混合MIMO相控阵雷达的交错稀疏阵列设计

针对常规的发射子阵分割会使混合MIMO相控阵雷达的孔径减小和馈电网络复杂度增加的问题,提出一种交错稀疏的发射子阵分割方法,通过寻求最大输出信干噪比的方式获得最佳的阵列结构.首先构建交错稀疏结构下的混合MIMO相控阵雷达模型,运用序列凸近似方法将非凸的目标函数转化为凸函数;然后通过凸优化分别求解出一维和二维混合MIMO相控阵雷达在阵元数目固定和阵元数目作为变量的情况下的最佳阵列结构;最后,通过仿真表明所提出方法不仅可以获得较大的信干噪比和较低的旁瓣电平值,且较常规的子阵分割方式能获得更高的波达方向估计精度.     

稀疏阵列MIMO雷达参数估计研究进展

利用稀疏阵列多输入多输出(multi-input and multi-output, MIMO)雷达的虚拟孔径扩展特性开展参数估计研究具有重要的理论意义和应用前景.本文以稀疏阵列MIMO雷达设计和参数估计为导向,以提高估计精度和降低运算量为落脚点,从子空间类和压缩感知类算法的契合点出发,围绕阵列设计、波达方向估计、角度联合估计等方面,构建了系统的稀疏阵列MIMO雷达参数估计理论.最后,从阵列优化设计、混合目标参数估计、非理想因素抑制和分布式平台搭建等方面展望了稀疏阵列MIMO雷达的发展趋势.     

基于内插阵列变换的扩展传播算子实值算法

针对内插阵列变换(VIA)思想在非圆信号波达方向(DOA)估计算法中的应用问题,提出一种基于内插阵列变换的扩展传播算子实值算法——VIA-EPM实值算法。利用真实阵列流型与虚拟阵列流型之间的变换矩阵,将真实阵列输出转换为虚拟阵列输出,再根据信号源为实数的特点,分别求取虚拟阵列输出的实部和虚部,将其串联组合,扩展阵列输出的维数,通过对扩展阵列输出矩阵进行分块并得出扩展传播算子,进而得到一种传播算子(PM)类的DOA估计算法。仿真实验表明：存在阵元位置误差的情况下,VIA-EPM实值算法通过对阵元位置校准数据进行内插阵列变换,取得与阵元位置校准的扩展传播算子实值算法(EPM实值算法)相当的估计性能,保持了阵列扩展能力、高估计精度以及高分辨力;并且在二维阵元位置误差情况下,其估计性能明显优于阵元位置未校准的EPM实值算法。结合VIA-EPM实值算法的计算复杂度分析可以看出：它同时获得了内插阵列变换技术以及信号非圆特性的优势;与复运算相比,其复杂度也相对降低。     

基于多对称虚拟变换的二维波达方向估计算法

提出一种多对称虚拟变换二维波达方向估计算法,通过对阵列进行多对称虚拟变换,得到多个分别关于原阵列对称的虚拟阵列,进而构造虚实平移不变子阵。利用该平移不变虚拟子阵的旋转不变因子,获得信号源的俯仰角,经多信号分类(MUSIC)一维搜索获得信号源方位角,方位角和俯仰角可自动配对。由于使用了各虚拟变换阵列的累加数据,累加运算使得各虚拟阵列数据的正负误差相互抵消,显著降低了虚拟变换矩阵导致的虚拟阵列和真实阵列之间的数据误差,提高了二维波达方向的估计精度。仿真实验研究了所提算法在信噪比、快拍数变化情况下,二维波达方向估计的均方根误差和成功率性能,证明了所提算法的有效性。     

稀疏互质阵列的迭代加权l_1范数约束来波方向估计

在阵元数确定的情况下,稀疏互质阵列能增大阵列孔径。为利用阵列的互质关系形成具有更多自由度的互质差合成阵列,采用稀疏重构方法,提出一种迭代加权l_1范数约束波达方向(DOA)估计算法。通过矢量化对稀疏互质阵列进行孔径扩展,进而在相应的过完备基下获得观测模型的l_0范数约束稀疏重构,再用加权l_1范数约束代替l_0范数约束重构方法,采用多次迭代运算求取最优解实现DOA估计。实验结果表明,该算法能够更好地利用稀疏互质阵列的阵列孔径,提高测向精度,并且通过迭代运算来弥合l_1范数约束与l_0范数约束之间的差别,克服传统l_1范数约束类算法存在估计偏差的缺点。     

