A new method for joint DOD and DOA estimation in bistatic MIMO radar

A joint direction of departures (DODs) and direction of arrivals (DOAs) estimation for bistatic MIMO radar via both ESPRIT and SVD of cross-correlation matrix of the received data from two transmit subarrays is presented. The proposed method, with the influence of spatial colored noise eliminated, is effective for three- or more-transmitter configured system. The DOAs and DODs of targets can be solved in closed form and paired automatically. Moreover, the maximum number of targets that can be identified by using this method is also analyzed. Simulation results are presented to verify the effectiveness of the method.     

Direction finding with automatic pairing for bistatic MIMO radar

Direction finding is an important issue for bistatic MIMO radar. A two-dimensional direction finding method with automatic pairing is developed. In the presented method, the property of the kronecker product is first utilized to reformulate the cost function in the quadratic form. Then, by constructing the orthogonality constraint of the target DOA to the quadratic form, all target DODs can be first estimated by solving the constrained quadratic form. Moreover, the pth target DOA can be directly estimated by the eigenvector which is related to the pth target DOD. Thus, the target DOD and DOA can be automatically paired. Finally, simulation results demonstrate that the effectiveness of the presented method.     

阵列误差下的多输入多输出雷达测向技术

针对多输入多输出(Multiple-Input Multiple-Output, MIMO)雷达收发阵列同时存在阵元互耦效应和幅相误差时目标测向性能下降的问题,提出了一种基于Capon波束形成的测向算法.该方法利用Toeplitz特性降低了参数空间维数,并结合Kronecker积特性将发射和接收阵列的阵列误差去耦合,从而对收发阵列误差进行迭代补偿,最终获得目标方位角的估计.仿真结果验证了所提算法的有效性和可行性.     

DOD and DOA estimation in bistatic MIMO radar for nested and coprime array with closed-form DOF

It is well known that sparse array can offer better angle resolution than that of uniform linear array (ULA) in the same number of physical sensors. But in bistatic minimum redundancy sparse array multi-input multi-output (MIMO) radar, it cannot offer closed-form degree of freedom (DOF) for the arbitrary number of sensors with direction of departure and direction of arrival estimation. Therefore, this article introduces a nested array and coprime array into sparse array to solve the problem. First, construct no holes difference-coarray by extracting specified covariance matrix elements. Then, transform the difference-coarray into ULA within bistatic MIMO radar through some mathematical operations. As a result, many angle estimation methods for traditional ULA can be applied to the sparse bistatic MIMO array radar. The proposed algorithm offers closed-form DOFs for sparse array and the array aperture is much larger than that of ULA with identical number of sensors. The usefulness of the proposed methods is verified through computer simulations.     

低快拍下多输入多输出雷达中的角度估计算法

研究了双基地多输入多输出(MIMO)雷达中的角度估计问题,提出了一种低快拍下的MIMO雷达的离开角(DOD)和波达角(DOA)联合估计算法。该算法利用矩阵束方法从接收数据中构造出扩展矩阵来进行奇异值分解(SVD),进而进行二维角度估计联合估计。在低快拍数情况下所提算法的角度估计性能优于传统的借助旋转不变技术的信号参数估计(ESPRIT)方法,同时该算法能自动配对、无需谱峰搜索,而且复杂度也低于传统的ESPRIT算法。分析了所提算法复杂度,推导了克拉美-罗界(CRB)。仿真结果验证了该算法的有效性。     

Coherent angle estimation based on Hankel matrix construction in bistatic MIMO radar

In this article, a novel coherent angle estimation method is proposed for bistatic multiple-input multiple-output radar. First, a decorrelation operation is taken by constructing a Hankel block matrix whose rank equals the number of coherent targets and is independent of the coherency between these targets. Therefore, the signal and noise subspaces of the Hankel block matrix can be estimated properly. Then, in conjunction with the ESPRIT algorithm, the shift invariance properties of the transmit and receive arrays are exploited to estimate the angles of coherent targets with automatic pairing. The numerical simulations demonstrate its validity.     

A modified spatial smoothing-based Nystrom approach for coherent target in bistatic MIMO radar

ABSTRACT

The performance of most angle estimation system degrades when the signal attributes coherency coupled with the high computational burden of the preprocessing technique. This paper addresses the issue of the computational burden of the coherent angle estimation for the bistatic multiple-input multiple-output (MIMO) radar. A modified spatial smoothing technique is initially developed by ensuring the generation of a lower rank kernel matrix of the decorrelated signal via a Nyström approach. Then the formed data matrix is subjected to the shift-invariance technique where the automatic pairing of the angles is estimated without loss of the virtual aperture. Hence, in addition to significantly reducing the computational complexity, the proposed method presents an improved performance against existing techniques verifiable by simulation results.     

