Low-Complexity Estimation of the Nominal Azimuth and Elevation for Incoherently Distributed Sources

This paper develops a new technique for estimating the two-dimensional direction-of-arrivals (DOAs) of incoherently distributed (ID) sources, which can estimate effectively the nominal azimuth and nominal elevation of multiple ID sources at the cost of less computational complexity. Using a pair of parallel uniform linear arrays (ULAs), a new approach for 2D DOA estimation of multiple ID sources is proposed. The proposed method firstly estimates the nominal elevation by the modified TLS-ESPRIT method, which is based on the approximate rotational invariance property with respect to the nominal elevation between two closely parallel ULAs. And then with the help of the nominal elevation estimates, the nominal azimuth is estimated by one-dimensional searching. Without multi-dimensional searching, the proposed method has significantly reduced the computational cost compared with the existing methods. Simulation results indicate that the proposed method can exhibit a good performance and be applied to the multisource scenario where different sources may have different angular distribution shapes.     

Simplified Estimation of 2D DOA for Coherently Distributed Sources

In mobile communications, local scattering in the vicinity of the mobile results in angular spreading as seen from a base station antenna array. In this paper, we consider the problem of estimating the two-dimensional (azimuth and elevation) direction-of-arrival (DOA) parameters of spatially distributed sources. Based on double parallel uniform linear arrays (ULAs), a simplified method without spectrum-peak searching is proposed for the 2D DOA estimation of multiple coherently distributed (CD) sources. The proposed method firstly obtains two approximate rotational invariance relations with respect to the nominal DOAs of CD sources by using one-order Taylor approximation to the generalized steering vectors (GSVs) of two pairs of shifted subarrays. And then a new ESPRIT-based method is utilized to estimate the nominal azimuth DOA and nominal elevation DOA. In addition, a simple parameter matching approach is also given. Compared with the conventional methods, our method has significantly reduced the computational cost and can sustain the estimation performance within a tolerable level. Moreover, our method is a blind estimator without any prior knowledge about angular distribution shape. Numerical examples illustrate the performance of the method.     

Fast DOA estimation of incoherently distributed sources by novel propagator

A low-complexity algorithm is presented for the estimation of the nominal direction-of-arrivals (DOAs) of incoherently distributed (ID) sources. The presented algorithm estimates the nominal DOAs of ID sources by a novel propagator method which makes use of the approximate rotational invariance relationship between two closely spaced identical uniform linear arrays. Without any search and the eigendecomposition of the sample covariance matrix, our algorithm can provide lower computational complexity than other known methods. In addition, it can be applied to the multisource scenario with different angular distribution shapes. Simulation results prove the effectiveness of the presented algorithm.     

三平行线阵中基于改进传播算子的二维DOA估计方法

提出了一种三平行线阵中基于改进传播算子的二维波达方向估计方法。该方法针对三平行阵列的结构特点,利用三平行线阵中两个相互垂直的双平行线阵,分别构造一个扩展传播矩阵,求得旋转矩阵。然后根据三平行线阵的特性,对分别得到的旋转矩阵进行配对。最后利用配对后的旋转矩阵,联合估计信号的方位角和俯仰角。该方法当俯仰角在70°~ 90°之间时不会出现角度估计失效问题,充分利用了所有阵元信息,提高了角度估计性能,而且具有更低的计算复杂度。仿真验证了提出方法的有效性。      

基于拉伸式COLD 传感器的DOA 和极化参数估计*

同点正交配置磁环和电偶极子(Co-centered orthogonal loop and dipole, COLD)是一种最常用的二分量 电磁矢量传感器,但是COLD 传感器没有充分利用磁环和电偶极子分量的空间信息。本文针对由COLD 传感器组成 的均匀线阵(Uniform linear array ,ULA),将所有磁环和电偶极子分量分别沿两个正交方向均匀拉伸,形成L 形阵,扩 展阵列的空间孔径,并提出了基于广义旋转不变的降维多重信号分类算法(Dimension reduction multiple signal classi fication method based on generalized rotational invariance, GRIDR-MUSIC)。所提算法利用L 形阵的几何构形,将导向 矢量分隔成三部分,通过两个正交ULA 的广义旋转不变结构,分别估计各个部分,使得波达角(Direction of arrival)和 极化参数仅需一维谱峰搜索就可以估计得到,且无需参数匹配。最后,仿真实验验证了所提算法的有效性。     

