共查询到20条相似文献,搜索用时 31 毫秒
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Li Li Tian-shuang Qiu De-rui Song 《AEUE-International Journal of Electronics and Communications》2013,67(11):947-954
This paper takes the alpha-stable distribution as the noise model and works on the parameter estimation problem of wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system in the impulsive noise environment. In many applications, it is not appropriate to approximate the wideband signal by the narrowband model. Furthermore, the echo signal may be corrupted by the non-Gaussian noise. The conventional algorithms degenerate severely in the impulsive noise environment. Thus, this paper proposes a new wideband signal model and a novel method in wideband bistatic MIMO radar system. It combines the fractional lower order statistics and fractional power spectrum, for suppressing the impulse noise and estimating parameters of the target. Firstly, a new signal array model is proposed under the alpha-stable distribution noise model. Secondly, Doppler stretch and time delay are jointly estimated by peak searching of the FLOS-FPSD. Furthermore, two modified algorithms are proposed for the estimation of the direction-of-departure and direction-of-arrival, including the fractional power spectrum density based on MUSIC algorithm (FLOS-FPSD-MUSIC) and the fractional lower-order ambiguity function based on ESPRIT algorithm (FLOS-FPSD-ESPRIT). Simulation results are presented to verity the effectiveness of the proposed method. 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
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在相关信号子空间方法的基础上,本文提出了一种阵列宽带信号二维角度的估计方法。该方法首先利用虚拟互相关计算方法得到阵列输出的协方差矩阵,并构造出两个子阵(实际子阵和虚拟子阵);然后采用投影算子来形成聚焦矩阵,最后对聚焦后的协方差矩阵采用ESPRIT方法估计出宽带信号的二维到达角。这种方法能抑制非高斯噪声对算法的影响,并能扩展阵列孔径,且不需要进行角度预估计;估计出的二维角度能自动配对,提高了算法的实现速度。计算机仿真试验证实了该算法的有效性。 相似文献
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Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT) algorithm can estimate Direction-Of-Arrival(DOA) of coherent signal,but its performance can not reach full satisfaction.We reconstruct the received signal to form data model with multi-invariance property,and multi-invariance ESPRIT algorithm for coherent DOA estimation is proposed in this paper.The proposed algorithm can resolve the DOAs of coherent signals and performs better in DOA estimation than that of ESPRIT-like algorithm.Me... 相似文献
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Bao Zhiqiang Wu Shunjun Zhang Linrang 《电子科学学刊(英文版)》2007,24(5):655-661
In this paper,a low complexity ESPRIT algorithm based on power method and Orthogo- nal-triangular (QR) decomposition is presented for direction finding,which does not require a priori knowledge of source number and the predetermined threshold (separates the signal and noise ei- gen-values).Firstly,according to the estimation of noise subspace obtained by the power method,a novel source number detection method without eigen-decomposition is proposed based on QR de- composition.Furthermore,the eigenvectors of signal subspace can be determined according to Q matrix and then the directions of signals could be computed by the ESPRIT algorithm.To determine the source number and subspace,the computation complexity of the proposed algorithm is approximated as (2log_2 n 2.67)M~3,where n is the power of covariance matrix and M is the number of array ele- ments.Compared with the Single Vector Decomposition (SVD) based algorithm,it has a substantial computational saving with the approximation performance.The simulation results demonstrate its effectiveness and robustness. 相似文献
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URV ESPRIT for tracking time-varying signals 总被引:2,自引:0,他引:2
Liu K.J.R. O'Leary D.P. Stewart G.W. Wu Y.-J.J. 《Signal Processing, IEEE Transactions on》1994,42(12):3441-3448
