集中式 MIMO 雷达部分相关波形设计与处理

该文针对集中式 MIMO 雷达发射方向图设计与波形设计无法分离,以及接收端如何提取信号多样性自适应地抑制杂波和干扰这两个问题,展开了深入研究.首先,给出了一种改进的快速发射波束形成算法,该算法能够有效地将发射方向图设计和波形设计分离.同时,为了避免发射信号相关矩阵出现奇异性导致信号多样性无法提取的问题,提出了采用特征值加载修正信号相关矩阵的方法.接着,给出了采用上述发射波形的 MIMO 雷达的接收阵列信号处理框架,证明了经过匹配处理后的阵列输出可以最大程度地恢复信号多样性信息.仿真实验表明,采用这种部分相关发射波形的 MIMO 雷达仍然能够充分利用信号多样性带来的额外自由度,有效抑制干扰和杂波.     

MIMO天波雷达波形综合分析与改进

针对天波雷达应用背景及实际需求,详细分析了多输入-多输出(Multiple-Input Multiple-Output,MIMO)天波雷达波形设计问题,对典型MIMO天波雷达波形的优缺点和适用探测任务进行了综合比较,并得出了部分波形之间的关系。为改善已有波形在多普勒容限、速度模糊和频率限制,提出了一种慢时间随机相位编码波形。相关结论和改进措施为MIMO天波超视距雷达信号理论研究、工程实现提供了参考。     

MIMO雷达的最小冗余线性阵列配置与优化

提出了一种利用最小冗余非均匀线性阵列对多输入多输出(MIMO)雷达系统进行阵列配置优化从而提高参数估计性能的方法。文中从MIMO雷达信号模型出发,分析了均匀线性阵列与非均匀线性阵列两种配置下,MIMO雷达系统获得的虚拟阵元数的差异,给出了一种在物理阵元数量较大时最小冗余非均匀线性阵列的生成方法。仿真结果表明:最小冗余线性阵列能够利用较少的物理阵元个数获得与均匀线性阵列相同的参数估计性能。而在物理阵元个数相同的情况下,最小冗余非均匀线性阵列MIMO雷达可以获得更多的虚拟阵元、更好的参数估计性能和更低的克拉美·罗界。     

多载频MIMO雷达解速度模糊及综合处理方法

多载频MIMO雷达采用稀布阵发射多载频FMCW信号,阵列接收目标回波。该文分析了多载频MIMO雷达的信号模型,提出了一种解速度模糊的新方法,该方法不需发射多重频信号,利用各发射通道模糊多普勒频率获得目标真实速度的最小二乘解。还提出了一种新的发射接收综合处理方法,该方法将积累后每个距离单元等分成Nn份,并用相参积累结果对其加权,在抑制距离栅瓣的同时充分利用了收发阵列孔径。最后讨论了多载频MIMO雷达的参数选取问题。仿真结果表明了该文方法的有效性。     

MIMO雷达中OFD-LFM-PC波形空时优化设计

MIMO雷达中传统正交频分线性调频( OFD-LFM)波形的空域合成信号存在较高的自相关栅瓣。为了解决这一问题,本文在OFD-LFM波形上调制相位编码序列,构造新的正交频分线性调频相位编码(OFD-LFM-PC)波形以消除空域合成信号自相关栅瓣。由于相位编码的调制,使得OFD-LFM-PC波形空域合成信号的自相关栅瓣消除但整体旁瓣水平有所升高,同时,发射功率方向图非全向。为此,基于OFD-LFM-PC波形的时域特性和空域特性分析,本文建立了空时特性优化模型,对调制的相位编码矩阵和载波频率编码序列进行联合优化,并提出了一种嵌套遗传算法的粒子群算法求解该优化问题。仿真结果表明,所优化设计的OFD-LFM-PC波形能够保证发射功率方向图的全向性,并且空域合成信号具有良好的自相关性能。     

一种分布式MIMO雷达正交波形和失配滤波器组联合设计方法

针对分布式MIMO雷达正交相位编码信号和其失配滤波器组分开设计输出的距离旁瓣电平仍然过高的问题,该文提出一种正交相位编码信号和失配滤波器组联合设计方法。首先,以约束信噪比损失和最小化失配滤波组输出的距离旁瓣电平为目标,构建联合设计准则。然后,根据最小p范数算法的理论,给出一种基于L-BFGS算法的双最小p范数算法进行求解。仿真结果表明,与分开设计方法相比,该文方法输出的距离旁瓣电平可以进一步降低。     