相干分布源DOA与角度扩展估计求根算法

论文提出了一种具有低复杂度的相干分布源波达方向和角度扩展估计算法。该算法将点源模型中的求根MUSIC算法推广应用至分布源模型。利用空间频率下的相干分布源广义方向矢量可以表示成参数去耦形式的结构特点,并根据相干分布源的角信号密度函数,构造参数估计的多项式求根形式,然后通过交替迭代的求根方法得到分布源的中心波达方向和角度扩展的估计值。该算法参数估计性能与DSPE算法相当,其计算复杂度要远小于DSPE算法,并且适用于不同分布类型的相干分布源同时存在的情况。计算机仿真验证了算法的性能。      

基于高阶ESPRIT的单声矢量水听器近场声源定位

为避免传统近场定位算法需要三维搜索,计算量大的问题,该文结合高阶累积量提出一种适用于单矢量水听器近场声源定位的旋转不变子空间(ESPRIT)算法。首先通过定义一系列的四阶累积量矩阵,获得了3个不变性矩阵,然后从这些不变矩阵中提取近场源的位置信息,该方法可以得到目标的方位角、俯仰角和距离的封闭形式的解。最后通过仿真验证了本算法的有效性。     

基于双平行线阵的相干分布源二维DOA估计

针对现有相干分布源二维波达方向(DOA)估计算法存在的一些问题,基于双平行均匀线阵提出了一种相干分布源二维DOA估计新算法。利用旋转不变的思想并结合传播算子法来估计相干分布源的二维中心DOA。无需谱搜索和对样本协方差矩阵做特征分解,和传统算法相比,其计算复杂度更低。此外,还给出了详细的参数配对过程,因而能够应用于多源场合。算法在小角度扩展条件下估计性能良好,其性能甚至接近于一维交替搜索算法。算法还是一种对角分布先验知识盲的估计。仿真结果证实了算法的有效性。     

相干分布式信源二维波达方向估计算法

针对相干分布式信源二维波达方向估计算法多采用谱峰搜索导致计算复杂度较大的问题,该文提出了一种二维波达方向分离估计算法。该算法通过将积分形式的相干分布式信源方向向量化简为点信源方向向量与实向量的Schur-Hadamard积,对子阵X接收的数据构造二阶统计量;利用传播因子最小二乘估计子阵X与Z,X与W之间的旋转不变矩阵。由二阶统计量与旋转不变矩阵分别估计方位角与仰角,对于接近90的仰角也可给出有效的估计。与传统子空间算法相比,无需任何谱峰搜索和特征值分解,降低了计算复杂度。仿真实验表明了所提算法的有效性。     

Computationally efficient DOA estimation for coprime linear array: a successive signal subspace fitting algorithm

ABSTRACT

In this paper, direction of arrival (DOA) estimation of multiple signals with coprime array is investigated and signal subspace fitting (SSF) method is linked to the coprime array, which achieves a better DOA estimation performance than the traditional uniform array. While the SSF method requires expensive computational cost in the case of multiple signals due to the multidimensional global angular searching, we propose a successive SSF (S-SSF) algorithm from a computationally efficient perspective. In the proposed algorithm, we employ rotational invariance and coprime property to obtain the initial estimates. Then, via a successive scheme, we transform the traditional multidimensional global angular searching problem into one-dimensional partial angular searching one. Consequently, the computational complexity has been significantly reduced. Specifically, the proposed S-SSF algorithm can obtain almost the same DOA estimation performance as SSF but with remarkably lower complexity. Finally, Cramer-Rao Bound (CRB) is provided and numerical simulations demonstrate the effectiveness of the proposed algorithm.     

