共查询到19条相似文献,搜索用时 109 毫秒
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提出一种采用Lanczos算法估计噪声子空间的新方法。该方法采用传统的空间平滑技术解相干,然后由多级维纳滤波器的预滤波器的性质可知,多级维纳滤波器的冗余分解级的预滤波器可以构成一个噪声子空间。由此可以采用Lanczos算法快速估计到噪声子空间。由于不需要对协方差矩阵作特征值分解,而且所要求的冗余分解的级数较少,其运算量比基于特征值分解方法要小得多。此外,采用Lanczos算法计算降维矩阵和冗余矩阵只构成多级维纳滤波器的前向递推,从而使得算法的复杂度大大降低。最后,计算机仿真验证了该方法的有效性。 相似文献
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提出一种低复杂度的信号子空间拟合的新方法.证明了多级维纳滤波器的匹配滤波器(或降维矩阵的列矢量)可以张成一个压缩信号子空间.利用其与Krylov子空间等效这一特点,推导出信号子空间拟合一个新的基本公式,进而建立信号子空间拟合一个新的准则函数.分析表明,压缩信号子空间可以由降维矩阵的列矢量有效地张成,而且计算降维矩阵只需要多级维纳滤波器的若干步前向递推,所以本文方法的运算量和复杂度均较小.最后,计算机仿真验证了本文方法的有效性. 相似文献
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基于多级维纳滤波的MIMO雷达自适应脉冲压缩方法 总被引:2,自引:0,他引:2
自适应脉冲压缩能够有效抑制MIMO雷达发射波形间的互干扰。该文提出了一种基于多级维纳滤波器(MSWF)的MIMO雷达自适应脉冲压缩方法,该方法利用多级维纳滤波器的前后向递推系数计算脉冲压缩滤波器的权系数。与基于最小均方误差(MMSE)的自适应脉冲压缩方法相比,该方法无需对观测数据的协方差矩阵进行估计和求逆,大大降低了计算复杂度。计算机仿真结果表明,该方法具有与MMSE自适应脉冲压缩方法和广义旁瓣相消(GSC)自适应脉冲压缩方法相近的脉冲压缩性能。 相似文献
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通过一种新的方法构造酉矩阵,将该酉矩阵替代多级维纳滤波器(MWF)中的分解滤波器,得到一种新的降维多级维纳滤波器(RDMWF)。根据表达式给出了有效实现结构,并证明了该滤波器是一种酉多级滤波器(RUMWF)。相比于常规级维纳滤波器实现算法,新算法的计算量得以进一步降低且干扰抑制性能不受影响。 相似文献
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Lei Huang Shunjun Wu Xia Li 《Signal Processing, IEEE Transactions on》2007,55(12):5658-5667
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针对数字信号在正交频分复用(OFDM)系统中传输受载波频率偏移(CFO)敏感的问题,提出一种基于连续符号平均功率方差最小化的恒模OFDM(CM-OFDM)系统盲载波频偏估计算法。该算法基于频域信号恒模特性构造出代价函数,通过试验三个频偏估计量对CM-OFDM系统中的时域信号进行补偿,并最终采用蒙特卡罗的方法估计出CFO。此外,利用快速傅里叶变换(FFT)的正反变换构成一个酉矩阵,从而降低算法计算过程的复杂度。仿真表明,提出的算法有效的提高了CFO估计的性能,并且具有较好的鲁棒性。 相似文献
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Direction of arrival (DOA) estimation is an important issue for monostatic MIMO radar. A DOA estimation method for monostatic MIMO radar based on unitary root-MUSIC is presented in this article. In the presented method, a reduced-dimension matrix is first utilised to transform the high dimension of received signal data into low dimension one. Then, a low-dimension real-value covariance matrix is obtained by forward–backward (FB) averaging and unitary transformation. The DOA of targets can be achieved by unitary root-MUSIC. Due to the FB averaging of received signal data and the eigendecomposition of the real-valued matrix covariance, the proposed method owns better angle estimation performance and lower computational complexity. The simulation results of the proposed method are presented and the performances are investigated and discussed. 相似文献
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C. F. T. Tang K. J. R. Liu S. F. Hsieh K. Yao 《The Journal of VLSI Signal Processing》1992,4(1):53-68
The Householder transformation is considered to be desirable among various unitary transformations due to its superior computational efficiency and robust numerical stability. Specifically, the Householder transformation outperforms the Givens rotation and the modified Gram-Schmidt methods in numerical stability under finite-precision implementations, as well as requiring fewer arithmetical operations. Consequently, the QR decomposition based on the Householder transformation is promising