MIMO Radar Using Compressive Sampling

A multiple-input multiple-output (MIMO) radar system is proposed for obtaining angle and Doppler information on potential targets. Transmitters and receivers are nodes of a small scale wireless network and are assumed to be randomly scattered on a disk. The transmit nodes transmit uncorrelated waveforms. Each receive node applies compressive sampling to the received signal to obtain a small number of samples, which the node subsequently forwards to a fusion center. Assuming that the targets are sparsely located in the angle-Doppler space, based on the samples forwarded by the receive nodes the fusion center formulates an $ell_{1}$ -optimization problem, the solution of which yields target angle and Doppler information. The proposed approach achieves the superior resolution of MIMO radar with far fewer samples than required by other approaches. This implies power savings during the communication phase between the receive nodes and the fusion center. Performance in the presence of a jammer is analyzed for the case of slowly moving targets. Issues related to forming the basis matrix that spans the angle-Doppler space, and for selecting a grid for that space are discussed. Extensive simulation results are provided to demonstrate the performance of the proposed approach at difference jammer and noise levels.      

Signal Processing for Passive Radar Using OFDM Waveforms

Passive radar is a concept where illuminators of opportunity are used in a multistatic radar setup. New digital signals, like Digital Audio/Video Broadcast (DAB/DVB), are excellent candidates for this scheme, as they are widely available, can be easily decoded to acquire the noise-free signal, and employ orthogonal frequency division multiplex (OFDM). Multicarrier transmission schemes like OFDM use block channel equalization in the frequency domain, efficiently implemented as a fast Fourier transform, and these channel estimates can directly be used to identify targets based on Fourier analysis across subsequent blocks. In this paper, we derive the exact matched filter formulation for passive radar using OFDM waveforms. We then show that the current approach using Fourier analysis across block channel estimates is equivalent to the matched filter, based on a piecewise constant assumption on the Doppler-induced phase rotation in the time domain. We next present high-resolution algorithms based on the same assumption: first we implement MUSIC as a 2-D spectral estimator using spatial smoothing; then we use the new concept of compressed sensing to identify targets. We compare the new algorithms and the current approach using numerical simulation and experimental data recorded from a DAB network in Germany.      

Improvement of EMC by Applying Ambiguity and Environmental Diagrams to the Design of Radar Waveforms

A technique for improving the electromagnetic compatibility of a radar system with respect to its operating electromagnetic environment and to assess RF spectrum usage is presented. The technique involves the use of the ambiguity diagram derived from the waveform and the construction of environinental diagrams for the radar. Overlays of the ambiguity diagram upon the environmental diagram, along desired target trajectories, provide a pictorial view by which EMC analysis and spectrum usage can be interpreted. The technique lends itself to the early phases in radar concept or development where waveform design can be modified. The technique also lends itself to assessing design towards receivèr interference rejection. Only nominal system parameter data is required for implementation.     

应用正交码组信号的传统雷达距离旁瓣抑制方法

为了抑制传统雷达的距离旁瓣和提高传统雷达抗欺骗式干扰性能,该文提出一种传统雷达随机发射一组正交信号的信号发射策略。给定一组正交性好且距离旁瓣低的相位编码信号,雷达在每次发射时从这组波形中随机选取一个波形进行发射,接收端已知该发射信号波形并基于该波形对接收信号进行脉冲压缩,最后对多次相邻脉冲的回波信号进行相干积累。理论分析和仿真结果均表明,距离主瓣信号能够有效积累,而距离旁瓣信号近似白化,因而脉冲积累后可明显降低系统的最大距离旁瓣电平。     

MIMO雷达正交混沌调频波形集设计

正交波形设计是实现MIMO雷达的关键技术之一,目前正交波形设计方法主要多采用统计优化算法,如模拟退火、遗传算法等,此类方法主要缺点是算法耗时长、效率低,且所设计的波形集性能随着波形个数的增加而下降,针对此问题,提出一种基于混沌调频的MIMO雷达正交波形集设计方法,采用混沌调频信号作为MIMO雷达的发射波形,利用混沌序列良好的统计特性,无需寻优处理即可得到性能优越的正交波形集,且理论上可以得到任意数目的波形而不损失波形集性能,因此,该方法在算法效率和波形多样性方面具有优势,计算机仿真实验验证了设计方法的有效性。      

MIMO跳频通信系统及其序列设计

在跳频通信系统中应用MIMO技术可以进一步提高数据传输速率和频谱利用率,但是多用户跳频通信系统还受到多址干扰和多径干扰的影响.本文提出一种T-NHZ时频序列的构造方法,应用到MIMO跳频系统中以消除多址干扰和多径干扰,同时由于这种序列的数目较大,有利于进一步提高系统容量.     

