基于联合矩阵对角化的双基地MIMO雷达DOD-DOA估计

针对双基地MIMO雷达收发角(DOD-DOA)估计问题,该文提出一种基于联合矩阵对角化的快速多目标收发角估计算法。该算法首先根据匹配滤波输出的数据结构,利用奇异值分解和秩1矩阵判断定理将收发角度估计问题转化为联合矩阵对角化问题,然后采用单次-扫描迭代算法对其求解,得到收发阵列流型矩阵,最后通过谱分析方法估计收发角。该算法充分利用匹配滤波输出的所有信息,无需2维谱峰搜索,每次迭代均可得到精确的闭式解,且收发角自动配对。与现有算法相比,该算法不仅提高了角度估计精度,而且有效降低了运算量。仿真结果证明了所提算法的有效性。     

多跳频信号的2D-DOA估计

为了利用跳频信号的二维波达方向（2D-DOA）辅助同步跳频信号的网台分选和信号识别、跟踪,提出一种基于酉ESPRIT算法的多跳频信号2D-DOA估计方法。首先利用形态学滤波的方法对跳频信号的时频图进行修正,并在修正的时频图上完成有效跳的提取;然后基于平面天线阵列结构,建立有效跳的阵列快拍数据模型;在此基础上,采用酉ESPRIT算法进行跳频信号的2D-DOA联合估计。该方法将接收数据从复数域转化到实数域处理,降低了运算复杂度;同时构造实矩阵时,复用了接收数据,提高了估计精度。仿真结果表明,该算法具有良好的估计性能。      

面向毫米波大规模极化敏感阵列的多径信号二维快速测向算法

作为B5G/6G的可能发展方向之一，毫米波大规模敏感阵列拥有诸多潜在的优势，如能提供高分辨率的二维波达角（2D-DOA）估计、可以实现极化保密通信等。关注极化敏感阵列中的相干源2D-DOA估计问题，提出了一种基于矩阵重排的快速估计方法。首先利用矩阵重排解决矩阵秩亏问题，再利用传播算子（PM）进行高效测向，并给出了算法相关性能的理论分析，包括计算复杂度、可辨识性和Cramer-Rao界。最后，通过仿真结果验证了所提算法的有效性。     

基于稀疏采样阵列优化的APG-MUSIC算法

针对稀疏阵列下2维波达方向(DOA)估计问题,该文提出一种基于稀疏采样阵列优化的加速逼近梯度(APG)算法与多重信号分类(MUSIC)算法相结合的2D-DOA估计方法。首先,建立稀疏阵列下的2D-DOA估计信号模型,并证明其具备低秩特征,满足零空间性质(NSP)。其次,为提高稀疏阵列下矩阵填充方法重构接收信号矩阵性能和以此为基础的2D-DOA估计精度,提出基于遗传算法(GA)的稀疏采样阵列优化方法。最后,将APG和MUSIC算法相结合,在重构完整平面阵列接收信号矩阵的基础上完成2维波达方向估计。计算机仿真结果表明,该方法在保证2维波达方向估计精度前提下,大幅提高阵元利用率,有效降低空间谱平均旁瓣,与常规2D-DOA估计方法相比具有优势。     

基于块状导频的OFDM信道估计

首先对OFDM系统中基于导频辅助的信道估计算法进行研究,为了降低复杂度,利用奇异值分解(SVD)给出一种低阶近似的信道估计器。仿真结果表明LMMSE算法利用信道相关特性增加了运算量,但可以获得较好的估计效果,其简化算法(SVD)的性能略有下降,且随着信噪比增大,会出现"地板效应"。     

单快拍数据的分布式阵列DOA估计

该文针对分布式阵列相干信号单次快拍波达方向估计问题,提出一种基于状态空间平衡法的1维波达角估计算法。该算法首先直接利用单快拍数据以分布式阵列每个子阵单元进行Hankle矩阵构造,然后采用状态空间平衡法,分别获得低精度无模糊的子阵单元内DOA估计和高精度有模糊的子阵单元间DOA估计,最后结合配对和解模糊算法获得高精度无模糊DOA估计。该算法不受信号形式限制,可同时对相干信号和非相干信号进行处理,能充分利用分布式阵列扩展阵列物理孔径特性,获得较高的DOA估计精度。计算机仿真结果验证了所提算法的有效性。     

多星测控中波达方向估计传播因子虚拟ESPRIT算法

针对多星测控中涉及的阵列天线信号波达方向估计问题,给出了一种新的基于传播因子的二维波达方向估计(2D-DOA)算法--传播因子虚拟ESPRIT算法(PMV-ESPRIT).传统的虚拟ESPRIT算法需要对互相关矩阵进行特征值分解(EVD)或对数据接收矩阵进行奇异值分解(SVD),因此其运算量较大.而新算法基于传播因子方...     