ESPRIT is an algorithm for determining the fixed directions of arrival of a set of narrowband signals at an array of sensors. Unfortunately, its computational burden makes it unsuitable for real time processing of signals with time-varying directions of arrival. The authors develop a new implementation of ESPRIT that has potential for real time processing. It is based on a rank-revealing URV decomposition, rather than the eigendecomposition or singular value decomposition used in previous ESPRIT algorithms. The authors demonstrate its performance on simulated data representing both constant and time-varying signals. They find that the URV-based ESPRIT algorithm is effective for estimating time-varying directions-of-arrival at considerable computational savings over the SVD-based algorithm 相似文献
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推导了运动扩展目标在全去斜率体制下的回波信号形式,指出其为多分量多项式相位信号(mc-pps).分析了时频分析方法和多项式相位变换方法对该信号处理的不足,提出一种采用双混频实现扩展目标运动参数估计和和散射中心重构的新方法:通过对回波的双混频处理避免自相关处理带来的能量损失及分辨率降低;根据相关函数的功率谱特点,在频域抑制由多分量带来的交叉项干扰;通过循环估计减小参数估计误差的传播影响,最后利用ESPRIT超分辨估计方法提高参数估计精度.仿真结果表明该方法能有效提取目标的运动特征并能重构目标的一维散射中心. 相似文献
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ESPRIT is a high-resolution signal parameter estimation technique based on the translational invariance structure of a sensor array. Previous ESPRIT algorithms do not use the fact that the operator representing the phase delays between the two subarrays is unitary. The authors present a simple and efficient method to constrain the estimated phase factors to the unit circle, if centro-symmetric array configurations are used. Unitary ESPRIT, the resulting closed-form algorithm, has an ESPRIT-like structure except for the fact that it is formulated in terms of real-valued computations throughout. Since the dimension of the matrices is not increased, this completely real-valued algorithm achieves a substantial reduction of the computational complexity. Furthermore, Unitary ESPRIT incorporates forward-backward averaging, leading to an improved performance compared to the standard ESPRIT algorithm, especially for correlated source signals. Like standard ESPRIT, Unitary ESPRIT offers an inexpensive possibility to reconstruct the impinging wavefronts (signal copy). These signal estimates are more accurate, since Unitary ESPRIT improves the underlying signal subspace estimates. Simulations confirm that, even for uncorrelated signals, the standard ESPRIT algorithm needs twice the number of snapshots to achieve a precision comparable to that of Unitary ESPRIT. Thus, Unitary ESPRIT provides increased estimation accuracy with a reduced computational burden 相似文献
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酉ESPRIT超分辨ISAR成像方法 总被引:1,自引:0,他引:1
针对ESPRIT超分辨成像方法没有利用复数共轭数据且难以确定散射点数目的不足,提出了采用酉ESPRIT实现ISAR超分辨成像的新方法.该方法利用改进的盖式圆盘方法确定散射中心的数目,克服了ESPRIT方法中无法确定散射中心数目的缺点.通过合成复观测数据及其共轭,提高了ESPRIT超分辨成像的分辨率.构造了中心复共轭对称矩阵,有效降低了计算量.利用仿真数据和实测数据对该方法进行了验证,结果表明该方法不但具有更优的抗噪性能和分辨率,也具有更高的运算效率. 相似文献
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结合分布式阵列和双基地多输入多输出(Multiple-Input Multiple-Output, MIMO)雷达的特点, 提出了一种新的双基地分布式阵列MIMO雷达的接收角(Direction of Arrival, DOA)和发射角(Direction of Departure, DOD)估计方法.根据发射阵列和接收阵列的空域旋转不变特性, 利用旋转不变估计技术(Estimation of Signal Parameters via Rotational Invariance Techniques, ESPRIT)获取无模糊DOA粗估计和高精度周期性模糊的DOA、DOD精估计; 再利用无模糊DOA粗估计、目标的双基地距离信息以及双基地MIMO雷达的几何特点, 解除DOA、DOD精估计的周期性模糊, 得到高精度且无模糊的DOA和DOD估计.最后, 根据ESPRIT算法原理和估计误差的概率统计特性进行算法的性能分析, 给出算法基线模糊门限的近似计算方法.该算法有效地放宽了发射阵列孔径扩展程度的限制, 从而提高了阵列在大孔径下的角度估计精度, 且能够实现DOA和DOD估计的自动配对.仿真结果验证了所提算法和性能分析方法的有效性. 相似文献
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摘 要:提出了基于Gerschgorin圆盘理论的宽带频谱感知算法:Gerschgorin似然估计算法和Gerschgorin圆盘半径迭代算法。通过在宽带频谱感知中引入Gerschgorin圆盘理论,将认知无线电用户频谱观测数据中噪声圆盘空间和信号圆盘空间进行分离,并基于对主用户所占用子频段集合势的估计,实现对宽带授权频谱中多个子频段状态的监测。为了进一步提高感知性能,还提出利用宽带频谱中主用户信号占用子频段的连续性特性改善算法性能。理论推导和仿真结果表明,在信噪比较小时,Gerschgorin似然估计算法较基于信息论准则的宽带感知算法具有更稳定的检测性能;Gerschgorin圆盘半径迭代算法与传统能量检测方法相比,优势在于不依赖任何噪声功率先验信息,且在采样次数较少情况下的感知错误率较小。因此,基于Gerschgorin圆盘理论的频谱感知更适合于实际CR系统,可为宽带频谱感知提供行之有效的算法实施方案。 相似文献