杂波背景下基于交替方向乘子法的低截获频控阵MIMO雷达收发联合优化方法

针对相控阵雷达无法有效实现特定区域能量控制的问题,该文提出一种杂波环境下基于交替方向乘子法(ADMM)的频控阵MIMO(FDA-MIMO)雷达低截获(LPI)优化设计方法。该方法的优化准则是在保证目标参数估计性能的条件下,通过联合设计发射波束和接收滤波器使FDA-MIMO雷达在目标2维(距离-方位)区域上辐射的能量尽量小,即尽可能地降低雷达被截获的概率;接着利用加权求和的方法将优化准则构造成多比例分式规划(FP)和的问题;然后利用循环迭代的方法,将优化问题转化成两个子优化问题;最后基于ADMM方法消除等式约束,并通过最小化2阶2次近似优化问题获得发射波束的闭合解。此外,也分析了该方法的计算复杂度。仿真部分通过输出信干燥比(SINR)、发射和接收方向图验证了该方法的有效性。     

基于ADMM改进的低截获FDA-MIMO雷达发射波束设计

针对信号依赖性杂波与目标位于同一方向上的低截获问题,结合交替方向乘子法（ADMM）,提出了一种改进的频控阵MIMO雷达发射波束设计方法。该方法在保证每个天线上发射能量恒定和信杂噪比限制下,最小化目标区域（距离-方位）的能量辐射。首先,利用广义瑞利熵获得接收滤波器;然后,为了解决分式规划不等式约束的二次规划问题,利用辅助变量,并结合ADMM通过并行处理获得发射波束的优化解;最后,进一步研究了收敛性和计算复杂度。仿真显示,与半正定规划方法相比,所提方法能有效控制发射功率恒定,且很好地在目标处能量聚焦;另外,所提方法在杂波和干扰处形成了-50 dB以上的零陷,有效抑制了杂波和干扰信号。     

干扰条件下MIMO雷达收发联合方向图优化设计

针对干扰条件下MIMO雷达面临的信号截获以及干扰源快速移动等问题,对雷达收发方向图进行优化设计。在发射端利用最小积分旁瓣准则对发射波束矩阵进行优化,将发射信号能量集中到目标空域,降低旁瓣并在干扰方向形成发射零陷;在接收端利用广义对角加载方法优化接收方向图,在提高信号接收稳健性的同时展宽零陷。通过对MIMO雷达收发方向图进行联合优化设计,解决了信号被截获及快速移动的有源干扰等问题,从收发两端共同提高雷达整体性能。通过实验仿真对比分析,验证了所提方法的可行性和有效性。     

基于波形优化和天线位置选择的MIMO雷达波束扫描算法研究

为实现集中式多输入多输出(MIMO)雷达波束扫描,本文在峰值平均功率比(PAPR)、能量以及布尔(天线位置选择)约束下,基于min-max波束图匹配准则,首次提出MIMO雷达天线位置和多组探测波形(一组波形对应一个独立的波束图)的联合优方法。由于非凸PAPR约束、布尔约束以及min-max目标函数的非凸非光滑性导致了优化问题成为典型的大规模NP-难问题。为求解该NP-难优化问题,该文首先利用Lawson算法将min-max问题转化为迭代加权最小二乘(ILS)问题,然后根据上界函数最小化(MM)准则简化ILS优化问题,最后用交替方向乘子法(ADMM)求解简化后的上界优化问题。数值仿真结果检验了所提算法的有效性。      

FDA-MIMO雷达主瓣欺骗干扰对抗方法

频率分集阵列多输入多输出(FDA-MIMO)雷达发射阵列中各阵元的载频相对于起始阵元存在频率偏移。基于频率分集阵列联合波束图存在的角度距离二维相关性,结合空间自适应波束形成技术可用来抑制主瓣欺骗干扰。针对FDA-MIMO 雷达波束形成抑制主瓣欺骗干扰时存在的距离周期性问题,提出了一种采用对数频率偏移来消除距离周期性的方法。该方法用对数频率偏移代替常用的线性频率偏移,克服了FDA-MIMO 雷达联合波束图的距离周期性,取得了更好的抗干扰效果。仿真结果验证了该方法的有效性。     

