Adaptive detection with conic rejection to suppress deceptive jamming for frequency diverse MIMO radar

With traditional radar systems, it is not easy to classify and suppress the intended false targets, especially in case of the mainlobe deceptive jamming. In this paper, the deceptive jamming suppression issue is formulated as a problem of detecting the presence of target signal while rejecting potential deceptive jamming under the multiple-input multiple-output (MIMO) radar with frequency diverse array (FDA) as the transmit array. The problem at hand is settled by resorting to the generalized likelihood ratio test (GLRT); at the design stage we define the sets where the false target and true target lie in. Since FDA-MIMO radar provides controllable degrees of freedom in both range and angle domains, the sets are range–angle related. This implies that both range and angle properties can be used to suppress the false targets. Based on the detector, a two-pulse scheme is proposed to guarantee high rejection probability of deceptive jamming. At the analysis stage, the performance of the detector is assessed in comparison with the conventional MIMO scenario and other detectors. The performance assessment shows that the proposed solutions are effective in the presence of electronic countermeasure (ECM) systems, especially when facing mainlobe deceptive jamming.     

Colocated MIMO radar waveform-design based on two-step optimizations in spatial and spectral domains

We propose an efficient colocated multiple-input multiple-output radar waveform-design method based on two-step optimizations in the spatial and spectral domains. First, a minimum integrated side-lobe level strategy is adopted to obtain the desired beam pattern with spatial nulling. By recovering the hidden convexity of the resulting fractional quadratically constrained quadratic programming non-convex problem, the global optimal solution can be achieved in polynomial time through a semi-definite relaxation followed by spectral factorization. Second, with the transmit waveforms obtained via spatial optimization, a phase changing diagonal matrix is introduced and optimized via power method-like iterations. Without influencing the shape of the optimized beam pattern, the transmit waveforms are further optimized in the spectral domain, and the desired spectral nulling is formed to avoid radar interference on the overlaid licensed radiators. Finally, the superior performance of the proposed method is demonstrated via numerical results and comparisons with other approaches to waveform design.     

非正侧视机载雷达一种改进的多普勒频移算法

非正侧机载雷达的杂波分布随距离变化而变化,各距离单元的杂波分布不再满足独立同分布条件,导致统计型STAP处理器性能下降。多普勒频移（Doppler Warping,DW）算法沿主波束方向对杂波非均匀进行了补偿,但在其余方向上杂波非均匀依然存在,因而性能较差。提出了一种改进的非正侧视机载雷达杂波抑制算法——修正的多普勒频移法（Modified Doppler Warping,MDW）,先通过多普勒频移法使各距离单元的杂波谱在主波束方向重合,再沿多个多普勒通道使参考单元和检测单元的杂波谱保持一致,进一步消除非正侧视机载雷达的杂波非均匀程度。仿真结果表明,与原有方法相比,该方法的杂波抑制性能有明显提高,且运算量增加不多,是一种具有工程应用价值的方法。     

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 sparse direction-of-arrival estimation algorithm for MIMO radar in the presence of gain-phase errors

In this paper, the problem of direction-of-arrival (DOA) estimation for monostatic multiple-input multiple-output (MIMO) radar with gain-phase errors is addressed, by using a sparse DOA estimation algorithm with fourth-order cumulants (FOC) based error matrix estimation. Useful cumulants are designed and extracted to estimate the gain and the phase errors in the transmit array and the receive array, thus a reliable error matrix is obtained. Then the proposed algorithm reduces the gain-phase error matrix to a low dimensional one. Finally, with the updated gain-phase error matrix, the FOC-based reweighted sparse representation framework is introduced to achieve accurate DOA estimation. Thanks to the fourth-order cumulants based gain-phase error matrix estimation, and the reweighted sparse representation framework, the proposed algorithm performs well for both white and colored Gaussian noises, and provides higher angular resolution and better angle estimation performance than reduced-dimension MUSIC (RD-MUSIC), adaptive sparse representation (adaptive-SR) and ESPRIT-based algorithms. Simulation results verify the effectiveness and advantages of the proposed method.     

On the role of waveform diversity in MIMO radar

MIMO radar employs multiple antennas to simultaneously transmit diverse waveforms, as well as multiple antennas to receive the radar returns. This paper studies the role of waveform diversity in MIMO radar as separate and distinct from the role of the multiple transmit antennas. This is done by comparing a MIMO radar system to a scanning phased array radar which uses the same transmit and receive arrays but only a single waveform. The performance characteristics of the two systems, in terms of the ambiguity function and the spatial response, are compared for single pulse operation as well as multi-pulse operation with coherent integration. Both element-space and beam-space systems are considered.     

