共查询到17条相似文献,搜索用时 203 毫秒
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在GPS接收机空时抗干扰的研究过程中,计算量大是目前主要的瓶颈,因此研究降维简化处理算法成为空时处理最关键的问题之一。在已给空时二维自适应滤波模型的基础上,通过对降维处理思想的分析,提出了一种基于多级维纳滤波(MWF)模型的改进方法——简化多级维纳滤波方法,并与一般的降维方法进行了均方误差(MSE)性能分析,仿真试验验证了该方法的有效性。 相似文献
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基于GSC框架降秩自适应滤波算法研究 总被引:1,自引:0,他引:1
基于对自适应滤波算法的研究可以得出,GSC(Generalized Sidelobe Canceller)框架是所有降秩滤波算法的统一基础模型,通过对GSC一般结构的降秩模型的研究。文中提出了3种能够改善一般结构结果的优化模型,PC(Prin-ciple Component)主分量算法、CS(Cross Spectrum)交叉谱算法、MWF(Mutistage Wiener Filter)多级维纳滤波器。这三种方法都是基于特征子空间截断的方法。通过对降秩矩阵T的特征值分解和重新构造,大大降低了自由度和工程运算量。该两种方法在实际应用中具有更优的实时性。仿真结果证明了提出的基于广义旁瓣相消的降秩自适应波束形成算法具有良好的降低自由度和波束形成性能,验证了算法的有效性。 相似文献
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传统的GPS空域抗干扰技术存在自由度低、抗干扰能力差等缺点.空时二维处理结构成功解决了这一问题,针对空时抗干扰处理复杂度高的不足,研究了空时处理方法的三种降秩处理方法:主成分法(PC)、互谱度法(CSM)、多级维纳滤波法(MWF),对它们的性能进行了比较.并选用高效降低运算量的相关相减多级维纳滤波算法(CSA-MWF),设计了一种GPS抗干扰的硬件实现方法.DSP仿真结果证实了所提方法的可行性. 相似文献
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在处理大型阵列时,阵元数较多,通常对阵列采用降秩处理可以较好地解决运算量过大的问题。基于广义旁瓣相消器(GSC)框架的降秩变换自适应滤波是各种降秩自适应滤波算法的统一模型。分析了基于GSC框架的几种降秩自适应滤波算法,针对当降秩阶数大于干扰数时方向图旁瓣过高、波形混乱和系统性能下降问题,提出了一种基于GSC框架的改进降秩算法,该算法利用特征子空间对GSC阻塞矩阵加以改进,使用改进后的阻塞矩阵进行降秩自适应处理,仿真结果证明了改进算法可以降低旁瓣电平,并形成较好的波束形状,提高了GSC性能的稳健性。 相似文献
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降秩自适应滤波算法研究 总被引:1,自引:0,他引:1
对降秩自适应滤波算法进行了系统的总结和分析,推导了其相互关系。分析表明,GSC(Generalized Sidelobe Canceller)框架降秩变换自适应滤波是各种降秩自适应滤波算法的统一模型。在此基础上导出了线性约束正交投影算法。降秩多级维纳滤波器在相关意义上进行截断降秩,其降秩性能优于基于特征子空间截断的降秩方法。酉多级维纳滤波器与共轭梯度法等效,均是基于Krylov子空间截断降秩的方法,降秩性能更优。最后通过计算机仿真试验比较了各种降秩处理算法的性能。 相似文献
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A generalized multidimensional Wiener filter for denoising is adapted to hyperspectral images (HSIs). Commonly, multidimensional data filtering is based on data vectorization or matricization. Few new approaches have been proposed to deal with multidimensional data. Multidimensional Wiener filtering (MWF) is one of these techniques. It considers a multidimensional data set as a third-order tensor. It also relies on the separability between a signal subspace and a noise subspace. Using multilinear algebra, MWF needs to flatten the tensor. However, flattening is always orthogonally performed, which may not be adapted to data. In fact, as a Tucker-based filtering, MWF only considers the useful signal subspace. When the signal subspace and the noise subspace are very close, it is difficult to extract all the useful information. This may lead to artifacts and loss of spatial resolution in the restored HSI. Our proposed method estimates the relevant directions of tensor flattening that may not be parallel either to rows or columns. When rearranging data so that flattening can be performed in the estimated directions, the signal subspace dimension is reduced, and the signal-to-noise ratio is improved. We adapt the bidimensional straight-line detection algorithm that estimates the HSI main directions, which are used to flatten the HSI tensor. We also generalize the quadtree partitioning to tensors in order to adapt the filtering to the image discontinuities. Comparative studies with MWF, wavelet thresholding, and channel-by-channel Wiener filtering show that our algorithm provides better performance while restoring impaired HYDICE HSIs. 相似文献
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On the equivalence of three reduced rank linear estimators with applications to DS-CDMA 总被引:4,自引:0,他引:4
Wanshi Chen Mitra U. Schniter P. 《IEEE transactions on information theory / Professional Technical Group on Information Theory》2002,48(9):2609-2614