基于多普勒扩展补偿的FDA-MIMO雷达运动目标检测

频控阵-多输入多输出(FDA-MIMO)雷达在检测运动目标时,由于发射阵元间的频率偏移与目标的速度耦合,因此在慢时间维出现严重的多普勒扩展,进一步造成各接收通道的信号能量无法相干累积,极大降低了系统的检测性能。针对此问题,该文提出一种基于多普勒扩展补偿的FDA-MIMO雷达运动目标检测算法。首先建立了FDA-MIMO雷达运动目标的回波模型,分析了频偏带来的多普勒扩展问题;然后在给出最大似然接收机模型的基础上,提出一种基于插值滤波的重采样算法来补偿FDA-MIMO雷达在检测运动目标时引起的多普勒扩展。仿真结果表明:该文所提算法在抑制多普勒扩展的同时,能够补偿子目标回波在距离维的跨单元走动,实现信号能量的相参累积。      

二维相控阵-MIMO雷达联合发射子阵划分和波束形成设计方法

为了有效地抑制干扰信号并进一步提高雷达系统的性能,该文提出一种基于2维相控阵-MIMO雷达的联合发射子阵划分和波束形成设计方法。该方法首先将MIMO雷达系统的发射阵列等分成一定数目的非重叠子阵并给每个天线分配相同的发射能量,以确保发射信号具有恒模特性;其次,在一定的约束条件下,以最大化接收波束形成器的输出信干噪比为准则建立关于子阵结构、每个子阵对应的发射波束形成权矢量以及接收波束形成权矢量的优化模型,并采用循环迭代方法进行求解。仿真结果证实了所提方法的正确性和有效性。     

基于知识辅助的MIMO雷达波形设计方法

该文针对雷达系统受到天线主瓣和副瓣杂波以及强干扰影响时性能下降问题,提出基于距离扩展目标和杂波先验信息的MIMO雷达波形设计方法。首先建立了目标函数,综合考虑了波束主瓣增益、旁瓣杂波抑制能力以及目标输出SCNR的改善性能;然后在优化问题求解中对约束条件进行松弛,使得波形矩阵空域和时域2维解耦合,从而实现空域波束形成和时域波形设计独立优化求解;其次利用L-BFGS算法设计恒模的发射波形矩阵,形成低副瓣的波束方向图和较深的强杂波抑制凹口,并基于目标输出SCNR最大化准则,利用迭代算法分步求解优化的主瓣发射波形和接收滤波器;最后通过电磁仿真的距离扩展目标数据验证所提算法的有效性。     

基于快速张量分解的波束空间MIMO雷达二维DOA估计算法

传统MIMO雷达由于采用全向发射模式导致目标增益损失严重,致使DOA估计算法性能较差.因此,本文提出基于波束空间MIMO雷达的张量模型和快速张量分解的二维DOA估计算法.波束空间MIMO雷达能够通过发射波束成形技术将发射能量集中到指定空域,弥补传统MIMO雷达的发射增益损失.通过高阶张量模型应用MIMO雷达多脉冲接收数...     

基于时不变点状波束优化的目标距离-角度联合估计

应用频控阵式多输入多输出(FDA-MIMO)雷达实现目标距离-角度联合估计越来越受到人们的重视,利用FDA同时获得发射波束图在角度和距离的自由度.但其性能因波束图的周期性和时变性而降低.因此,该文基于时间调制和距离补偿FDA-MIMO(TMRC-FDA-MIMO)雷达的新波形合成模型,提出了一种改进的基于旋转不变技术的...     