Range‐angle target indication using FDA‐MIMO with sinusoidal element spacing

By introducing a tiny frequency increment across the array elements, frequency diverse array (FDA) radar produces a range‐angle‐dependent beampattern. However, the range‐angle coupling and time‐variant problem block the application potential of the conventional FDA. Employing sinusoidal element spacing and symmetrical sinusoidal modulated frequency offsets, a novel scheme termed as Sin‐FDA is proposed. To eliminate the time‐varying effect, multiple‐input multiple‐output technique and multiple matched filters at receiver are adopted. The proposed scheme can generate a pencil‐shaped beampattern with smaller spatial region of mainlobe in range‐angle domains, which is helpful for improving the target indication performance. Furthermore, the beampattern produced by the proposed scheme has narrower mainlobe both in the range and angle dimensions as well as acceptable sidelobe level. The exploration of nonuniform element spacing can better direct the range‐angle decoupled beampattern design for FDA radar. Simulation results validate the superiority of the proposed scheme over the existing decoupled FDA systems.     

线性调频信号的一种新的频域脉压处理方法

线性调频波形由于多普勒性能突出，一直是一种在雷达中具有广泛应用的脉冲压缩波形，但是线性调频的距离旁瓣不够理想，强目标的旁瓣过高就有可能淹没弱目标的主瓣。该文根据线性调频信号的频谱结构，采用频域数字处理技术，提出了一种新的基于理想压缩脉冲的频域滤波器（SSF）设计方法，导出了可实现低的压缩脉冲距离旁瓣的条件。与其它方法相比，线性凋频信号由该文方法压缩后主副瓣比得到很大的提高，并且主瓣不会展宽，因此不影响距离分辨力。通过数学公式推导和计算机仿真表明，所提出的方法是正确的和可行的，而且步骤简单，运算量小，易于实现。     

基于DPSS投影矩阵的单通道运动目标检测方法

为了提高机载单通道雷达在低多普勒分辨率情况下的运动目标检测性能,提出了一种基于离散长球序列(DPSS)投影矩阵的运动目标检测方法.首先根据系统参数构造DPSS投影矩阵,然后利用正交DPSS投影矩阵抑制主瓣杂波,最后在多普勒域进行运动目标检测.该方法在抑制主瓣杂波的同时能够比较好地保留目标的能量,能够明显提高目标的检测性能.仿真实验验证了上述方法的有效性.     

极化MIMO雷达隐身目标检测性能研究*

多输入多输出(MIMO)雷达使用了远距分布的阵元,它利用了信号的空间分集增益来获取更多的目标信息。极化是另一种可以提高雷达系统性能的分集方式。当应对隐身目标时,传统的极化雷达在某些观测角度会遭受到较大的目标雷达截面积(RCS)衰减,而无法获得较好的检测性能。而在一个雷达系统中同时利用这两种分集增益,可以得到一种比传统极化雷达更具优势的新雷达检测系统——极化统计MIMO雷达,它可以更好地应对隐身目标检测。给出了相应的模型,并推导出了该雷达系统的检测性能解析式。将其与传统相控阵及非极化统计MIMO雷达比较,可以看到极化统计MIMO雷达的检测性能更佳。联系到隐身目标的特性,极化MIMO雷达的检测器特性应对它时具有显著优势。最后,以上方法通过仿真得到了验证。     

基于高阶累积量的最大似然估计方法及其应用

讨论了高距离分辨率制导雷达的近距角闪烁抑制问题,提出了利用超分辨谱估计算法对混叠在同一距离分辨单元内的两个或多个散射中心进行离析,然后采用最大似然估计方法分别估计各个散射中心谐波分量幅度与相位信息的新方法.实验结果表明,该方法能够有效克服目标多散射中心之间的干涉现象,为解决末制导过程中目标的稳定跟踪问题提供了一种有效途径.     

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.     

机载MIMO STAP收发天线联合设计研究

针对机载多输入多输出雷达进行动目标检测时,天线稀疏出现栅瓣导致盲速、天线密布导致冗余及布阵需考虑平台尺寸等问题,对天线结构进行研究.首先基于相位中心等效原理,讨论一定收发阵元数目下如何实现最大自由度和最大孔径;然后根据机载平台结构,设计更合理的收发天线布阵结构;最后结合多相编码进行空时自适应处理,实现动目标检测和杂波抑制.仿真实验表明,与其他天线结构相比,本文方法可获得更好的动目标检测性能.     