Novel Blind Carrier Frequency Offset Estimation Algorithm for OFDM System Via Generalized Precoding

In this letter, we develop a blind carrier frequency offset (CFO) algorithm for orthogonal frequency division multiplexing (OFDM) systems by utilizing a generalized precoding. Generalized precoding is employed to obtain multiple covariance matrices, and then a CFO estimation algorithm for OFDM system using joint diagonalization is proposed. Comparing to estimation of signal parameters via rotational invariance techniques (ESPRIT) method, the algorithm that we presented has improved CFO estimation performance. Furthermore, our algorithm even works well without virtual carrier. Simulation results illustrate performance of this algorithm.     

基于对称旋转不变性的非圆相干分布源直接定位算法

针对现有相干分布源直接定位方法中存在的依赖分布模型、计算复杂等问题,该文提出一种基于非圆信号特征的对称旋转不变直接定位算法。该方法首先根据分布源参数化假设建立基于数据域信息的直接位置估计模型,并利用非圆信号特征扩展接收信号的协方差矩阵。然后针对中心对称阵列,证明了相干分布源的确定性角信号分布函数矢量具有对称特性,基于这一特征建立了扩展方向矢量的旋转不变关系;构造了融合多个观测站信息的目标函数,直接估计目标位置,避免了对分布模型的依赖,且降低了待估计参数维度。仿真结果表明,与现有相干分布源定位算法相比,所提算法提高了分布源位置估计精度和效率,避免了对分布模型的依赖,更具实用价值。     

A Fast Decoupled Nominal 2-D Direction-of-Arrival Estimation for Coherently Distributed Source

In this paper, we consider the problem of the nominal 2-D (azimuth and elevation) direction-of-arrival (DOA) estimation for coherently distributed source. This new approach is based on the rotation matrices of three parallel uniform linear arrays as deduced, which has decoupled the nominal 2-D DOA from those of angular spreads. The estimator makes use of the eigenvalue decomposition to beamspace data to estimate the nominal elevation DOA. And then using a new cross-correlation matrix, the nominal azimuth DOA estimates are decoupled from the elevation estimates and can be obtained with no searching. The proposed algorithm has lower computational complexity particularly when the radio of array size to the number of source is large, at the expense of negligible performance loss. Simulation results verify the effectiveness of the proposed method.     

DOA estimation of LFM signals based on STFT and multiple invariance ESPRIT

In order to improve the angle measurement precision of LFM signals with a low computational complexity, a direction of arrival (DOA) estimation algorithm STFT-MI-ESPRIT is proposed in this paper. The algorithm is based on short time Fourier transform (STFT) and multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT). Firstly, the STFT of the array element’s output is calculated and the signals are transformed to the time-frequency domain. Then the spatial time-frequency distribution matrix can be obtained through selecting multiple single-source time-frequency points in the time-frequency plane and the signal subspace can also be obtained using Eigen decomposition. Finally, the multiple rotational invariant equation of the array based on STFT is obtained and the closed-form solution is obtained using the multi-least-squares (MLS) criterion. The simulation results show that the proposed algorithm can improve the estimation precision greatly compared with the traditional ESPRIT-like algorithms and its computational complexity remains the same in general. This paper also proposes that the STFT-MI-ESPRIT algorithm can use partial rotational invariances of the array instead of all the rotational invariances, which can reduce the computational complexity on the basis of ensuring the estimation precision basically. The simulation results verify the effectiveness of the conclusion.     