宽带双基地MIMO雷达的参数联合估计的新方法

提出了一种基于分数阶功率谱的宽带双基地MIMO雷达中参数联合估计的新方法。在许多情况下,根据窄带信号模型对宽带回波信号中的参数进行估计是不合适的,因此提出一个新的宽带回波信号模型对运动目标参数进行估计。根据分数阶功率谱(FPSD)的峰值点对多普勒频移因子和时延参数进行联合估计。并依据分数阶功率谱的峰值点构造2个子阵,提出的FPSD-MUSIC算法和FPSD-ESPRIT算法实现了对收发角的联合估计。接下来推导了该信号模型中参数估计的克拉美罗界。仿真实验验证了算法的有效性。     

基于降维子空间重构的双基地MIMO雷达角度估计算法

根据双基地MIMO雷达的工作原理和回波模型,结合阵列信号处理,提出了降维子空间重构的角度估计算法,并给出了算法有效性证明。理论分析表明,该算法可以有效解决二维空间搜索计算成本高,矩阵运算量大和低快拍数下算法适应性差的问题,并通过蒙特卡罗实验对不同信噪比、快拍数和接收阵元数等情况下角度估计的方差进行了仿真,证实了理论分析的正确性。     

非均匀矩形阵列下双基地MIMO雷达目标定位方法

该文针对双基地MIMO雷达发射端、接收端皆为非均匀矩形阵列配置情况,将MIMO技术和最小冗余阵列相结合,提出基于双重孔径自由度扩展的目标发射俯仰角、发射方位角、接收俯仰角、接收方位角4参数联合估计新算法。首先利用矩阵Khatri-Rao积的运算特性,构造出2个置换矩阵,对接收信号进行矢量行变换,再通过数据的“去冗余”、“多维平滑”和“折叠”运算,使得新数据具备MIMO雷达自身和最小冗余阵列双重自由度扩展的特点。理论和仿真结果表明：该文算法能够有效估计出目标的4个参数值,且能够实现自动配对;在相同仿真条件下,该文算法的估计精度优于交替最小二乘和多维ESPRIT算法,并且提高了最大可估计的目标数目。     

Novel angle estimation for bistatic MIMO radar using an improved MUSIC

In this article, we study the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar and propose an improved multiple signal classification (MUSIC) algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation. The proposed algorithm obtains initial estimations of angles obtained from the signal subspace and uses the local one-dimensional peak searches to achieve the joint estimations of DOD and DOA. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm, and is almost the same as that of two-dimensional MUSIC. Furthermore, the proposed algorithm can be suitable for irregular array geometry, obtain automatically paired DOD and DOA estimations, and avoid two-dimensional peak searching. The simulation results verify the effectiveness and improvement of the algorithm.     

Robust angle estimation method for noncircular targets in MIMO radar with mutual coupling

A robust angle estimation method for noncircular targets based on unitary tensor decomposition with mutual coupling in multiple-input multiple-output (MIMO) radar was proposed.Firstly,utilizing the banded symmetric Toeplitz structure of the mutual coupling matrix to eliminate the influence of unknown mutual coupling in tensor field.Then a special augmented tensor was constructed to capture the no circularity and its inherent tensor multidimensional structure of noncircular signals.And taking advantage of the centro-Hermitian characteristic of the augmented tensor to transform the sub-tensor into real-values tensor by the unitary transformation.Finally,the signal subspace estimation based on tensor was obtained by taking advantage of the higher-order singular value decomposition (HOSVD) technology,and then the direction-of-departure (DoD) and direction-of-arrival (DoA) estimation was obtained by utilizing the real-values subspace technology.Due to the consideration of both the noncircularity and multidimensional structure,the proposed algorithm has better recognition performance than the existing angle estimation methods.At the same time,the proposed algorithm only requires real-valued operations and has lower computational complexity.Simulation experiments verify the effectiveness and superiority of the proposed algorithm.     

MIMO双基地雷达空间多目标定位方法

该文提出了一种L型阵列配置MIMO双基地雷达空间多目标定位方法。该方法利用L型接收阵列所包含的相对发射阵和接收阵的目标4维角度信息,先对接收信号进行解相干处理,然后根据DOA矩阵法的思想构造估计矩阵,通过特征参数与待估参数之间特定关系,导出了多目标4维角度联合估计算法公式,进而实现双基地雷达的空间多目标定位。该算法不涉及多维非线性谱峰搜索,只需一次特征值分解,计算量较小,且估计出的参数可自动配对。仿真结果表明了该文算法的正确性和可行性。     

Joint parameter estimation of DOD/DOA/polarization for bistatic MIMO radar

In the paper,polarization-sensitive array is exploited at the receiver of multiple input multiple output (MIMO) radar system,a novel method is proposed for joint estimation of direction of departure (DOD),direction of arrival (DOA) and polarization parameters for bistatic MIMO radars. A signal model of polarimetric MIMO radar is developed,and the multi-parameter estimation algorithm for target localization is described by exploiting polarization array processing and the invariance property in both transmitter array and receiver array. By making use of polarization diversity techniques,the proposed method has advantages over traditional localization algorithms for bistatic MIMO radar. Simulations show that the performance of DOD and DOA estimation is greatly enhanced when different states of polarization of echoes is fully utilized. Especially,when two targets are closely spaced and cannot be well separated in spatial domain,the estimation resolution of traditional algorithms will be greatly degraded. While the proposed algorithm can work well and achieve high-resolution identification and accurate localization of multiple targets.     