基于压缩感知的二维DOA估计

针对L阵列,提出基于压缩感知的二维波达方向估计新方法。定义方位角和俯仰角余弦乘积为空间合成角,利用等余弦网格划分空间合成角构造超完备的冗余字典,将子阵接收的单快拍数据矢量转化为冗余字典下的稀疏表示问题;采用单位列向量组合矩阵随机抽取的新方法构造高斯随机测量矩阵;通过改进正交匹配追踪算法求解二维波达角。指出所提出的算法比传统二维MUSIC算法在高信噪比、多快拍条件下估计性能更好,并且有一定的阵元节约效能。计算机仿真实验证明了以上结论。     

基于辅助阵元的二维波达方向估计算法

;针对任意平面阵列,提出了一种基于辅助阵元的二维波这方向估计算法.首先利用附加的一个辅助阵元及信号的空、时域信息,构造时空旋转矩阵实现对仰角的分离估计,再利用得到的仰角信息通过一维搜索获取方位角.与传统基于子空间的二维波达方向估计算法相比,该方法不需要进行二维谱峰搜索与参数配对,对阵元的幅相误差具有较强的鲁棒性,并具有...     

一种V型阵列的二维波达方向估计的新方法

波达方向估计是阵列信号处理的一个重要研究方向,在雷达、通信、声纳、地震勘测等领域都有着广泛的应用前景.它已成为阵列无源探测和智能天线中的关键技术.针对二维信号,本文研究一种基于V型阵二维波达方向估计的新算法.该算法根据阵列结构的特点形成多个需要的相关矩阵,构造一个特殊大矩阵并经特征分解获得信号子空间的估计,最后利用2D-ESPRIT方法实现二维角度估计,可以解决β角兼并信号的波达方向估计问题,无需谱峰搜索且信号参数自动配对.最后用计算机仿真验证了该算法的有效性.     

基于移位内插互质阵列高分辨DOA估计

针对互质阵列现有算法中可估计信源数少,自由度仍低的问题.提出一种新的虚拟域波达方向(DOA)估计算法.首先,对一般互质阵列改进形成移位互质阵列,通过差集数组形成虚拟阵列,增加了阵元个数,提高了阵列自由度;其次,通过虚拟阵元内插对虚拟域中缺失孔洞进行填充,形成连续虚拟阵列;最后,通过最小化原子范数的设计和内插虚拟阵列协方...     

电磁矢量互质阵中基于降维Capon的DOA和极化估计算法

将传统电磁矢量均匀阵列推广为电磁矢量互质阵列,突破了阵元间距不大于半波长的限制。提出了电磁矢量互质阵列中基于降维Capon的波达方向（Direction of arrival,DOA）和极化联合估计算法。该算法无需假设已知极化信息,且只需一维搜索,避免了多维搜索,可实现DOA和极化参数自动配对;与相同阵元数的均匀阵列相比,明显提高了角度估计性能,并拓展了天线孔径,具有相对较高的自由度,且降低了运算复杂度。相同阵列及参数条件下,本文算法的角度估计性能优于ESPRIT算法和三线性分解算法。     

Joint direction of arrival estimation and array calibration for coprime MIMO radar

Compared to large-scale MIMO radar, coprime MIMO radar can achieve approximate estimation performance with reduced antenna number. In this paper, joint direction of arrival (DOA) estimation and array calibration for coprime multiple-input multiple-output (MIMO) radar is considered, and an iterative method for the estimations of DOA and array gain-phase errors is proposed. Based on the received data structure of coprime MIMO radar, trilinear decomposition is firstly adopted to obtain the estimations of transmit and receive direction matrices, which are perturbated by the gain-phase errors. Through equation transformation, the un-perturbated direction matrices and gain-phase errors can be iteratively updated based on Least squares (LS). Finally, the unique DOA estimation is determined from the intersection of transmit and receive direction matrices. The proposed algorithm achieves better DOA estimation and array calibration performance than other methods including estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm, multiple signal classification (MUSIC)-like algorithm and joint angle and array gain-phase error estimation (JAAGE) method, and it performs close to the method with ideal arrays. Multiple simulation results verify the algorithmic effectiveness of the proposed method.     

Two-dimensional angle estimation for monostatic MIMO arbitrary array with velocity receive sensors and unknown locations

In this paper, the problem of two-dimensional angle estimation for monostatic multi-input multi-output (MIMO) array is studied, and an algorithm based on the usage of velocity receive sensors is proposed. The algorithm applies the estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm to obtain automatically paired two-dimensional angle estimation. By utilizing the relationship within the outputs of velocity sensors, the rotational invariance property of ESPRIT does not depend on the array geometry any more. Hence, the proposed algorithm can provide two-dimensional DOA estimation for the MIMO array without the knowledge of sensor locations in the array. The algorithm requires no peak searches, so it has low complexity. Furthermore, it has better angle estimation performance than propagator method using the same sensor configuration. Error analysis and Cramér–Rao bound (CRB) of angle estimation in MIMO radar are derived. Simulation results verify the usefulness of the algorithm.     