未预期模型误差影响下秩减估计器的性能分析

从理论上定量分析了未预期模型误差影响下秩减估计器的方位估计性能。通过对秩减估计空域谱进行一阶Taylor级数展开得到方位估计偏差的表达式,基于此分别推导了秩减估计器的方位估计均方误差和测向成功概率。针对一种用于均匀阵列互耦自校正的秩减估计器给出数值实验,实验结果验证了理论推导的有效性。     

有限采样影响下秩减估计器的波达方向估计性能分析

首先从理论上分析有限采样影响下秩减估计器的波达方向估计性能,然后基于信号(或噪声)子空间的正交投影矩阵扰动定理,分别推导秩减估计器方位估计偏差的一阶和二阶闭式表达式,在此基础上给出其方位估计均方误差、偏置以及测向成功概率的理论计算公式,最后针对若干重要的秩减估计器给出数值实验,实验结果验证了所提理论推导的有效性。     

一种MPSK信号载频高精度实时估计算法

常用的对多阶相移键控(MPSK)载频进行高精度估计的算法运算量大,不适合实时处理。针对此问题,提出了一种新的MPSK信号载频高精度实时估计算法,对非线性变换后信号进行正交下变频和2级DFT处理,可对载频频率高精度的实时估计。通过计算机仿真试验验证了该算法的估计精度与直接DFT频率估计方法近似。     

Two-dimensional DOA estimation for acoustic vector-sensor array using a successive MUSIC

This paper discusses the problem of two-dimensional (2D) direction of arrival (DOA) estimation for acoustic vector-sensor array, and derives a successive multiple signal classification (MUSIC) algorithm therein. The proposed algorithm obtains initial estimations of the azimuth and elevation angles obtained from the signal subspace, and uses successively one-dimensional local searches to achieve the joint estimation of 2D-DOA. The proposed algorithm, which requires the one-dimension local searches, can avoid the high computational cost within 2D-MUSIC algorithm. The proposed algorithm can obtain automatically-paired 2D-DOA estimation for acoustic vector-sensor array, and it has better DOA estimation performance than propagator method, estimation of signal parameters via rotational invariance technique algorithm and trilinear decomposition algorithm. Meanwhile, it has very close angle estimation to 2D-MUSIC algorithm. Furthermore, it is suitable for non-uniform linear arrays, works well for the sources with the same azimuth angle, and imposes less constraint on the sensor spacing, which does not have to be restricted within half-wavelength. We have also derived the mean-square error of DOA estimation of the proposed algorithm and the Cramer-Rao bound of DOA estimation. Simulation results verify the usefulness of the proposed algorithm.     

2D-DOA estimation of noncircular signals for uniform rectangular array via NC-PARAFAC method

In this paper, we propose a two-dimensional direction of arrival (2D-DOA) estimation algorithm for uniform rectangular array via noncircular-parallel factor (NC-PARAFAC) method. Compared to the conventional parallel factor (PARAFAC) algorithm, the proposed algorithm exploits the property of noncircular signals to double the array aperture. Therefore, the angle estimation performance of the proposed algorithm is better than the conventional PARAFAC method. The proposed algorithm achieves automatically paired two-dimensional angle estimates, and has better 2D-DOA estimation performance than some conventional algorithms, which include estimation of signal parameters via rotational invariance technique (ESPRIT), propagator method (PM), PARAFAC algorithm, noncircular-ESPRIT (NC-ESPRIT) and noncircular-PM (NC-PM). We also derive the Cramér–Rao bound for the 2D-DOA estimation of noncircular signals with uniform rectangular array. Simulation results verify the effectiveness and improvement of the proposed algorithm.     

A low-complexity joint 2D-DOD and 2D-DOA estimation algorithm for MIMO radar with arbitrary arrays

In this article, we study the problem of four-dimensional angles estimation for bistatic multiple-input multiple-output (MIMO) radar with arbitrary arrays, and propose a joint two-dimensional direction of departure (2D-DOD) and two-dimensional direction of arrival (2D-DOA) estimation algorithm. Our algorithm is to extend the propagator method (PM) for angle estimation in MIMO radar. The proposed algorithm does not require peak searching and eigenvalue decomposition of received signal covariance matrix, because of this, it has low computational complexity. And it can achieve automatic pairing of four-dimensional angles. Furthermore, the proposed algorithm has much better angle estimation performance than interpolated estimation method of signal parameters via rotational invariance techniques (ESPRIT), and has very close angle estimation performance to ESPRIT-like algorithm which has higher computational cost than the proposed algorithm. We also analyze the complexity and angle estimation error of the algorithm, and derive the Cramer‐Rao bound (CRB). The simulation results verify the effectiveness and improvement of the proposed algorithm.     