Low complexity 3D-OMP algorithms for DOD DOA and Doppler frequency estimation in bistatic MIMO radar

The biggest challenge of the traditional 3D orthogonal matching pursuit (OMP) method for direction-of-departure (DOD), direction-of-arrival (DOA) and Doppler frequency estimation in bistatic multiple-input multiple-output (MIMO) radar is the heavy computational burden due to a large number of atoms in the overcomplete dictionary. In this paper, low complexity 3D-OMP algorithms are investigated. First, the traditional 3D-OMP algorithm is given. Then, two-dimensionality reduced OMP-based algorithms are proposed exploiting the property of Khatri-Rao product and proper sparse representation. Also, the multiple measurement vectors (MMV) model is introduced to our OMP algorithms to guarantee the estimation performance. The simulation results show that the DOD, DOA and Doppler frequency can be effectively estimated with a small number of pulses and low computation cost. With similar accuracy compared with the traditional 3D-OMP method, much lower computational burden can be achieved by using the proposed methods.     

互耦条件下基于4阶累积量的双基地MIMO雷达角度估计

发射和接收阵列的互耦效应将使得双基地多输入多输出(MIMO)雷达的角度估计算法性能下降.针对阵列互耦效应和高斯色噪声并存情况,该文提出一种基于4阶累积量组合矩阵构造的收发角度估计方法.该方法首先根据收发互耦矩阵的Kronecker乘积特点,并结合互耦矩阵带状、对称的Toeplitz变换性质,充分利用所有的接收数据,构造...     

一种双基地MIMO雷达目标参数估计算法

为了实现双基地多输入多输出(MIMO)雷达目标参数估计,建立了双基地MIMO雷达信号模型,提出了一种目标方向角和多普勒频率估计方法,该方法利用2次ESPRIT方法分别估计目标的多普勒频率和来波角度(DOA),然后利用ROOT-MU-SIC方法估计得到目标去波方向(DOD)。所提算法只进行3次特征值分解,避免了多维非线性的谱峰搜索,配对过程简单。仿真结果证明了该算法的有效性。     

一种新的双基地MIMO雷达目标参数联合估计算法

摘 要：为了实现双基地多输入多输出（MIMO）雷达目标参数估计,本文建立了双基地MIMO雷达信号模型,提出了一种目标方向角和多普勒频率联合估计方法,该方法通过构造空时矩阵,只进行一次特征值分解,即可得到雷达多目标多参数的闭式解,避免了多维非线性的谱峰搜索,并可实现自动配对。仿真结果证明了所提算法的有效性。     

Joint Doppler frequency, 2D-DOD and 2D-DOA estimation for bistatic MIMO radar in spatial coloured noise

In this paper, we address the problem of four-dimensional angle and Doppler frequency estimation for L-shaped bistatic multiple input multiple output radar in spatial coloured noise. A novel method of joint estimation of Doppler frequency, two-dimensional direction of departure and two-dimensional direction of arrival based on the propagator method is discussed. Utilising the cross-correlation matrix which is formed by the adjacent outputs of matched filter in the time domain, the special matrix is constructed to eliminate the influence of spatial coloured noise. The proposed algorithm provides lower computational complexity and has very close parameter estimation to the estimation of signal parameters via rotational invariance techniques algorithm and DOA-matrix algorithm in high signal-to-noise ratio and Cramér–Rao bound is given. Furthermore, multidimensional parameters can be automatically paired by this algorithm to avoid the performance degradation resulting from wrong pairing. Numerical simulation results demonstrate the effectiveness of the proposed method.     

新的双基地MIMO雷达角度估计方法

为降低双基地MIMO雷达前端数据处理的计算量,构造出了“扩展”信号子空间,并根据此信号子空间的特点,提出了多项式求根—空域滤波的收发角度估计算法,避免了二维谱搜索,实现了目标角度的自动配对,并推导了多目标和单目标下双基地MIMO雷达角度估计的克拉美罗下界（CRB）。研究表明空域滤波时,泰勒级数展开的阶数越高,目标的角度估计精度越好;当目标各发射角度相隔较近时,仍能得到较好的估计结果;在低信噪比时,估计精度优于ESPRIT算法,在高信噪比时,2种算法的估计精度均接近于CRB。