基于联合收发权值优化的认知雷达MIMO-STAP

研究了认知雷达中多收多发空时自适应处理(MIMO-STAP)联合收发权值优化问题。提出了一种在收发两端联合空时自适应处理(JSTAP)的方法,该方法通过对收发权值联合寻优以获得最优的信干噪比。分析了受发射权值影响的杂波协方差矩阵结构,并基于此建立了MIMO-STAP的权值迭代更新结构。其权值迭代更新步骤为:固定发射权值,求解优化模型得到接收权值;然后固定接收权值,根据杂波协方差矩阵与发射权值的关系,得到发射权值;返回接收权值优化步骤,循环迭代以获得最优收发权值。仿真实验结果表明在慢速目标环境中,联合空时处理与常规空时处理相比,有效提高了接收端的信干噪比。     

利用目标与杂波先验知识的机载雷达发射波形自适应生成方法

发射波形自适应能够优化雷达在检测、跟踪和抗干扰等方面的能力,但其性能的好坏与雷达目标和杂波先验知识有很强的相关性。采用最大输出信杂噪比准则设计的雷达发射波形自适应方法已经在理论上被证实可行和有效。为了提升这类方法的实际应用价值,本文利用Swerling统计模型和数字高程模型（Digital elevation model,DEM）提供的目标和杂波先验信息,针对机载相控阵雷达,分析了基于最大输出信杂噪比（Signal-to-clutter-noise ratio,SCNR）准则的发射波形自适应方法性能和实用价值。仿真结果表明,这类发射波形能够自适应地随着目标和杂波的变化而改变,并实现二者的最优匹配,在提升雷达输出信杂噪比上优于传统发射波形,具有良好的实际应用前景。     

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.     

A new approach to dual-band polarimetric radar remote sensing image classification

1 Introduction Comparing with a traditional synthetic aperture radar (SAR), a polarimetric SAR is able to provide target scattering characteristics in the polarimetric domain, so more in- formation is available for applications of radar remote sensing such as target detection, scattering behavior analysis and classification, etc.; a dual-band polarimetric SAR even provides frequency domain information for remote sensing applications, which achieves better result than a single band polarimet…     

机载雷达级联降维空时自适应杂波抑制方法

提出一种机载雷达杂波抑制的级联降维空时自适应算法,即,先对全空时两维接收数据进行预滤波处理,将杂波局域化,降低杂波自由度;然后对预处理输出的信号的相关矩阵进行子阵划分,求解低维权向量,进一步降低运算量和采样要求。理论分析和实验仿真结果表明,所提算法具有良好的收敛性能和杂波抑制能力,并且对于阵元随机幅相误差和杂波起伏具有很好的容差能力。基于实测数据的实验验证了算法的有效性和稳健性。     

Robust and fast iterative sparse recovery method for space-time adaptive processing

Conventional space-time adaptive processing (STAP) requires large numbers of independent and identically distributed (i.i.d) training samples to ensure the performance of clutter suppression, which is hard to be achieved in practical complex nonhomogeneous environment. In order to improve the performance of clutter suppression with small training sample support, a robust and fast iterative sparse recovery method for STAP is proposed in this paper. In the proposed method, the sparse recovery of clutter spatial-temporal spectrum and the calibration of space-time overcomplete dictionary are achieved iteratively. Firstly, the robust solution of sparse recovery is derived by regularized processing, which can be calculated recursively based on the block Hermitian matrix property, afterwards the mismatch of space-time overcomplete dictionary is calibrated by minimizing the cost function. The proposed method can not only alleviate the effect of noise and dictionary mismatch, but also reduce the computational cost caused by direct matrix inversion. Finally, the proposed method is verified based on the simulated and the actual airborne phased array radar data, which shows that the proposed method is suitable for practical complex nonhomogeneous environment and provides better performance compared with conventional STAP methods.     

基于改进的AR模型的逆波束形成方法研究

逆波束形成是利用各阵元接收信号间的互功率谱估计声场平面波强度的理论,较之常规波束形成,它具有更高的方位分辨能力和噪声干扰抑制能力。在分析逆波束形成理论及其傅立叶类求解算法的基础上,提出了基于改进的AR模型的求解方法。该方法将参数模型引入到逆波束形成的求解当中,通过引入前向后向平均,克服了信号协方差矩阵在小信噪比和快拍数较少情况下估计不准的问题,从而减轻了旁瓣的起伏,有助于实现对弱目标信号的检测与估计。通过大量计算机仿真实验,证实了所提算法的可行性和优越性。