This correspondence shows the equivalence of three previously proposed reduced-rank detection schemes for direct-sequence code-division multiple-access (DS-CDMA) communication systems. The auxiliary vector filtering (AVF) algorithm is simplified through a key observation on the construction of the auxiliary vectors. After simplification, it is shown that the AVF algorithm is equivalent to the multistage Wiener filtering (MWF) algorithm of Honig and Goldstein (2002). Furthermore, these schemes can be shown to be equivalent to the multistage linear receiver scheme based on the Cayley-Hamilton (CH) theorem when the minimum mean-square error (MMSE) criterion is applied to the reduced dimensional space of the received signal. 相似文献
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Recently, a generalized noise reduction scheme has been proposed, called the Spatially Preprocessed, Speech Distortion Weighted, Multichannel Wiener Filter (SP-SDW-MWF). It encompasses the Generalized Sidelobe Canceller (GSC) and a multichannel Wiener filtering technique as extreme cases. Compared with the widely studied GSC with Quadratic Inequality Constraint (QIC-GSC), the SP-SDW-MWF achieves a better noise reduction performance for a given maximum speech distortion level. We develop a low-cost, stochastic gradient implementation of the SP-SDW-MWF. To speed up convergence and reduce computational complexity, the algorithm is implemented in the frequency domain. Experimental results with a behind-the-ear hearing aid show that the proposed frequency-domain stochastic gradient algorithm preserves the benefit of the exact SP-SDW-MWF over the QIC-GSC, while its computational cost is comparable to the least mean square-based scaled projection algorithm for QIC-GSC. 相似文献
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Resende L.S. Romano J.M.T. Bellanger M.G. 《Signal Processing, IEEE Transactions on》2004,52(3):636-644
This paper proposes a new structure for split transversal filtering and introduces the optimum split Wiener filter. The approach consists of combining the idea of split filtering with a linearly constrained optimization scheme. Furthermore, a continued split procedure, which leads to a multisplit filter structure, is considered. It is shown that the multisplit transform is not an input whitening transformation. Instead, it increases the diagonalization factor of the input signal correlation matrix without affecting its eigenvalue spread. A power normalized, time-varying step-size least mean square (LMS) algorithm, which exploits the nature of the transformed input correlation matrix, is proposed for updating the adaptive filter coefficients. The multisplit approach is extended to linear-phase adaptive filtering and linear prediction. The optimum symmetric and antisymmetric linear-phase Wiener filters are presented. Simulation results enable us to evaluate the performance of the multisplit LMS algorithm. 相似文献
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Pezeshki A. Scharf L.L. Azimi-Sadjadi M.R. Yingbo Hua 《Signal Processing, IEEE Transactions on》2005,53(1):121-135
The problem of two-channel constrained least squares (CLS) filtering under various sets of constraints is considered, and a general set of solutions is derived. For each set of constraints, the solution is determined by a coupled (asymmetric) generalized eigenvalue problem. This eigenvalue problem establishes a connection between two-channel CLS filtering and transform methods for resolving channel measurements into canonical or half-canonical coordinates. Based on this connection, a unified framework for reduced-rank Wiener filtering is presented. Then, various representations of reduced-rank Wiener filters in canonical and half-canonical coordinates are introduced. An alternating power method is proposed to recursively compute the canonical coordinate and half-canonical coordinate mappings. A deflation process is introduced to extract the mappings associated with the dominant coordinates. The correctness of the alternating power method is demonstrated on a synthesized data set, and conclusions are drawn. 相似文献