非圆信号方位、俯仰及初相联合估计

该文利用双平行线阵的阵列结构,提出了用于非圆信号二维方向和初相联合估计的扩展MUSIC(EN-MUSIC)算法。EN-MUSIC算法估计得到的方位角、俯仰角与初相一一对应,自动配对,其可测向信号数大于子阵阵元数,方位及俯仰测角精度与非圆信号二维测向酉ESPRIT(2D-NC-UESPRIT)算法大致相当,优于波达方向矩阵法(DOAM)。     

基于非圆信号的二维测向算法

提出了一种基于窄带非圆信号的二维测向算法,利用非圆信号的椭圆协方差矩阵非零特性将阵列有效阵元数和孔径同时扩展,提高多信号检测的能力。进一步通过利用L阵的几何性质和两子阵间的互相关来滤除噪声,提高角度估计精度,并采用快速算法获得信号方位角和俯仰角。最后计算机仿真结果验证了该方法由于利用非圆信号特性比传统测向算法的估计性能更高。     

采用降秩多级维纳滤波器的二维DOA估计快速算法

针对双平行线阵的二维波达方向(DOA)估计问题,为有效降低计算复杂度,提出了一种基于降秩多级维纳滤波器(MSWF)的快速算法。首先利用MSWF的前向递推实现信号子空间的快速估计,无需估计协方差矩阵和特征分解;然后,通过MUSIC算法对方位角和俯仰角的估计进行分维估计,使二维DOA估计退化为两个一维DOA估计问题,且方位角和俯仰角自动配对,进一步降低了运算量。仿真结果表明,该方法的估计精度优于同样基于双平行线阵提出的波达方向矩阵法(DOAM),俯仰角兼并时同样适用,计算复杂度低,适用于实时性要求高的应用背景。     

共轭传播算子测向算法

针对一维信号提出了共轭传播算子测向算法(COP),新算法利用了阵列输出数据的共轭,通过对阵列孔径的扩展,可对多于阵元数的信号进行测向,其分辨力和测角精度优于OPM(正交传播算子测向算法)和MUSIC 算法.分析了新算法的均方误差性能和计算复杂度,得到了均方误差的解析表达式.仿真实验验证了COP算法的优良性能,均方误差的理论值与仿真值相符.     

一种基于余弦特性的快速DOA估计算法

为了满足实时测向处理系统的要求,需要降低测向算法的运算量。在众多测向算法中,其中基于圆阵的MUSIC类算法因为其测向频段宽,可估计二维波达方向,性能稳健,测向精度高,并且在各个方向上具有相同的测向性能而广泛应用于实际系统中。本文主要针对均匀圆阵的阵列流形,分析了均匀圆阵导向矢量的特点,提出了一种基于余弦特性的快速DOA估计算法。该算法利用余弦信号周期特性来构造统计量,通过数学推倒可以证明该统计量只与俯仰角有关,与方位角无关。通过这种分维处理的思想从而可以先估计出俯仰角,再通过所得俯仰角的空间谱切片把二维搜索转化为一维搜索,这样处理大大降低了算法运算量,提高了算法估计速度,特别适合阵元数目较多的应用场合。同时考虑到实际应用中在同一个窄带信道中干扰信号和期望信号同时存在,并且互相影响,特别是强信号对弱信号的影响。本文利用数字滤波器提取期望信号估计,减少了干扰信号对期望信号的影响,提高了估计精度。通过计算机仿真验证了该算法的有效性。      

基于扩展传播算子的非圆信号测向方法

现代通信系统大量使用非圆信号,利用经典高分辨算法对其测向没有充分利用非圆信号的信息,因而性能受限.本文提出的扩展传播算子测向算法(EPM)先对数据进行共轭扩展,再利用传播算子方法(PM)测向,充分利用了非圆信号的特点,从而可对多于阵元数的信号进行测向,分辨力和测角精度优于OPM(正交传播算子测向算法)和MUSIC算法,同时保持了PM算法的特点,不需要特征分解(ED)或奇异值分解(SVD).文中还分析了EPM算法的均方误差性能和计算复杂度,得到了均方误差的解析表达式.仿真实验验证了EPM算法的优良性能,均方误差的理论结果与仿真值相符.     

一种基于TDOA的多天线联合测角算法

针对分布式多天线系统中传统测角方法存在测量精度偏低、宽带信号不适用等问题,提出了一种基于时延差（Time Difference of Arrival,TDOA）测量的多天线二维测角算法。该算法基于最小二乘原理,综合利用多基线测量结果进行迭代计算,有效提高了估计精度,且无需解模糊。推导了算法的克拉美罗界(Cramér-Rao Lower Bound,CRLB)与均方根误差表达式,讨论了算法的测角性能。当天线数为7、天线间距100 m、时延估计精度优于10 μs时,测角精度接近CRLB,方位角精度优于3°,俯仰角精度优于4°。算法复杂度适中,能够应用到多天线无源侦察、空间目标跟踪等应用中。     

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。     

基于偶数阶累积量的非圆信号测向方法

提出了基于2q阶累积量的非圆信号测向MUSIC(Multiple Signal Classification)算法(称为NC-2q-MUSIC),作为2q-MUSIC算法利用非圆信息的一种扩展,在可测向信号数、分辨力和测角精度等方面的性能均优于2q-MUSIC算法.并且,q越大,NC-2q-MUSIC算法的可测向信号数越大,分辨力越高,对模型误差也越不敏感.针对均布线阵(ULA:Uniform Linear Array)提出的NC-2q-MUSIC/ULA算法减小了计算量.仿真实验验证了NC-2q-MUSIC算法的优良性能.     