for VLSI implementation and real-time high throughput modern signal processing. In this paper, a recursive complex Householder transformation (CHT) with a fast initialization algorithm is proposed and its associated parallel/pipelined architecture is also considered. Then, a CHT based recursive least-squares algorithm with a fast initialization is presented. Its associated systolic array processing architecture is also considered.This work was supported in part of the National Science Council of the R.O.C. under grant NSC80-E-SP-009-01A.This work was supported in part by a UC Micro grant and NSF grant NCR-8814407. 相似文献
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针对双基地多输入多输出(MIMO)雷达定位的实时性问题,提出了一种基于Toeplitz矩阵的目标快速定位算法。双基地MIMO雷达接收的信号往往是相干的,因此无法直接应用角度估计算法。首先通过接收的数据得到一组Toeplitz子矩阵,利用这组子矩阵重构得到协方差矩阵,其秩等于目标个数,达到解相干的目的。采用改进多级维纳滤波器(MSWF)的前向递推,不需要通过特征值分解,得到信号子空间,结合ESPRIT算法,估计出目标的发射角度(DOD)和接收角度(DOA)。算法通过构造Toeplitz矩阵解相干,仅改变矩阵结构,降低了计算复杂度,具有较好目标分辨力和解相干能力。 相似文献
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针对时间反转(TR)多输入多输出(MIMO)雷达多重信号分类(MUSIC)算法计算量庞大的问题,提出一种基于时间反转的MIMO雷达实值MUSIC算法。首先,通过采用降维思想对TR MIMO回波信号进行降维处理,来减少计算量;然后,为将协方差矩阵转化到实数域,构造酉变换矩阵进行实值变换;最后,分解出实值协方差矩阵的噪声子空间,构造谱函数估计信号波达角。相对于传统的MUSIC算法,该算法借助实值变换剔除了复数运算,极大地降低了计算量,而且不需要空间平滑降低阵列孔径就具有解相干的能力。仿真结果证实了算法的正确性。 相似文献
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Xianpeng WANG Yuehao GUO Mengxing HUANG Chong SHEN Chunjie CAO Wenlong FENG 《通信学报》2019,40(7):144-150
A robust angle estimation method for noncircular targets based on unitary tensor decomposition with mutual coupling in multiple-input multiple-output (MIMO) radar was proposed.Firstly,utilizing the banded symmetric Toeplitz structure of the mutual coupling matrix to eliminate the influence of unknown mutual coupling in tensor field.Then a special augmented tensor was constructed to capture the no circularity and its inherent tensor multidimensional structure of noncircular signals.And taking advantage of the centro-Hermitian characteristic of the augmented tensor to transform the sub-tensor into real-values tensor by the unitary transformation.Finally,the signal subspace estimation based on tensor was obtained by taking advantage of the higher-order singular value decomposition (HOSVD) technology,and then the direction-of-departure (DoD) and direction-of-arrival (DoA) estimation was obtained by utilizing the real-values subspace technology.Due to the consideration of both the noncircularity and multidimensional structure,the proposed algorithm has better recognition performance than the existing angle estimation methods.At the same time,the proposed algorithm only requires real-valued operations and has lower computational complexity.Simulation experiments verify the effectiveness and superiority of the proposed algorithm. 相似文献
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该文提出了一种基于QR分解的Power-ESPRIT (以下简称QP-ESPRIT算法) 新算法。首先使用采样数据协方差矩阵的幂(Power)获得噪声子空间的估计,然后对噪声子空间进行QR分解并使用R矩阵估计信源个数,提出了无特征分解的信源个数检测算法SDWED算法。进而,信号子空间的特征向量就可以由Q矩阵确定,从而应用ESPRIT算法获得信源波达方向的估计。该算法不需要预先知道信源个数的先验知识以及分离信号与噪声特征值的门限。在确定信源个数和子空间估计的同时,本文算法与传统的基于奇异值分解算法相比,具有近似性能时却拥有较低的计算复杂度。仿真结果证明了该方法的有效性。 相似文献