DOA estimation of noncircular signals for coprime linear array via locally reduced-dimensional Capon

We investigate the issue of direction of arrival (DOA) estimation of noncircular signals for coprime linear array (CLA). The noncircular property enhances the degree of freedom and improves angle estimation performance, but it leads to a more complex angle ambiguity problem. To eliminate ambiguity, we theoretically prove that the actual DOAs of noncircular signals can be uniquely estimated by finding the coincide results from the two decomposed subarrays based on the coprimeness. We propose a locally reduced-dimensional (RD) Capon algorithm for DOA estimation of noncircular signals for CLA. The RD processing is used in the proposed algorithm to avoid two dimensional (2D) spectral peak search, and coprimeness is employed to avoid the global spectral peak search. The proposed algorithm requires one-dimensional locally spectral peak search, and it has very low computational complexity. Furthermore, the proposed algorithm needs no prior knowledge of the number of sources. We also derive the Crámer-Rao bound of DOA estimation of noncircular signals in CLA. Numerical simulation results demonstrate the effectiveness and superiority of the algorithm.     

宽带循环平稳信号的二维空间谱估计

本文提出了一种新的宽带二维波达方向估计方法。理论分析表明,该方法不需要进行二维搜索,既适用于宽带信号,也适用于窄带信号,且能够实现二维参数的自动配对。通过利用循环平稳特性,该方法能够抑制宽带干扰和加性噪声的影响,从而大大提高了算法的信号检测能力。     

均匀圆阵部分阵元失效情况下的DOA估计方法

在空间谱估计中,均匀圆阵(Uniform Circular Array--UCA)具有诸多优点,其得到广泛的应用.但在用MUSIC 算法测向时,一旦某一个或几个阵元通道失效,则通道数据变成无效数据,导致测向性能严重恶化,甚至完全失效.本文对在均匀圆阵部分通道失效的情况下,利用均匀圆阵其余阵元数据实现对信号来波方向进行有效估计的方法进行了分析和验证.其原理在于,直接将失效阵元进行隔离,利用剩余阵元形成的非均匀圆阵,进行MUSIC算法测向.该方法能在较高信噪比条件下实现和原阵列几乎相同的估计精度,在较低信噪比、信号数较小的条件下,也能取得良好的估计性能,大大增强了整个阵列谱估计的稳健性和鲁棒性.     

Efficient 2-D DOA and frequency estimation for L-shaped array via RD-PM

This paper addresses the issue of joint two-dimensional direction of arrival (2-D DOA) and frequency estimation via reduced-dimensional propagator method (RD-PM) with L-shaped array. The proposed algorithm has no need for eigenvalue decomposition of the sample covariance matrix and simplifies three-dimensional global spectral search within the three-dimensional propagator method (3-D PM) to one-dimensional local search, which greatly reduces computational complexity. Furthermore, the proposed algorithm can work under both uniform and non-uniform L-shaped array and can achieve paired 2-D DOA and frequency estimates automatically. In addition, the 2-D DOA and frequency estimation performance for the proposed method is approximate 3-D PM algorithm and parallel factor (PARAFAC) method but exceeds the estimating signal parameters via rotational invariance techniques (ESPRIT) algorithm and improved PM algorithm. The detailed derivation of Cram´er-Rao bound (CRB) is provided and the simulation results demonstrate the effectiveness and superiority of the proposed approach.     

波达方向估计中的宽带信号个数检测新方法

在进行波达方向估计时,往往要对信号个数进行判断,传统的宽带信号个数检测方法需要在每个频点上进行多次采样,否则无法正确完成测向.针对此问题,提出了一种基于Bootstrap准则实现的宽带信号个数检测新方法.将宽带信号划分为若干个互不重叠的子带部分,之后对每个子带信号进行特征分解,利用特征值对相应的特征向量进行加权,再通过Bootstrap准则构造新的信号重采样矩阵,用聚类的方法判断出该子带上的信号个数,最后将各个子带上的结果进行综合判断出宽带信号个数.所提方法回避了聚焦的过程,且在非高斯噪声背景下也有较高的估计成功概率,尤其是在小快拍数下有着较好的估计性能,仿真结果证明了该方法的性能.     

Direction of arrival estimation of non-Gaussian signals for nested arrays: Applying fourth-order difference co-array and the successive method

Herein, we estimate the direction of arrival (DOA) of non-Gaussian signals for nested arrays (NAs) by implementing the fourth-order difference co-array (FODC) and successive methods. In particular, considering the property of the fourth-order cumulant (FOC), we first construct the FODC of the NA, which can obtain O(N⁴) virtual elements using N physical sensors, whereas conventional FOC methods can only obtain O(N²) virtual elements. In addition, the closed-form expression of FODC is presented to verify the enhanced degrees of freedom (DOFs). Subsequently, we exploit the vectorized FOC (VFOC) matrix to match the FODC of the NA. Notably, the VFOC matrix is a single snapshot vector, and the initial DOA estimates can be obtained via the discrete Fourier transform method under the underdetermined correlation matrix condition, which utilizes the complete DOFs of the FODC. Finally, fine estimates are obtained through the spatial smoothing-Capon method with partial spectrum searching. Numerical simulation verifies the effectiveness and superiority of the proposed method.     

