相干信源波达方向估计的加权空间平滑算法

提出了一种用于空间相干源DOA估计的加权空间平滑算法(WSS，weighted spatial smoothing)。常规的空间平滑算法没有利用子阵输出的互相关信息，而且对相干信源的分辨力较差。WSS算法充分利用了子阵输出的自相关信息和互相关信息，将主阵协方差矩阵的所有子阵阵元数阶的子矩阵进行加权平均，以期提高常规空间平滑算法的分辨性能。文中以加权平滑后等效的信源协方差矩阵的对角化为约束条件，推导了加权矩阵的理论表达式。计算机仿真结果表明，WSS算法与常规空间平滑算法相比具有更高的分辨性能和更低的信噪比门限。特别是在于阵划分较多时其优越性更加明显。     

Performance analysis of spatial smoothing with interpolated arrays

The interpolated spatial smoothing algorithm is a computationally efficient method for estimating the directions of arrival (DOAs) of signals, some of which may be perfectly correlated. It extends the spatial smoothing method to arbitrary array geometries. A statistical performance analysis of the algorithm is presented. Closed-form expressions for the covariance matrix of the DOA estimation errors are derived using a perturbation analysis. Evaluating these expressions for specific cases and comparing them to the Cramer-Rao lower bound for the DOA estimates provides insight into the statistical efficiency of this algorithm. The formulas for the error covariance are quite general and can be specialized to provide results for other DOA estimation algorithms as well     

Improved spatial smoothing technique

The authors present a spatial smoothing technique which can be considered as being an improvement on two spatial smoothing techniques developed previously. To verify its usefulness, our improved technique and those previously developed are applied to decorrelate coherent multipath signals in the context of indoor radio channels. The multipath arrival times are then super-resolved using forward-backward (FB) MUSIC and the results are compared to determine the improvement     

Weighted subspace fitting for general array error models

Model error sensitivity is an issue common to all high-resolution direction-of-arrival estimators. Much attention has been directed to the design of algorithms for minimum variance estimation taking only finite sample errors into account. Approaches to reduce the sensitivity due to array calibration errors have also appeared in the literature. Herein, one such approach is adopted that assumes that the errors due to finite samples and model errors are of comparable size. A weighted subspace fitting method for very general array perturbation models is derived. This method provides minimum variance estimates under the assumption that the prior distribution of the perturbation model is known. Interestingly, the method reduces to the WSF (MODE) estimator if no model errors are present. Vice versa, assuming that model errors dominate, the method specializes to the corresponding “model-errors-only subspace fitting method.” Unlike previous techniques for model errors, the estimator can be implemented using a two-step procedure if the nominal array is uniform and linear, and it is also consistent even if the signals are fully correlated. The paper also contains a large sample analysis of one of the alternative methods, namely, MAPprox. It is shown that MAPprox also provides minimum variance estimates under reasonable assumptions     

Finite data performance analysis of MVDR beamformer with andwithout spatial smoothing

The finite-data performance of a minimum-variance distortionless response (MVDR) beamformer is analyzed with and without spatial smoothing, using first-order perturbation theory. In particular, expressions are developed for the mean values of the power gain in any direction of interest, the output power, and the norm of the weight-error vector, as a function of the number of snapshots and the number of smoothing steps. It is shown that, in general, the smoothing, in addition to decorrelating the sources, can alleviate the effects of finite-data perturbations. The above expressions are reduced to the case in which no spatial smoothing is used. These expressions are valid for an arbitrary array and for arbitrarily correlated signals. For this case, an expression for the variance of the power gain is also developed. For a single interference case it is shown explicitly how the SNR, spacing of the interference from the desired signal and the correlation between them influence the beamformer performance. Simulations verify the usefulness of the theoretical expressions     

Blind multiuser detection: from MOE to subspace methods

The minimum output energy (MOE) multiuser receiver has been shown to approach the minimum mean-square-error (MMSE) receiver at high signal-to-noise ratio (SNR). However, performance degradation is incurred by noise induced channel estimation error. In this paper, we propose a Power of R (POR) technique to significantly improve the performance of the MOE receiver. It is shown that the new receiver asymptotically converges to the MMSE receiver without performance penalty. The convergence is established either under high SNR, with large exponent raised in the power of the covariance matrix, or with sufficiently large number of data samples. Connection between our POR method and a widely studied subspace method is investigated from the respective optimization criteria. Asymptotic equivalence between these two methods is also established. Extensive simulations based on finite data samples show that the proposed method significantly outperforms the subspace method in systems with medium to heavy loading, severe multipath distortion, or smaller processing gain. Moreover, adaptive implementation of the proposed method exhibits very robust performance in a dynamic loading environment.     