基于任意麦克风阵列的声源二维DOA估计算法研究

对基于麦克风阵列的声源定位技术进行了研究,分析了基于麦克风阵列的远场信号模型,并结合子空间的方法推导出了声源二维(水平角和俯仰角)DOA估计——2D-MUSIC算法,该算法适用于任意拓扑结构的麦克风阵列。利用MATLAB仿真工具,对几种典型阵列结构进行了对比分析,提出了2种新型的三维麦克风阵列:均匀球面阵和三维均匀直线阵。仿真结果表明,提出的DOA估计算法在二维的均匀圆阵、三维的均匀球面阵和三维均匀直线阵中,均能得到较好的DOA估计效果。     

RAM-based angle estimation with linear spatially separated polarisation sensitive array

Two-dimensional direction of arrival (2D-DOA) and polarisation estimation of multiple incident signals for linear spatially separated polarisation sensitive array (SS-PSA) is investigated with reweighted atomic norm minimisation (RAM) algorithm. Single vector sensor in this paper is composed of spatially separated three dipoles and three loops. Firstly, the received data of the proposed array with single snapshot is converted into the new received data with six virtual snapshots. Each virtual snapshot data is the data sensing by dipoles or loops located in the same direction. Secondly, based on each virtual snapshot data, the complex amplitudes and frequencies of the virtual signals are restored using RAM algorithm. Lastly, 2D-DOA and polarisation angles are derived according to the restored complex amplitudes and frequencies. Simulation results demonstrate that the RAM algorithm used in 2D-DOA and polarisation estimation with SS-PSA exhibits superior performance, which is better compared with polarisation multiple signal classi?cation (PMUSIC) algorithm and rotational invariance techniques (ESPRIT) algorithm.     

基于平行互质虚拟阵列的低复杂度二维DOA联合估计算法

针对传统平行阵列2维测向自由度低、分辨能力差和小快拍情况下估计误差大等问题,该文提出基于平行互质虚拟阵列的低复杂度2维波达角(DOA)估计算法。该算法利用两个相互平行的互质线阵扩展生成虚拟阵列,并通过协方差矩阵和互协方差矩阵构造具有增强2维角度自由度的扩展矩阵,最后通过奇异值分解(SVD)和旋转不变技术(ESPRIT)获得自动匹配的2维角度估计。相比于传统的2维DOA估计方法,所提算法更好地利用了阵列接收数据信息,能识别更多的入射信号,分辨能力高,不需要进行2维线性搜索或者角度参数匹配,在低信噪比 (SNR)和小快拍情况下也有很好的估计效果。实验仿真结果验证了提出算法的有效性和可靠性。     

Multiple Emitters Localization by UAV with Nested Linear Array: System Scheme and 2D-DOA Estimation Algorithm

Unmanned Aerial Vehicle(UAV)equipped with uniform linear array has been applied to multiple emitters localization.Meanwhile,nested linear array enables to enhance localization resolution and achieve under-determined Direction of Arrival(DOA)estimation.In this paper,we propose a new system structure for emitters localization that combines the UAV with nested linear array,which is capable of significantly increasing the positioning accuracy of interested targets.Specifically,a localization scheme is designed to obtain the paired two-dimensional DOA(2D-DOA,i.e.azimuth and elevation angles)estimates of emitters by nested linear array with UAV.Furthermore,we propose an improved DOA estimation algorithm for emitters localization that utilizes Discrete Fourier Transform(DFT)method to obtain coarse DOA estimates,subsequently,achieve the fine DOA estimates by sparse representation.The proposed algorithm has lower computational complexity because the coarse DOA estimates enable to shrink the range of over-complete dictionary of sparse representation.In addition,compared to traditional uniform linear array,improved 2D-DOA estimation performance of emitters can be obtained with a nested linear array.Extensive simulation results testify the effectiveness of the proposed method.     

基于对称天线相位干涉仪的入射角估计及跟踪

针对现有相位干涉仪角度估计算法在近场条件下性能不佳的问题,该文提出一种远近场均性能良好的改进的导向矢量匹配算法。该算法采用对称结构天线接收来波信号,利用近场条件下对称位置天线的到达相位差中距离相关项对消的特性设计新的代价函数。代价函数最大值位置对应的入射角即为目标信号的入射角估计。在此基础上,利用相关函数的梯度正比于角度误差的特性设计角跟踪环路。作为一种局部极值估计算法,角跟踪环路相比其它全局最大值估计算法具有更好的相位噪声鲁棒性。仿真实验验证了该算法在不同相位噪声以及远近场条件下的优良性能。     

基于宽带均匀同心球阵列的低复杂度二维波达方向估计算法

该文提出一种基于宽带均匀同心球阵列(UCSA)的2维波达方向(2D-DOA)低复杂度估计算法.该方法将宽带UCSA输出信号转换为相位模式,并对其进行频率补偿,实现近似频率不变(FI)特性,从而降低宽带信号处理的计算复杂度.为了进一步降低2D-DOA估计的计算复杂度,该文提出基于FI-UCSA的降维多重信号分类(MUSI...