短快拍条件下均匀矩形阵中的二维DOA估计

二维波达方向（Direction of Arrival,DOA）估计能获取比一维DOA估计更多的空间位置信息,但是二维多重信号分类(Multiple Signal Classification,MUSIC)、二维子空间旋转不变估计技术(Estimation Signal Parameter via Rotational Invariance Techniques,ESPRIT）等经典算法依赖于大量的快拍数据,当快拍数据不足时估计性能严重下降甚至失效。针对上述问题,将迭代自适应方法拓展到二维DOA估计,提出了一种适用于矩形面阵的二维DOA估计算法,首先利用加权最小二乘法估计出信号幅值,然后利用循环迭代技术对估计结果进行更新。由于每次估计结果均来自上一次迭代,而不依赖于快拍数据,因此该算法在短快拍条件下具有很高的估计精度和分辨率。仿真结果表明,在短快拍条件下,该算法具有优越的估计性能。     

DOA estimation method of weak sources for an array antenna under strong interference conditions

The concept of a preserving source orthogonality and characteristic beam is defined according to an array data model. It is proven theoretically that the corresponding eigenvectors maintain the preserving orthogonality when the powers and the angle intervals between the signals are large. The theory is then applied to the direction of arrival (DOA) estimation for the array antenna in the presence of strong interference. A novel DOA estimation algorithm based on the elimination of the eigenvectors of interference is proposed. The simulation results and comparison of the jamming jam method (JJM) algorithm show that the proposed algorithm does not require the position of the interference source to be known. Moreover, its interference suppression ability and statistical estimation performance are superior to those of the JJM, and thus, it is more suitable for low SNR and small angle intervals.     

An efficient DOA estimation method in multipath environment

An efficient direction of arrival (DOA) estimation method is proposed with uniform linear array (ULA) in multipath environment. By applying a transformation, we can convert a constructed complex matrix to a real one, and then utilize the real matrix combined with our proposed criterion to estimate the DOAs of uncorrelated signals. Afterwards, the contributions of uncorrelated signals are eliminated, and then several new matrices without the information of uncorrelated signals are constructed to resolve the remaining coherent signals. The proposed estimation method overcomes the shortcomings of the existing methods and has satisfactory performance. Simulation results confirm the theoretical analysis and show the effectiveness of the proposed method.     

Off-grid direction-of-arrival estimation for wideband noncircular sources

Researchers have recently shown an increased interest in estimating the direction-of-arrival (DOA) of wideband noncircular sources, but existing studies have been restricted to subspace-based methods. An off-grid sparse recovery-based algorithm is proposed in this paper to improve the accuracy of existing algorithms in low signal-to-noise ratio situations. The covariance and pseudo covariance matrices can be jointly represented subject to block sparsity constraints by taking advantage of the joint sparsity between signal components and bias. Furthermore, the estimation problem is transformed into a single measurement vector problem utilizing the focused operation, resulting in a significant reduction in computational complexity. The proposed algorithm's error threshold and the Cramer–Rao bound for wideband noncircular DOA estimation are deduced in detail. The proposed algorithm's effectiveness and feasibility are demonstrated by simulation results.     

分布式嵌套阵列及其DOA估计

提出了一种分布式嵌套阵列天线结构,由两个相互独立的四级嵌套子阵构成。两个子阵间存在一个基线长度,且满足一定条件。对该阵列天线接收到的信号进行高阶累积量和Khatri-Rao积运算可以得到三个完全相同的均匀直线阵列天线结构。针对新得到的阵列天线结构,使用基于空间平滑技术的双尺度酉旋转不变子空间( ESPRIT)波达方向( DOA)估计算法对信号进行DOA估计。该方法可以有效地提高阵列天线的自由度,进而达到提高估计精度的目地。仿真结果证明了基于所提出阵列天线结构的DOA估计方法的有效性。     

Off‐grid DoA estimation method of wideband signals

In this paper, an off‐grid direction of arrival (DoA) estimation method is proposed for wideband signals. This method is based on the sparse representation (SR) of the array covariance matrix. Similar to the time domain DoA estimation methods, the correlation function of the sources was assumed to be the same and known. A new measurement vector is obtained using the lower‐left triangular elements of the covariance matrix. The DoAs are estimated by quantizing the entire range of continuous angle space into discrete grid points. However, the exact DoAs may be located between two grid points; therefore, this estimation has errors. The accuracy of DoA estimation is improved by the minimization of the difference between the new measurement vector and its estimated values. Simulation results revealed that the proposed method can enhance the DoA estimation accuracy of wideband signals.     