一种MIMO雷达多模式波形优化设计方法

在多目标多任务情况下,通常要求雷达具有多种工作模式,以实现搜索、跟踪等不同功能。传统雷达在某一时刻只能实现一种功能,工作模式不够灵活,很难高效利用系统资源。针对此问题,该文提出一种MIMO雷达多模式波形设计方法,该方法以方向图逼近、期望方向的信号功率谱或频谱逼近等为准则,在恒模约束下建立关于波形矩阵的多目标优化模型,并采用共轭梯度方法进行优化求解。仿真结果表明,所设计波形在空域上具有多波束方向图,波束指向上的信号具有多种工作模式的特性,可以同时实现搜索、跟踪等功能。     

波形相关矩阵未知情况下单基地MIMO雷达中一种改进MUSIC的DOA估计算法

该文研究了波形相关矩阵未知情况下多输入多输出(MIMO)雷达中的角度估计问题,提出了一种单基地MIMO雷达中改进多重信号分类(MUSIC)的到达角(DOA )估计算法。该算法可以在波形相关矩阵未知的情况下工作且性能优于传统的传播算子(PM)和借助旋转不变技术估计信号参数(ESPRIT)算法以及基于接收信号重构的MUSIC算法。该文算法可以扩展到任意阵列结构的MIMO雷达中进行角度估计。该文还给出了单基地MIMO雷达中DOA估计的克拉美罗界(CRB)。仿真结果验证了该算法的有效性。     

提高MIMO雷达估计性能的稳健波形优化设计

多输入多输出雷达的波形优化基于初始参数估计值,通常对参数估计误差较敏感。稳健波形设计通过将参数不确定性显式包含进优化问题以减轻敏感性。基于克拉美-罗界,在参数不确定凸集上考虑改善最差参数估计性能的稳健波形优化问题。提出一种优化波形相关阵的迭代算法以改善最差参数估计性能。迭代中的每步都可通过凸松弛求解。仿真表明,相对于不相关波形,所提方法可显著提高最差参数估计性能。     

最小化旁瓣的MIMO雷达发射方向图优化算法

为了获得低旁瓣的MIMO雷达发射方向图,该文提出一种新的最小化峰值旁瓣或积分旁瓣的MIMO雷达方向图优化算法.由于最小化峰值旁瓣或积分旁瓣的优化问题为非凸问题,该算法通过两步来得到此非凸优化问题的全局最优解.第1步通过对发射总功率的约束进行松弛,将原问题转变为一个凸优化问题,第2步则将第1步得到的解进行尺度变换使其满足发射总功率的约束,从而得到原问题的全局最优解.仿真实验表明了该算法相比于已有算法可以获得更低的峰值旁瓣或更低的积分旁瓣.     

批次处理解决气象雷达距离模糊

借鉴WSR-88D雷达所采用的批次处理方法，并对该算法进行了改进，加入了噪声功率门限判断，使回波数据保留了更多的信息量。介绍了雷达终端、临控和信号处理所实现的功能，并且从工程实现的角度讲述批次处理的时序设计和DSP软件设计的流程。改进后的算法在3830气象雷达上得以实现，给出的试验结果表明该方法具有较好的解距离模糊效果。     

MIMO Radar Beamforming Using Orthogonal Decomposition of Correlation Matrix

MIMO radar is the next generation radar which transmits arbitrary waveforms at each one of its apertures. It has been shown that the design of waveforms for MIMO radars in order to synthesize a desired spatial beampattern is mapped into a waveform correlation matrix R design in the narrowband case. As of now, given a desired beampattern or estimated locations information of targets, calculating R has been modeled as an optimization problem like semi-definite programming. Also, in some special cases like rectangular beampattern, closed-form solutions for R has been proposed. In this paper, we introduce a fast algorithm which is capable of designing R in order to achieve more arbitrary beampatterns. Our proposed algorithm is based on eigenvalue decomposition of correlation matrix which employs neither an optimization process nor an iteration one. Furthermore, the proposed algorithm leads to uniform elemental power, low sidelobe level and targets decorrelation which is a great boon, looking from both the hardware and the software perspective. Here, we also introduce a novel algorithm which can work in tandem with the eigenvalue decomposition algorithm and other existing correlation matrix design algorithms to enhance or adapt the designed beampattern.     

基于MIMO噪声雷达的高速运动目标检测

针对传统体制雷达对高速运动目标不能进行长时间有效相参积累检测问题,该文提出了一种基于MIMO噪声雷达的高速运动目标检测方法。该方法利用MIMO噪声雷达在短时间内输出的多路回波数据进行相参并行处理来取代回波数据的长时间相参积累检测,以避免距离走动,径向速度变化以及反射截面积(RCS)快起伏等非平稳因素对目标检测的影响,有效实现了多个高速运动目标的无模糊检测。仿真结果验证了MIMO噪声雷达在高速运动目标检测方面的优越性。