基于多级维纳滤波的ESPRIT算法

因奇异值分解引入了庞大的计算量,子空间分解类的测向算法在工程中难以实现实时处理.多级维纳滤波(MSWF)算法,避免了奇异值分解运算,有效地减少了运算量.通过对多级维纳滤波算法进行改进,提出了一种信源数目的估计方法.与传统多级维纳滤波算法相比,该方法提高了测向精度.通过仿真证明了该算法的有效性.     

非圆信号多级维纳滤波MUSIC测向算法

为降低非圆信号的MUSIC(记为NC-MUSIC)测向算法的计算量,提出了基于多级维纳滤波的NC-MUSIC算法.首先,该算法将非圆信号特性用于多级维纳滤波算法,构造出扩展阵列输出矩阵,利用多级维纳滤波的递推特性求出信号子空间,而不需要估计样本协方差矩阵和对其特征值分解;其次,为了进一步降低算法的计算量,推导出信号子空间的谱峰一维搜索公式进行非圆信号谱峰搜索的计算,快速估算出目标的方位值.仿真结果和计算复杂度分析表明,新算法不但在均方根误差性能上与其他快速算法相似,均接近于NC-MUSIC算法,具有良好的估计性能,而且降低了NC-MUSIC算法的计算最,使其计算复杂度小于非圆信号扩展传播算子快速测向算法的计算复杂度.证实了新算法快速有效的估计性能.     

多级维纳滤波在子空间类测向算法中的应用

以MUSIC为代表的子空间类测向算法运算量很大。利用多级维纳滤波的正交分解特性,提出一种快速估计子空间的方法,避免了协方差矩阵的特征值分解,降低该算法的运算复杂度。采用多级维纳滤波的前向递推,将予空间的估计变成一系列的简单运算,提高处理速度．     

一种基于L阵的二维解相干测向算法

本文对高斯白噪声环境下基于L型阵列二维测向的ESPRIT算法进行了改进.该算法利用阵列结构特点通过平滑原理获得3个互相关矩阵,然后由3个矩阵构造一个特殊大矩阵并对其进行奇异值分解来估计信号子空间,最后利用2D-ESPRIT方法实现二维测向.该算法估计精度高,运算量小,能够对相干信号进行估计.     

一种多路并行盲搜索的空时二维抗干扰算法

针对卫星导航抗干扰中传统的空时自适应处理算法运算量大、处理速度较慢的问题,在介绍多级维纳滤波基本原理的基础上,提出了一种多路并行的盲搜索空时二维抗干扰自适应处理算法。该方法采用多级维纳滤波降维处理的方法求解信号子空间和干扰子空间,从而使输出信号的信干噪比达到最优,实现干扰的有效抑制。仿真结果表明,该算法具有较好的抗干扰性能,且运算量较低,有较好的工程应用前景。     

一种不需要特征值分解的ESPRIT方法

多级维纳滤波是一种降维算法,本文提出了一种将多级维纳滤波引入到ESPRIT算法的预处理模型,提出了一种构造预处理滤波器的方法,提出了适合于ESPRIT方法的多级维纳滤波的结构。本文提出的方法避免了采样数据二阶统计的特征值分解,降低了运算量。本文方法具有一般性,适合于基于子空间方法的一大类DOA估计。仿真结果证明了方法的有效性。     

信号DOA和极化参数的自适应估计

运用ESPRIT算法进行信号参数的估计,关键是对信号子空间的估计。在实际运用中,接收到的信号的参数往往是随时间变化的,因此要得到信号参数的实时估计值就需要根据阵列的接收数据对信号子空间进行更新。分析了如何运用ESPRIT算法得到信号的DOA和极化参数,并在矩阵扰动理论的基础上,利用矩阵特征分解一阶修正方法更新特征值和特征向量,从而使得ESPRIT算法能够自适应地估计信号DOA和极化参数。最后通过Matlab仿真验证了该方法的有效性。     

基于多级维纳滤波的循环平稳信号阵列测向方法

针对现有的循环平稳信号阵列测向方法因存在计算量大而无法直接应用于工程实践的问题,通过引入子空间快速估计的多级维纳滤波思想,与Cyclic MUSIC和SC—SSF方法相结合,提出了基于多级维纳滤波的循环平稳信号阵列测向的快速实现方法,计算量分析和仿真结果表明,新方法在性能没有受到显著影响的情况下极大地提高了计算效率。     

基于辅助矢量基的超分辨快速测向算法

以MUSIC和ESPRIT为代表的空间谱估计测向算法需要对矩阵进行特征分解或奇异值分解。当阵列数量增加时,矩阵特征分解将耗费大量的运算资源。给出了一种基于辅助矢量基的超分辨快速测向算法,通过计算一组辅助矢量基构造子空间进行测向,获得了较好的测向精度,避免了矩阵的特征分解,从而降低了计算复杂度,最后通过仿真示例验证了该方法的有效性和可行性。     

基于ESPRIT宽带信号测向技术研究

研究了基于ESPRIT宽带信号测向技术,采用信号子空间变换方法分别对2个平移矩阵聚焦处理,并利用窄带ESPRIT测向方法计算出来波方向,提出利用ESPRIT与聚焦处理相结合测向的方法,解决了ESPRIT宽带信号测向精度差问题。通过聚焦处理有效抑制噪声,提高信噪比,从而获得高精度、高分辨率的渐进无偏估计信号方向。计算机仿真验证了算法的有效性。     