Robust Joint Design of Transmit Beamforming and Receive Filter for TB-MIMO STAP Radar

In this paper, we consider the joint design of transmit beamforming and receive filter for transmit beamspace (TB) multiple-input multiple-output (MIMO) radar red space-time adaptive processing (STAP) under the target information uncertainty. The associated robust joint design problem is formulated by maximizing the signal-to-interference-plus-noise ratio (SINR) to guarantee the target detection performance. An iterative optimization procedure is developed to resolve the NP-hard joint design problem. The optimized transmit beamforming weight vector and receive filter exhibit superior performance in terms of output SINR. Several simulation examples are presented to demonstrate the effectiveness of the proposed algorithm.

     

PR-based SAR reconstruction algorithm for phase noise mitigation based on the hidden convexity

The performance of synthetic aperture radar (SAR) reconstruction is significantly deteriorated by the random phase noises arising from the atmospheric turbulence or frequency jitter of the transmit signal. Recently, the emerging phase retrieval (PR) technique is gradually extended to the SAR reconstruction problem via the phase-corrupted data attributing to its alluring potential for phase noise mitigation. In this paper, a novel PR-based SAR reconstruction algorithm for phase noise mitigation is proposed by jointing alternating direction method of multipliers (ADMM) and Kolmogorov spectral factorization (KoSF). Owing to the exploiting of the hidden convexity of PR-based SAR reconstruction problem and the structure advantage of the quadratic magnitude measurement, the proposed algorithm acquires better robustness for the complex-valued Gaussian white noises and the random phase noises than the existing PR-based SAR reconstruction algorithms. In the experiments, the synthetic scene data and the moving and stationary target recognition Sandia laboratories implementation of cylinders (MSTAR SLICY) target data are provided to verify the validity of the proposed algorithm.     

User clustering and robust beamforming design in multicell MIMO-NOMA system for 5G communications

In this paper, we present a robust beamforming design to tackle the weighted sum-rate maximization (WSRM) problem in a multicell multiple-input multiple-output (MIMO) – non-orthogonal multiple access (NOMA) downlink system for 5G wireless communications. This work consider the imperfect channel state information (CSI) at the base station (BS) by adding uncertainties to channel estimation matrices as the worst-case model i.e., singular value uncertainty model (SVUM). With this observation, the WSRM problem is formulated subject to the transmit power constraints at the BS. The objective problem is known as non-deterministic polynomial (NP) problem which is difficult to solve. We propose an robust beamforming design which establishes on majorization minimization (MM) technique to find the optimal transmit beamforming matrix, as well as efficiently solve the objective problem. In addition, we also propose a joint user clustering and power allocation (JUCPA) algorithm in which the best user pair is selected as a cluster to attain a higher sum-rate. Extensive numerical results are provided to show that the proposed robust beamforming design together with the proposed JUCPA algorithm significantly increases the performance in term of sum-rate as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.     

Beamforming design for energy-constrained full-duplex two-way relaying system

A beamforming design was proposed under simultaneous wireless information and power transfer (SWIPT) protocol.A utility optimization problem was considered aiming to maximize the harvested energy by jointly optimizing the beamforming matrix,the power splitting ratio at the relay and the transmit powers at the sources.Since the formulated joint optimization problem was nonconvex,it was difficult or even intractable to obtain the global optimal solution.To overcome this issue,the objective problem into three subproblems was decoupled which could be solved by the proposed semidefinite relaxation technique and the derived constraints activation solution,respectively.The solution was finally obtained with the proposed convergent iterative algorithm.Simulation results show that the proposed joint optimization scheme achieves the optimal performance.Compared with the traditional half-duplex (HD) algorithm,the proposed algorithm can obtain 2~3 times energy harvesting (EH) efficiency improvement,while the computational complexity increases slightly.     