MIMO雷达技术综述

多输入多输出（Multiple input multiple output,MIMO）雷达是把无线通信系统中的多个输入和多个输出技术引入到雷达领域,并和数字阵列技术相结合而产生的一种新体制雷达。由于采用了波形分集技术,MIMO雷达拥有许多传统相控阵雷达所无法比拟的优越性。本文对MIMO雷达进行了评述。首先对MIMO雷达的概念和原理进行了说明,并指出其同相控阵雷达的关系;然后对MIMO雷达的特点进行了分析,并据此给出MIMO雷达相对传统相控阵雷达存在的优势和缺点;最后结合MIMO雷达的特点和优势,给出MIMO雷达的几种潜在应用。     

十字阵的单基地MIMO雷达中一种低复杂度的二维DOA估计算法

提出了在单基地多输入多输出(Multiple-input multiple-output,MIMO)雷达中的基于十字阵的一种低复杂度的二维波达方向(Direction of arrival,DOA)估计算法。该算法利用传播算子法(Propagator method,PM)避免了协方差矩阵的构造及其特征值分解,也无需谱峰搜索,从而大大降低了运算的复杂度;同时该算法可实现方位角和仰角的自动配对。本文算法的性能在高信噪比下逼近借助旋转不变技术估计信号参数(Estimation ofsignal parameters via rotational invariance techniques,ESPRIT)算法。文中还推导了目标方位角和仰角的均方误差。仿真结果证明了该算法的有效性。     

DOA estimation of mixed coherent and uncorrelated targets exploiting coprime MIMO radar

We propose a new scheme to estimate the directions-of-arrival (DOAs) of mixed coherent and uncorrelated targets exploiting a collocated multiple-input multiple-output (MIMO) radar with transmit/receive coprime arrays. In the proposed scheme, the DOAs of the uncorrelated targets are first estimated using subspace-based methods, whereas those of the coherent targets are resolved using Bayesian compressive sensing. Compared with the previous works, the proposed approach achieves improved DOA estimation accuracy with a flexible coprime array configuration and may resolve more targets than the number of coarray elements. Theoretical analysis and simulation results validate the effectiveness of the proposed technique.     

双基地MIMO雷达中基于传播算子的DOD和DOA估计算法

多输入多输出(Multiple-input multiple-output,MIMO)雷达利用多个天线发送和接收信号,具有超过传统相控阵的潜在优势.本文提出一种双基地MIMO雷达中基于传播算子的离开角(Direction of departure,DOD)和到达角(Direction of arrival,DOA)估计...     

A nested-PARAFAC based approach for target localization in bistatic MIMO radar systems

Bistatic MIMO radar systems gather several advantages such as increased resilience to electronic countermeasures, unknown receiver location, higher identifiability of targets and direct application of several high resolution adaptive techniques. In this paper, we propose a tensor-based method for joint direction of departure (DoD) and direction of arrival (DoA) estimation in bistatic MIMO radar systems. By assuming that the transmit array is divided into two maximally overlapping subarrays, we initially model the cross-covariance matrix of the matched filters outputs as a Nested-PARAFAC decomposition of a fourth-order covariance tensor. Then, exploiting the structure of this decomposition, we first propose a two stage algorithm for joint DoD and DoA estimation of multiple targets based on double alternating least squares (DALS). In addition, for scenarios in which the number of receive antennas exceeds the number of targets, we propose a closed-form solution to the second stage of the proposed method based on the least squares Khatri-Rao factorization (LS-KRF) concept. Simulation results show that the proposed method offers a highly-accurate localization of multiple targets in real-world scenarios where the antenna elements at the transmit and receive arrays have positioning errors as well as less complexity compared to competing state-of-the-art tensor-based solutions.     

基于双频互质阵列的DOA估计方法

本文提出了一种利用双频工作模式提升互质阵列DOA估计最大可分辨率信号源数目的方法,通过选择单个合适的额外工作频率获取额外不同位置的差协同阵虚拟阵元,进而填充参考工作频率下互质阵列差协同阵中两个缺失的虚拟阵元。相比于单频工作模式,双频工作模式获取了更多均匀分布的虚拟阵元,DOA估计的自由度得到了提升,实现了对更多非相干信号源的DOA估计。