基于四阶累积量的非圆信号测向方法

对通信系统中大量使用的BPSK等非圆信号测向,可以采用共轭扩展MUSIC(CE-MUSIC)算法,也可以采用基于四阶累积量的MUSIC-like算法。CE-MUSIC算法没有利用高阶信息,MUSIC-like算法没有利用信号的非圆信息,性能均受限。该文提出的四阶扩展MUSIC(FO-EMUSIC)算法利用了非圆信号在四阶累积量中的信息,分辨力和测角精度明显优于MUSIC-like算法,略优于CE-MUSIC算法,可测向阵元数大于CE-MUSIC算法和MUSIC-like算法。针对均布线阵,为减小计算量,还提出了FO-EMUSIC/ULA算法。仿真实验验证了FO-EMUSIC算法的优良性能。     

An automatically paired two-dimensional direction-of-arrival estimation method for two parallel uniform linear arrays

In two-dimensional (2-D) direction-of-arrival (DOA) estimation, paring the azimuth and elevation angles of multiple sources is an important issue. In this letter, we propose a new automatically paired 2-D DOA estimation method by designing the geometry of two antenna subarrays and using the propagator method (PM). A special geometry between two parallel uniform linear arrays (ULAs) with a position displacement on the axial direction is proposed to facilitate the elevation and azimuth pairing and estimation. The simulation results have shown that the proposed method can achieve the same 2-D DOA estimation performance as the existing methods, while the complexity is reduced considerably.     

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。      

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.     

Two-Dimensional DOA Estimation by?Cross-Correlation Matrix Stacking

In this paper, we present a novel scheme to improve the two-dimensional (2-D) direction-of-arrival (DOA) estimation performance for narrowband signals impinging on two orthogonal uniform linear arrays (ULAs). The proposed scheme exploits the cross-correlation matrix information between subarray data to construct a stacking matrix and derive an expanded signal subspace representation through the singular value decomposition (SVD). This method enables the alleviation of the effects of additive noise. In particular, 2-D DOA estimation can be achieved by computing two rotation matrices with the same set of eigenvectors obtained by partitioning the expanded signal subspace. The pair matching procedure for elevation and azimuth angles is implemented by permutation test. Simulation results demonstrate that the proposed method performs better than the existing techniques in DOA estimation as well as the detection of successful pair matching.     

DOA error estimation in 3D cylindrical dipole array geometries including the mutual coupling effect

The direction of arrival (DOA) error in dipole 3D arrays is estimated through Monte-Carlo simulations using the standard MUSIC algorithm. Novel 3D geometries are implemented which demonstrate better precision given the same lateral area. The mutual coupling effect is included by changing the search vector in the MUSIC DOA algorithm for the novel 3D geometries. A simple straight forward method is used which does not need complex electromagnetic computations. Simulations show that the proposed method can successfully account for the mutual coupling effects in two dimensional direction finding (both azimuth and elevation angle) with novel 3D array geometries. Reduced DOA estimation error is observed in the novel geometries which can be used as a method of mitigation for the mutual coupling effect.     

Closed-form 2-D angle estimation with rectangular arrays in elementspace or beamspace via unitary ESPRIT

The UCA-ESPRIT is a closed-form algorithm developed for use in conjunction with a uniform circular array (UCA) that provides automatically paired source azimuth and elevation angle estimates. The 2-D unitary ESPRIT is presented as an algorithm providing the same capabilities for a uniform rectangular array (URA). In the final stage of the algorithm, the real and imaginary parts of the ith eigenvalue of a matrix are one-to-one related to the respective direction cosines of the ith source relative to the two major array axes. The 2-D unitary ESPRIT offers a number of advantages over other proposed ESPRIT based closed-form 2-D angle estimation techniques. First, except for the final eigenvalue decomposition of a dimension equal to the number of sources, it is efficiently formulated in terms of real-valued computation throughout. Second, it is amenable to efficient beamspace implementations that are presented. Third, it is applicable to array configurations that do not exhibit identical subarrays, e.g., two orthogonal linear arrays. Finally, the 2-D unitary ESPRIT easily handles sources having one member of the spatial frequency coordinate pair in common. Simulation results are presented verifying the efficacy of the method     

L-shaped array-based elevation and azimuth direction finding in the presence of mutual coupling

For two-dimensional (2-D) directions-of-arrival (DOA) estimation problem, both the mutual coupling and the failure in pairing can cause severe performance degradation. In this paper, a new elevation and azimuth direction finding algorithm is developed to overcome the above-mentioned two difficulties in the L-shaped array configuration. The key points of this paper are: (i) constructing several correlation matrices to blindly compensate the effect of unknown mutual coupling using the outputs of properly chosen sensors and (ii) deriving a rank-reduction propagator method to estimate elevation and azimuth angles so as to avoid pairing parameters. Simulation results are presented to validate the performance of the proposed method.