均匀圆阵二维波达角估计的Cramer-Rao界

均匀圆阵(UCA)是一种应用广泛的具有二位波达角估计能力的平面阵列。为了从理论上分析不同阵列参数下到达波方位角(AOA)、仰角估计精度,推导了均匀圆阵二维波达角估计的性能界,以此为基础分析了阵列孔径、阵元个数、快拍数以及来波仰角高低与到达角估计精度的关系,并通过对UCA-MUSIC算法计算机仿真验证了推导结果的正确性。研究结果为波达角估计类算法提供了可供参考的性能下界,圆阵设计时也不再需要大量的Monte Carlo仿真试验确定阵列参数,可直接从估计精度表达式中获得。     

基于虚拟阵列的非圆信号DOA估计

针对传统的子空间类波达方向（Direction of Arrival,DOA）估计算法只适用于入射信号个数少于天线数的局限性,利用现代通信系统中常用的非圆信号实值特性,提出了一种虚拟阵列多重信号分类法（Virtual Array Based Multiple Signal Classification,VA-MUSIC）。该方法通过对阵列输出信号进行共轭重构和合并,获得虚拟阵列来增加阵列的有效孔径。更进一步,结合空间平滑技术有效地解决了相干信号的DOA估计问题。与传统的MUSIC算法相比,新算法不仅可以增加最大可估计信源数,而且在DOA估计精度、信号源角分辨能力等方面均有明显的优势。计算机仿真验证了该算法的有效性和优越性。     

基于十字阵的MIMO雷达的二维DOA估计

多输入多输出（MIMO）雷达使用多个天线同时发射独立波形,在不同位置的目标回波彼此线性独立,以获得较好的空间分辨率。文章提出了基于收发不共位的线阵在水平面内构成十字阵的MIMO雷达信号模型;研究利用MUSIC算法来估计该模型下的MIMO雷达的二维波达角;分析了基于均匀十字阵的MIMO雷达的优越性,并探讨了十字阵MIMO雷达性能与阵元间距的关系,仿真表明,在满足远场条件下,均匀十字阵比均匀线阵可以估计更多的目标而且精度更高;通过非均匀布阵,可以进一步提高MIMO雷达的二维波达角的估计精度。     

基于Y形阵的空时二维波达方向估计

提出了一种适用于Y形阵的空时二维波达方向估计方法,在低信噪比下实现了无模糊的二维波达方向估计。该方法利用了Y形阵的特性,具有较好的稳定性和较小的估计方差。仿真结果证明了本方法的有效性。     

基于多项式展开宽带信号二维来波方向估计

本文提出了一种新的宽带信号二维来波方向(2D-DOA)估计方法。该方法通过对阵列方向矩进行多项式展开来构造聚焦矩阵,它不需要进行角度预估计和信号个数估计。计算机仿真试验证实了方法的有效性。     

L型阵列互耦条件下的二维波达方向估计

针对L型阵列,提出一种去互耦算法.该算法在L型阵列的两均匀线阵上分别取受互耦影响一致的阵元,则其理想导向向量可与互耦参数剥离,用其中一组阵元输出的协方差阵和两组阵元输出的互协方差阵构建矩阵,根据其传播算子构成的信号子空间和阵元导向向量张成同一空间以及均匀线阵的旋转不变特性得到两个与方向角和俯仰角相关的信息参量.在这两参量配对时,只需对包含信息参量的其中一个矩阵进行一次特征值分解以及简单的除法运算即可实现.理论和仿真表明,该算法无需谱峰搜索,只需一次特征分解,有效抑制了互耦影响,测量精度高.     

Two-dimensional DOA estimation of coherent signals using acoustic vector sensor array

In this paper, we present two new methods for estimating two-dimensional (2-D) direction-of-arrival (DOA) of narrowband coherent (or highly correlated) signals using an L-shaped array of acoustic vector sensors. We decorrelate the coherency of the signals and reconstruct the signal subspace using cross-correlation matrix, and then the ESPRIT and propagator methods are applied to estimate the azimuth and elevation angles. The ESPRIT technique is based on the shift invariance property of array geometry and the propagator method is based on partitioning of the cross-correlation matrix. The propagator method is computationally efficient and requires only linear operations. Moreover, it does not require any eigendecomposition or singular-value decomposition as for the ESPRIT method. These two techniques are direct methods which do not require any 2-D iterative search for estimating the azimuth and the elevation angles. Simulation results are presented to demonstrate the performance of the proposed methods.     

共形阵列非圆信号波达方向估计算法

受共形载体变曲率结构的影响,各天线单元指向不尽相同,使得共形天线阵列呈现极化多样性。因此,共形天线阵列的建模过程中需考虑不同阵元的极化响应特性。基于柱面共形天线阵列的快拍数据模型,利用非圆信号的特性对阵列输出进行扩展,基于秩亏理论和子空间原理实现信号波达方向（DOA）估计,所提方法估计精度高,不需要参数配对。存在相干信源时,提出对扩展后的虚拟阵列进行划分,对划分出的子阵进行虚拟的空间平滑,实现解相干的预处理操作。仿真结果表明该方法能有效应用于柱面共形阵列非圆信号DOA估计,并提高了空间分辨率。