确性对于LTE—A系统的性能是至关重要的,而在信道估计算法（MMSE）中,噪声估计的准确性将直接影响到信道估计的性能。因此,为了更加准确地进行信道估计,对噪声估计的研究是非常有必要的。     

一种基于经验模态分解的信噪比盲估计新算法

为了增强未知样式信号的信噪比估计性能,提出了一种基于经验模态分解（EMD） 的信号信噪比估计新算法,通过固有模态函数（IMF）分量平均周期判断信号与噪声界限。 给出了经验模态分解估计法的工作原理和流程图,分析了经验模态分解估计法的性能。仿真 结果表明,与信号空间分解法一样,经验模态分解估计法能够实现盲信号信噪比估计,后者 估计均方误差比前者要小,在0 dB信噪比下均方误差不超过0.3 dB。     

Performance analysis of blind carrier frequency offset estimatorsfor noncircular transmissions through frequency-selective channels

This paper deals with the problem of blind estimation of the carrier frequency offset of a linearly modulated noncircular transmission through an unknown frequency-selective channel. A frequency estimator is developed based on the unique conjugate cyclic frequency of the received signal, which is equal to twice the frequency offset. Consistency and asymptotic normality of the frequency estimator together with a closed-form expression for its asymptotic variance are also established. The closed-form expression of the asymptotic variance enables analysis of the performance of the proposed frequency offset estimator as a function of the number of estimated cyclic correlation coefficients used. It is shown that optimum is obtained if the number of correlation coefficients taken into account coincides with the degree of the channel. Numerical simulations are provided and confirm the conclusion of the theoretical asymptotic analysis     

On adaptive EVD asymptotic distribution of centro-symmetriccovariance matrices

This article investigates the gain in statistical performance/complexity of the adaptive estimation of the eigenvalue decomposition (EVD) of covariance matrices when the centro-symmetric (CS) structure of such matrices is utilized. After deriving the asymptotic distribution of the EVD estimators, it is shown, in particular, that the closed-form expressions for the asymptotic covariance of batch and adaptive EVD estimators are very similar, provided that the number of samples is replaced by the inverse of the step size     

Iterative frequency estimation by interpolation on Fourier coefficients

The estimation of the frequency of a complex exponential is a problem that is relevant to a large number of fields. In this paper, we propose and analyze two new frequency estimators that interpolate on the Fourier coefficients of the received signal samples. The estimators are shown to achieve identical asymptotic performances. They are asymptotically unbiased and normally distributed with a variance that is only 1.0147 times the asymptotic Crame/spl acute/r-Rao bound (ACRB) uniformly over the frequency estimation range.     

有限快拍四阶累量无偏估计性能分析

关于累量域估计的研究以前主要着重于渐进性能的研究,包括渐近无偏估计及渐近方差。本文主要研究有限快拍累量域无偏估计性能,包括有限快拍的无偏估计及方差性能分析。仿真结果表明无偏估计在低信噪比情况下波达方向参数估计性能优于有偏估计,从而推动累量域本身估计的研究。     

Joint decorrelating multiuser detection and channel estimation inasynchronous CDMA mobile communications channels

The asymptotic efficiencies of two decorrelators, path-by-path and channel-matched decorrelators, are analyzed in fading multipath propagation environments, and based upon the analytical results, a new joint multiuser detection and channel estimation scheme is proposed for asynchronous code division multiple access (CDMA) mobile communications channels. In the path-by-path decorrelator, each of the received signals corresponding to one of the multiple propagation paths is regarded as an independent interference source. On the contrary, in the channel-matched decorrelator, each composite signal transmitted from an identical user is regarded as a response of the multipath channel to the corresponding user's spreading sequence. The asymptotic efficiency of the path-by-path decorrelator is shown to drop rapidly as the number of simultaneous users increases. It is shown that the asymptotic efficiency can be made independent of the number of the propagation paths by the channel-matched decorrelator at the expense of requiring knowledge about the fading complex envelopes of all the propagation paths. The proposed joint multiuser detection and channel estimation scheme uses both path-by-path and channel-matched decorrelators. The path-by-path decorrelator is used for providing the channel estimator with the (noisy) channel information path-by-path, and decisions are made on the output of the channel-matched decorrelator. The decision results are fed back to the channel estimator, and used as the reference signals. The received complex envelope of each of the propagation paths is estimated in the channel estimator. Results of a series of exhaustive computer simulations are presented in order to demonstrate the overall performance of the proposed scheme, both in non-fading and fading multipath propagation environments     

Asymptotic analysis of blind cyclic correlation-based symbol-rate estimators

This paper considers the problem of blind symbol rate estimation of signals linearly modulated by a sequence of unknown symbols. Oversampling the received signal generates cyclostationary statistics that are exploited to devise symbol-rate estimators by maximizing in the cyclic domain a (possibly weighted) sum of modulus squares of cyclic correlation estimates. Although quite natural, the asymptotic (large sample) performance of this estimator has not been studied rigorously. The consistency and asymptotic normality of this symbol-rate estimator is established when the number of samples N converges to infinity. It is shown that this estimator exhibits a fast convergence rate (proportional to N/sup -3/2/), and it admits a simple closed-form expression for its asymptotic variance. This asymptotic expression enables performance analysis of the rate estimator as a function of the number of estimated cyclic correlation coefficients and the weighting matrix. A justification for the high performance of the unweighted estimator in high signal-to-noise scenarios is also provided.     

ML approaches to channel estimation for pilot-aided multirateDS/CDMA systems

This paper analyzes the asymptotic performance of maximum likelihood (ML) channel estimation algorithms in wideband code division multiple access (WCDMA) scenarios. We concentrate on systems with periodic spreading sequences (period larger than or equal to the symbol span) where the transmitted signal contains a code division multiplexed pilot for channel estimation. First, the asymptotic covariances of the training-only, semi-blind conditional maximum likelihood (CML) and semi-blind Gaussian maximum likelihood (GML) channel estimators are derived. Then, these formulas are further simplified assuming randomized spreading and training sequences under the approximation of high spreading, factors and high number of codes. The results provide a useful tool to describe the performance of the channel estimators as a function of basic system parameters such as number of codes, spreading factors, or traffic to training power ratio     

Discrete-Time Estimation of Second-Order Statistics of Generalized Almost-Cyclostationary Processes

In this paper, the problem of estimating second-order statistics of continuous-time generalized almost-cyclostationary (GACS) processes is addressed. GACS processes in the wide sense have autocorrelation function almost-periodic in time whose generalized Fourier series expansion has both frequencies and coefficients that depend on the lag shifts. Almost-cyclostationary (ACS) processes are obtained as a special case when the frequencies do not depend on the lag shifts. ACS processes filtered by Doppler channels and communications signals with time-varying parameters are further examples. It is shown that continuous-time GACS processes do not have a discrete-time counterpart. The discrete-time cyclic cross-correlogram of the discrete-time ACS processes obtained by uniformly sampling GACS processes is considered as estimator of samples of the continuous-time cyclic cross-correlation function. The asymptotic performance analysis is carried out by resorting to the hybrid cyclic cross-correlogram which is partially continuous-time and partially discrete-time. Its mean-square consistency and asymptotic complex Normality as the number of data-samples approaches infinity and the sampling period approaches zero are proved under mild conditions on the regularity of the Fourier series coefficients and the finite or practically finite memory of the processes expressed in terms of summability of cumulants. It is shown that the asymptotic properties of the hybrid cyclic cross-correlogram are coincident with those of the continuous-time cyclic cross-correlogram. Hence, discrete-time estimation does not give rise to any loss in asymptotic performance with respect to continuous-time estimation.