基于空域平滑稀疏重构的DOA估计算法

该文提出一种基于空域平滑稀疏重构的DOA估计算法,利用空域平滑理论对协方差矩阵进行处理,然后通过KR积变换改变其结构,并对变换后的矩阵进行稀疏重构获得角度估计。此外,该文还给出了两种不同的目标函数误差求解方法。从仿真实验可以看出,该算法与传统的基于压缩感知理论的DOA估计算法对比,明显降低了运算量,且对于相干和非相干信号的处理性能均有所提高,在低角度间隔、低信噪比和低采样数条件下优势更为突出。     

频谱分析在DOA估计中的应用

子空间方法的本质是利用噪声子空间与阵列流型之间的正交性对阵列空间采样数据中空间频率进行估计。文章从快拍数据频谱分析的角度来实现这一估计。文中详细推导了窄带情况下DOA和快拍频谱的关系,提出了两种运算量较小、便于工程实现的利用FFT估计窄带DOA的方法。在宽带情况下,详细推导了宽带信号空间频率和时间频率的关系,推导出宽带信号频率对齐的方法,提出了两种直接利用对齐结果来估计宽带DOA的新方法。文中所用方法运算量小,便于硬件实现,仿真结果证明了算法的有效性。     

基于MCMC的DOA估计及其在空域滤波中的应用

针对传统算法在进行波达方向角估计时需要进行全空间的谱峰搜索,且依赖初始化迭代和插值的缺陷,设计了一种贝叶斯估计方法。首先,构建基于均匀圆阵的频域信号处理模型,提出了基于马尔科夫链蒙特卡罗进行波达方向角估计的方法,实现了无需初始化和插值的测向算法,且不需要进行全空间的谱峰搜索即可直接估计结果,同时推导了该模型下进行波达方向角估计的克拉美罗下界。在以测向结果为先验信息,同时设计了一种新的空域滤波增益模型。利用马尔科夫链蒙特卡罗算法对信号子空间进行解耦合,然后计算滤波器增益系数,以此实现空域滤波。最后在无线电设备搭建的真实环境中进行实验,验证了基于马尔科夫链蒙特卡罗算法进行阵列波达方向角估计和空域滤波的有效性,并且与其他模型相比要明显优于后者。     

信号频率和DOA联合估计方法

提出了一种针对均匀线阵的信号频率和DOA(direction of arrival)联合估计的快速算法。通过对采样数据进行分段与合并，构成含频率信息的时延旋转因子，利用ES-PRIT方法可以估计出信号的频率和DOA，不需要进行配对处理和增加任何多余的硬件。计算机仿真试验证实了该方法的有效性。     

利用改进遗传算法的DOA估计

用极大似然估计（ＭＬＥ）得到到达信号的方向（ＤＯＡ）,在统计性能方面要比其它一些理论优越,但是由于该方法为种多维参数估计,采用常规搜索方法,精度受到网格限制,不能任意逼近最优解,并且容易收敛到局部最优。而遗传算法是一种有导向的随机搜索方法,它具有适用条件宽松,有较大的概率收敛到全局最优等优点。在此通过改进的遗传算法（ＩＧＡ）,较好地解决了一般搜索算法存在的不足,计算机模拟实验证明可行。     

基于FRF域对称空域平均的相干LFM信源DOA估计研究

本文将时频分析中的FRFT与传统的MUSIC算法相结合,在FRF域找到具有时不变性的方向向量,很好地解决了雷达中典型的LFM非平稳信号的DOA估计问题,并针对相干信源入射的情况,提出通过在FRF域引入对称空域平均处理技术构造阵元接收信号的SATFD矩阵来消除信源间的相干性,最后仿真验证了本文所提算法的有效性,且与空间平滑解相干技术相比,具有更高的DOA估计精度。     

矩阵法在短波信号DOA估计中的应用

研究分析了基于均匀双平行线阵的矩阵法,并将其应用到短波信号的二维DOA估计中,通过计算机仿真验证了该方法的有效性。     

宽带独立信号和相干信号的DOA估计

当独立信号和相干信号共存时,传统四阶累积量方法无法估计出宽带相干信号的来波方向(DOA),针对这个问题提出了一种新方法。该方法首先通过离散傅里叶变换,将宽带阵列接收数据分解为若干个窄带信号,构造出各个窄带频率处的自相关矩阵,再通过MUSIC(Multiple Signal Classification)算法估计出各个窄带信号的DOA,将各个窄带信号的空间谱相加求平均,通过谱峰搜索得到宽带独立信号的DOA;然后分离出独立信号的信息,构造出一个只包含宽带相干信号信息的矩阵,最后通过稀疏重构的方法估计出相干信号的DOA。计算机仿真结果证明该算法的正确性和有效性。     

基于解相干的改进MUSIC算法DOA估计

MUSIC算法是一种子空间分解算法。在非相干的情况下,经典MUSIC算法能准确进行波达方向（DOA）估计,但当信号源在相干的情况下时算法失效。在对经典MUSIC算法进行理论分析研究的基础上,对其阵元接收数据阵做相应变换,得到共轭重构后的协方差矩阵,通过特征值分解再进行DOA估计。就经典的MUSIC和改进算法的DOA估计性能进行了仿真分析。结果表明,改进后的算法在信号源相干的情况下也能精确地估计信号的波达方向。     

色噪声环境下强相关源的DOA估计

结合MMUSIC（Modified multiple Signal Classfication)算法和SWEDE（Subsapce Method Without Eigen DE composition)方法的优点提出了联合DOA估计方法,该法使得在色噪声环境下强相关信源DOA（Direction Of Arrival)估计成为可能。理论分析与仿真结果表明：联合DOA估计方法在明显降低运算复杂度的同时,无需空间噪声必须为白噪声的约束,更加贴近现实情况,而且有利于在线处理。     

基于信号-阶循环平稳特性的源信号方向估计方法

本研究并给出了基于信号-阶循环平稳特性的阵列信号模型,根据该信号模型结合最小二乘方法得到了对源方向进行有效估计的算法,并与MUSIC算法作了简单的比较.对单目标和多目标两种情况分别进行了仿真计算,仿真结果说明了所给方法的有效性.     