Security enhancement with joint transmit antenna selection and transmit beamforming under energy harvesting constraints

This paper considers a multiuser multiple‐input single‐output (MISO) broadcasting system with simultaneous wireless information and power transfer (SWIPT), which consists of one information receiver (IR) and several energy harvesting receivers (ERs) which are capable of eavesdropping the legitimate signals. For reducing cost and hardware complexity, transmit antenna selection (TAS) is applied in the transmitter. We aim to maximize the achievable secrecy rate under the individual energy harvesting constraint at the ERs and the transmit power constraint at the transmitter by jointly optimizing TAS, transmit beamforming, and artificial noise (AN). The joint optimization problem is a non‐convex mixed integer programming problem. We apply variable replacements to decouple the variable couplings and relax and approach the binary constraint by the difference of two convex constraints. Afterwards, penalty method and constrained concave convex procedure (CCCP) are applied to transform the relaxed problem into a sequence of semi‐definiteness programming (SDP) problems. Simulation results shows that our proposed joint optimization scheme is superior over existing non‐joint optimization schemes. This paper studies the joint transmit antenna selection (TAS), transmit beamforming, and artificial noise (AN) optimization in a multiple‐input multiple‐output (MISO) wiretap system with simultaneous wireless information and power transfer (SWIPT). The joint optimization problem is nonconvex and we propose a penalty method based scheme to solve it. The simulation results show that our joint optimization scheme is superior to other non‐joint optimization schemes.     

Mutual information–based LPI optimisation for radar network

Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.     

一种基于SIC-CDM的低复杂度混合波束赋形方案

为了平衡毫米波大规模多输入多输出系统的性能和硬件开销,降低系统功耗,以频谱效率为优化目标,在部分连接结构下提出了一种收发端联合设计的低复杂度混合波束赋形方案。首先,基于连续干扰消除将原始优化问题转化为多个子阵的速率优化问题;然后,利用坐标下降法完成模拟波束赋形矩阵设计;最后,引入等效信道矩阵大幅降低矩阵维度,再对其进行奇异值分解获得数字波束赋形矩阵。仿真结果表明,与其他算法相比,所提算法在系统功耗降低的同时保持了较优的性能,且性能逼近部分连接结构的最优方案。     

放大转发双向中继系统中降低总功率的波束成形设计

本文研究了多天线放大转发双向中继系统中在满足源节点信噪比要求条件下最小化系统总功率的波束设计问题。该问题是非凸优化问题,为了有效求解该问题,采用分层优化方法将原问题分解成发送波束成形向量优化、接收波束成形向量优化和中继波束成形矩阵优化三类子问题。发送/接收波束成形向量通过求解Rayleigh商最小化问题来获得。中继波束成形矩阵优化问题通过半正定松弛方法转化成半正定优化问题来求解。在求解这三类优化问题的基础上,提出了一种迭代波束成形算法,并采用单调有界序列定理证明了所提算法的收敛性。计算机仿真表明:所提算法经过若干次迭代即可收敛到稳定点;相比于已有算法,本文算法能显著降低系统总功率。      

Transmit beamforming for space-frequency coded MIMO-OFDM systems with spatial correlation feedback

This paper addresses the problem of joint optimization of transmit beamforming and space-frequency (SF) coding for MIMO-OFDM systems with spatial correlation feedback in broadband communications. This problem is challenging in the sense that the transmitter should be designed to beamform across multiple eigenspaces associated with the multipath environment simultaneously. With arbitrary transmit spatial correlation, the performance analysis for SF-coded MIMO-OFDM systems with beamforming is provided, and a general optimization problem for the beamforming design is formulated. Three suboptimal approaches to design the beamformer based on the derived design criteria are proposed: i) eigenvalue selection scheme; ii) eigenspace selection scheme; and iii) per-subcarrier approach based on decoding at each subcarrier. The proposed schemes take into account the multiple eigenspace information associated with the multipath-delay channel. Improvement in the performance over SF coding without beamforming is shown through simulations in terms of bit error rate. The eigenvalue selection scheme provides the best performance among the proposed algorithms. This scheme locates the subspace associated with the largest eigenvalues in the eigenspace of the covariance matrices. With the eigenvalue selection scheme, the performance improvement is about 3 dB over the SF coding without beamforming for highly correlated channels as shown in our simulations.