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。     

Unitary Subspace-Based Method for Angle Estimation in Bistatic MIMO Radar

In this paper, the issue of joint angle estimation for bistatic multiple-input multiple-output (MIMO) radar is investigated, and an algorithm for the joint estimation under real-valued computation is proposed. By utilizing the unitary transformation, the direction matrices and the data matrix are transformed to be real-valued ones. The direction of departure (DOD) can be estimated via the real-valued rotational invariance in the subspace, and the direction of arrival (DOA) can be obtained via the real-valued reduced-dimension function of multiple signal classification (MUSIC). The proposed algorithm utilizes both the signal and noise subspaces, requires no peak searching, and can achieve automatically paired estimations of the angles. Furthermore, it has better angle estimation performance than some existing methods. The simulation results verify the algorithmic effectiveness and robustness of the proposed algorithm.     

A RD-ESPRIT algorithm for coherent DOA estimation in monostatic MIMO radar using a single pulse

This paper discusses the problem of coherent direction of arrival (DOA) estimation in a monostatic multi-input multi-output (MIMO) radar using a single pulse, and proposes a reduced dimension (RD)-estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. We reconstruct the received data and then utilise it to construct a set of Toeplitz matrices. After that, we use RD-ESPRIT to obtain the DOAs of the sources. The proposed algorithm is effective for coherent angle estimation based on a single pulse, and it has much better angle estimation performance than the forward backward spatial smoothing (FBSS)-ESPRIT algorithm and the ESPRIT-like of Li, as well as very close angle estimation performance to the ESPRIT-like of Han. For complexity comparison, our algorithm has very close complexity to the FBSS-ESPRIT algorithm, and lower complexity than the ESPRIT-like of Han and the ESPRIT-like of Li. Simulation results present the effectiveness and improvement of our approach.     

用于非圆信号二维测向的扩展Root-MUSIC算法

利用双平行线阵的阵列结构,提出了用于非圆信号二维测向的扩展root-MUSIC(ERM)算法.ERM算法估计得到的俯仰角与方位角一一对应,自动配对,无需搜索,其可测向信号数大于子阵阵元数,方位测角精度优于同样基于双平|亍线阵的二维测向波达方向矩阵法(DOAM),俯仰测角精度在低信噪比下优于DOAM算法,俯仰角兼并时算法仍有效.     

一种自动匹配的分布式非圆信号二维DOA快速估计方法

在相干分布式非圆信号2维波达方向(DOA)估计中,针对利用非圆特性后维数扩展带来的较大复杂度问题,且现有的低复杂度算法均需要额外的参数匹配,该文提出一种基于互相关传播算子的自动匹配2维DOA快速估计算法。该算法考虑L型阵列,在建立相干分布式非圆信号扩展阵列模型的基础上,首先证明了L阵中两个子阵的广义方向矢量(GSV)均具有近似旋转不变特性,然后通过阵列输出信号的互相关运算消除了额外噪声,最终利用子阵GSV的近似旋转不变关系通过传播算子方法得到中心方位角与俯仰角估计。理论分析和仿真实验表明,所提算法无须谱峰搜索和协方差矩阵特征分解运算,具有较低的计算复杂度,并且能够实现2维DOA估计的自动匹配;同时,相比于现有的相干分布式非圆信号传播算子算法,所提算法以较小的复杂度代价获得了性能的较大提升。     

采用局部搜索的二维DOA估计

针对酉旋转不变估计信号参数(Unitary-ESPRIT)算法估计精度较低的问题,提出了一种采用局部搜索实现的非相干信源二维波达方向(2-D DOA)估计方法.该方法首先利用实特征矢量近似值估计导向矩阵,然后利用矩阵Kronecker积性质以及阵列旋转不变特性获得自动配对的角度估计值,降低了2-D DOA初始估计复杂度,实现了对Unitary-ESPRIT算法的改进;接着,采用一维局部搜索法对该初始估计结果进行优化,提高了低信噪比下的2-D DOA估计精度.仿真实验结果表明,相较于传统的Unitary-ESPRIT算法,所提方法在DOA估计精度和成功率上具有明显的优势,特别是在低信噪比以及快拍数较少条件下,因此该方法能够在计算复杂度和估计性能之间取的较好的折中.