Multichannel blind identification: from subspace to maximumlikelihood methods

A review of blind channel estimation algorithms is presented. From the (second-order) moment-based methods to the maximum likelihood approaches, under both statistical and deterministic signal models. We outline basic ideas behind several new developments, the assumptions and identifiability conditions required by these approaches, and the algorithm characteristics and their performance. This review serves as an introductory reference for this currently active research area     

Improved angular resolution for spatial smoothing techniques

Spatial smoothing techniques are used to estimate the directions of coherent arrivals. The performance of these techniques deteriorates rapidly as the coherent arrivals become closely spaced. The author examines the resolution performance of the existing forward-only and forward/backward spatial smoothing techniques. It is shown that the resolution for coherent signals can be improved by squaring array covariance matrices before forming smoothed array covariance matrices     

Signal enhancement of the spatial smoothing algorithm

A spatial smoothing algorithm to decorrelate highly correlated sources for direction-of-arrival (DOA) estimation in narrowband problems is developed. The rate of decorrelation of the coherent sources is very low and sensitive to the signal-to-noise ratio (SNR) for sources with close DOAs. A method to enhance the signal (to remove the effects of the sensor noise) and to make the spatial smoothing robust with respect to SNR is proposed. This approach will significantly improve the resolution of the algorithm. Statistical characteristics of the improved spatial smoothing are compared with that of the standard spatial smoothing     

Adaptive array with global weighted spatial smoothing

Global weighted spatial smoothing is utilised in adaptive arrays for coherent interference suppression. With the prior knowledge of the directions of coherent sources, signal cancellation is eliminated and the smoothing index can be reduced to the number of sources even for small spatial separation.     

图像平滑处理方法的比较研究

图像平滑处理在数字图像处理中有着重要的作用。系统分析目前具有代表性的图像平滑处理方法,并用MATLAB7．0软件实现了各种算法。实验结果表明,各种方法均有各自的优缺点和适用条件,在做图像平滑处理之前,应对图像进行分析,针对图像的特点和应用需求选用合适的方法。     

Analysis of spatial smoothing with uniform circular arrays

We analyze spatial smoothing with uniform circular arrays (UCAs). In particular, we study the performance of the Root-MUSIC with smoothing in the presence of correlated sources, finite data perturbations, and errors in the transformed steering vector that arise due to some approximations made while extending the Root-MUSIC and smoothing to UCA. Expressions are derived for the asymptotic performance of the Root-MUSIC with smoothing applied to the transformed UCA data. An attempt has been made to bring out the impact of both the forward and forward-backward smoothing. We consider UCAs with isotropic as well as directional sensors in our study. Computer simulations are provided to demonstrate the usefulness of the analysis     

Performance of spatial smoothing algorithms for radar signaturemodelling

In the area of radar signature modelling, subspace-based methods have recently become very popular. To model radar signals using subspace-based methods, spatial-smoothing preprocessing (SSP) is essential to estimate the covariance matrix of the received signals. Here, the performances of two typical SSP techniques are compared in the context of radar signature modelling     

Weighted interdigital transducers for smoothing of ripples in acoustic-surface-wave bandpass filters

The transfer function of acoustic-surface-wave (a.s.w.) bandpass filters exhibits ripples in the passband and sidelobes in the stopband, owing to the finite length of the sin x/x-shaped interdigital transducer used for the filter's impulse-response synthesis. A direct means of overcoming this inconvenience by weighting the interdigital transducer according to smoothing functions, such as those of Fejèr and Lanczos, which were developed for the suppression of ripples due to the Gibbs phenomenon, has been devised. The reported results show the effectiveness of this simple approach to the improvement of a.s.w.-filter capabilities.     

On spatial smoothing for two-dimensional direction-of-arrivalestimation of coherent signals

We present an analysis of a spatial smoothing scheme extended for the estimation of two-dimensional (2-D) directions of arrival (DOAs) of coherent signals using a uniform rectangular array. The uniform rectangular array is divided into overlapping rectangular subarrays by the extended scheme, which is referred to as the 2-D spatial smoothing scheme. The analysis shows that when the extended preprocessing scheme is used in conjunction with the eigenstructure technique, the size of the subarrays should be at least (K+1)×(K+1), and the number of the subarrays must be no less than K×K in order to guarantee the “decorrelation” of κ coherent signals for all possible scenarios. The minimum size of the total uniform rectangular array is thus shown to be 2K×2K. Instead of using a uniform rectangular array, a minimal subarray structure incorporated with a minimal subarray grouping is also devised for resolving the 2-D DOAs of K coherent signals. The number of sensor elements of the minimal total array is then (K²+4K-2) instead of 4K²     

Improved adaptive ing of coherent interference without spatial smoothing

A new scheme for adaptive ing in the presence of coherent interference is proposed that finds the weight vector using a nonsquare correlation matrix without spatial smoothing. Conventional schemes, which use square matrices, correspond to specific cases of the new method. It allows us to increase the dimension of the weight vector such that the ing capability is enhanced. Theoretic performance analysis is made, showing that the output signal-to-interference ratio (SINR) of such a beamformer is proportional to the weight dimension for sidelobe interference. Simulation results confirm this.     

Improved spatial smoothing techniques for DOA estimation ofcoherent signals

In the context of coherent signal classification, spatial smoothing is necessary for the application of the eigen-based direction of arrival (DOA) estimation methods. However, the currently known spatial smoothing algorithms not only reduce the effective aperture of the array, but also do not consider the cross correlations of the subarray outputs. An improved spatial smoothing algorithm which can fully utilize the correlations of the array outputs and produce a more stable estimate of the covariance matrix is presented. Simulation results are provided to verify the theoretical prediction. The superiority of this method over the conventional methods is obvious, especially when the SOSR (subarray to overall size ratio) is small     

Transient intensity noise of semiconductor lasers: experiments andcomparison with theory

An experimental setup for the measurement of the nonstationary intensity fluctuations during the turn-on transient of semiconductor lasers is presented. Measurements are carried out and compared with simulations, which are based on rate equations with Langevin fluctuation functions. Good agreement between theory and measurements is found, and it is confirmed that the nonstationary intensity noise can be interpreted as timing jitter