基于分数阶矩的测向算法研究

在SαS噪声环境中基于阵列输出信号分数阶矩的TLS-ESPRIT测向算法，该算法在保持了原TLS-ESPRIT算法无需谱峰搜索，计算量和存储量小等优点的基础上，对加性SαS噪声有较好的抑制作用，扩展了ESPRIT算法的信号模型和应用环境，计算机仿真验证了该算法的何行性和有效性。     

COMPENSATION FOR THE MUTUAL COUPLING EFFECT FOR THE ESPRIT ALGORITHM IN SINGLE SNAPSHOT ARRAY PROCESSING

An effective method is introduced to compensate the effects of mutual coupling for the Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) direction finding algorithm in application of signal snapshot array processing.Changing the covariance matrix into a Teoplitz matrix can achieve high resolution in the Direction Of Arrive (DOA) estimation.How the mutual coupling affects the array antennas has been discussed and a new definition of mutual im- pedance has been used to characterize the mutual coupling effects between the array elements.Based on the new mutual impedance matrix,a practical method is presented to eliminate the effects of mutual coupling for ESPRIT in the single snapshot data processing.The simulation results show that, this new method not only properly reduces the effects of mutual coupling,but also maintains its steady performance even for weak signals.     

基于带通欠采样的脉冲超宽带信号重建算法性能研究

从脉冲超宽带(PPM-UWB)信号解调的角度, 该文探讨了PPM-UWB带通欠采样信号处理的信号重建算法, 并将零化滤波算法和ESPRIT算法进行了仿真对比。ESPRIT算法与零化滤波算法相比需要的最小带宽要求较大, 但是在同等带宽条件下, ESPRIT算法具有更好的抗噪声性能。      

Multiresolution ESPRIT algorithm

Multiresolution ESPRIT is an extension of the ESPRIT direction finding algorithm to antenna arrays with multiple baselines. A short (half wavelength) baseline is necessary to avoid aliasing, and a long baseline is preferred for accuracy. The MR-ESPRIT algorithm allows the combination of both estimates. The ratio of the longest baseline to the shortest one is a measure of the gain in accuracy. Because of various factors, including noise, signal bandwidth, and measurement error, the achievable gain in accuracy is bounded     

一种低复杂度的ESPRIT新算法

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。     

Frequency-Azimuth-Elevation Determination with a Single Acoustic Vector-Sensor Involved in a Reflecting Boundary

The temporally regularized multiresolution ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is proposed to exploit the second-order information present in the superposition of incidence of direct and reflected monochromatic acoustic waves for uni-vector-sensor direction finding in the presence of a reflecting boundary. The data are organized such that the phase shifts for frequency estimation of each signal corresponding to two distinct sampling rates are separately embedded in the modulus and argument of the ESPRIT eigenvalue, whereas the direction cosines for azimuth-elevation direction-of-arrival (DOA) estimation dwell in the associated ESPRIT eigenvector, and thus the matching procedure for aligning the output of multidimensional and multi-invariant data manipulation is avoided. The temporal multiresolution herein realized is iteration free and needs merely one lower-dimensional eigendecomposition. The simplified version of the presented method offers a similar performance while requiring only two time-delayed data sets and thus has a comparable computational complexity with the traditional single resolution ESPRIT. This ESPRIT-type method is also blind to the reflection coefficient which generally depends on the boundary nature, medium property, and signal parameters still to be estimated, viz. DOAs and signal frequencies. Simulation results are included to validate the proposed algorithm.     

共轭增强ESPRIT算法

提出了共轭增强ESPRIT（CA-ESPRIT）算法，利用阵列输出的延迟相关函数及其共轭形成伪阵列输出，从而得到伪协方差矩阵，对其进行特征分解，用ESPRIT算法得到波迭方向。仿真实验表明，新算法可对多于阵元数的信号进行测向，其测角精度和分辨能力优于ESPRIT算法，运行时间小于有相同阵列扩展能力的MUSIC—like算法。     

基于双L型阵的二维测向算法

提出了一种基于双L型阵的二维测向算法。通过定义新的三维波达方向角,同时利用旋转不变算法获得每一维入射角的独立估计,再由波达方向角之间的约束关系进行配对,提高了测向精度与二维角成功配对概率,改善了双L阵二维测向精度对来波方向敏感的问题。计算机仿真结果表明:所提算法在观测的区域内均具有较高测向精度,特别是在仰角较小时较传统算法其测向精度有较大提高,在低信噪比情况下与传统算法比较提高了二维测向中的角度配对成功概率。     

2D DOA and Frequency Estimation Method with One Vector-Sensor and Two Pressure Sensors Based on ESPRIT and Signal Power

We use one vector and two pressure sensors to form a sparse large aperture L-shape array for high performance two-dimensional (2D) direction of arrival (DOA) and frequency estimation. Because the number of sensors is small and there is only one vector sensor in the presented array, thus, the installation of sensors in the array is simpler and installation error is smaller, than the conventional array. Meanwhile, a high performance 2D DOA and frequency estimation method is presented. Firstly, utilizing single vector sensor and based on the ESPRIT, a group coarse 2D DOA and frequency parameters are obtained. Secondly, to restrain space noise or interference, a matrix filter is utilized to process the covariance matrix which comes from sensor array, so as to form a new covariance matrix which possesses high signal to noise ratio. Thirdly, utilizing the new covariance matrix and based on the ESPRIT again, accurate but ambiguity angles estimates are obtained. Fourthly, one signal power estimator and one optimization method are presented to solve the angle ambiguity and frequency ambiguity problems, respectively. The proposed method gains a high performance 2D DOA and frequency estimation results. Numerical simulations are performed to verify the feasibility of the proposed method.