基于累积量的空间特征估计算法及其在智能天线中的应用

在智能天线系统中,波达方向(DOA)估计是实现空分多址的关键问题之一.本文提出了一种基于累积量的多用户空间特征估计算法,并将该算法用于智能天线中的多用户相干源DOA估计.该算法利用累积量构造了空间特征矩阵,通过对空间特征矩阵的特征分解得到各用户信号的空间特征估计,并基于空间特征估计,利用前后平滑空间特征协方差矩阵估计共信道多用户信号的DOA.仿真实验验证了算法的有效性.     

Incoherent DOA Estimation in Uniform Antenna Arrays with Inordinate Spacing Using a Subband Hopping Approach

Given a certain transmission frequency, the Shannon spatial sampling limit defines an upper bound for the antenna element spacing. Beyond this bound, the exceeded ambiguity avoids correct estimation of the signal parameters (i.e., array manifold crossing). In this survey, the problem of simultaneous signal and direction-of-arrival (DOA) estimation of broadband sources is addressed when the element spacing of a uniform array antenna (uniform linear array (ULA)) is inordinate. It is illustrated that one can resolve the aliasing ambiguity by utilizing the inherent frequency diversity of the broadband sources. An algorithm based on maximum likelihood estimation (MLE) has been developed to estimate the transmitted data signal and the DOA of each source. Through confirmatory simulation, it is shown that the performance gain of the proposed setup is potentially significant, specifically under a low signal-to-noise ratio (SNR) and when the transmitters are closely spaced. This relaxes the stringent maximum element-spacing constraint of ULAs pertinent to the upper-bound frequency of transmission and suggests that the element spacing—which in practical applications results in detrimental element coupling—can be conveniently increased, in particular under wide transmission spectrum and low SNR (e.g., license-free communication). A method similar to the frequency hopping approach (i.e., subband hopping) is utilized for the problem of source associations and identification. In the sequel, a suboptimal subspace-based algorithm is proposed and its performance is investigated. An approximate expression for the estimation error has also been developed to gauge the behavior of the proposed setup.     

基于级联自适应陷波器的正弦波频率估计

常用的传统和现代方法对于噪声环境中正弦信号的频率估计均存在一定的缺陷。本文利用二阶陷波器级联构造自适应陷波器,实现对多个信号频率的估计;采用递推误差信号和递推最小二乘法同时优化各个二阶陷波器的参数。仿真结果表明,该方法对于单频、多频和频率变化等情况均具有较好的估计结果,且对于噪声干扰具有较强的鲁棒性。     

An ESPRIT-like algorithm for coherent DOA estimation based on data matrix decomposition in MIMO radar

A direction-of-arrival (DOA) estimation method for coherent sources is presented for MIMO radar. It uses symmetrical array mode for both the transmit and receive arrays and reconstructs a special data matrix from the range-compressed receive data. In the reconstructed matrix, the signal term is a Toeplitz matrix with the rank only related to the DOAs of the signals and independent with their coherency. Taking the noise term into account, the average method of multiple pulses is utilized to obtain the signal and noise subspaces. And then the DOA can be resolved via the SVD-based ESPRIT algorithm. Furthermore, the presented method is also useful in spatial colored noise scenario for MIMO radar. Theoretical and numerical simulations show the effectiveness of the proposed algorithm.     

QPSO算法在FIR数字滤波器设计中的应用

FIR数字滤波器的设计实际上是一个多维变量寻优问题,滤波器的设计可转化为滤波器参数优化的问题。文章介绍了粒子群优化算法、量子粒子群优化算法,然后利用算法对参数空间进行搜索以获得参数的最优化,根据预期频率特性的设计要求,通过仿真实验表明设计方法的有效性。     

Fast maximum likelihood DOA estimation in the two-target case with applications to automotive radar

Direction-of-arrival (DOA) estimation of two targets using a single snapshot plays an important role in automotive radar for advanced driver assistance systems. Conventional Fourier methods have a limited resolution and generally yield biased estimates. Subspace methods involve a numerically complex eigendecomposition and require multiple snapshots or a suboptimal pre-processing for reliable estimation. We therefore consider the maximum likelihood (ML) DOA estimator, which is applicable with a single snapshot and shows good statistical properties. To reduce the computational burden, we propose a grid search procedure with a simplified calculation of the objective function. The required projection operators are pre-calculated off-line and stored. To save storage space and computations, we further propose a rotational shift of the field-of-view such that the relevant angular sector, which has to be evaluated, is delimited and centered with respect to broadside. The final estimates are obtained using a quadratic interpolation. The developed method is demonstrated with an example. Simulations are designed to assess the performance of the considered ML estimator with grid search and interpolation, and to compare it among selected representative methods. We further present results obtained with experimental data from a typical application in automotive radar.     

水下电磁场源的二维DOA和极化估计

以电磁矢量传感器在均匀海水中的电声测量为运用背景,建立了水中单个电磁矢量传感器的数据接收模型,采用特征值分解的信号子空间TLS-ESPRIT算法,对基于该算法的单个电磁矢量传感器估计多个信号源的DOA和极化参数问题进行了研究.