一种相位编码信号和失配滤波器联合优化方法

针对相位编码信号和失配滤波器分开优化输出的距离旁瓣电平仍然过高的问题,提出了一种恒定主瓣宽度的相位编码信号和失配滤波器联合优化方法．首先,在给定发射信号持续时间和需要的距离分辨率的条件下,给出了恒定主瓣宽度的相位编码信号和失配滤波器联合优化准则;然后,基于罚函数法和p范数理论,将带约束并且非光滑的优化问题进行转化;最后,使用最小p范数算法进行求解．仿真实验表明,在给定发射信号持续时间和需要的距离分辨率的条件下,与分开优化方法相比,该联合优化方法输出的峰值旁瓣电平分别可以降低10.72dB和4.77dB．     

一种空时联合优化的MIMO雷达波形设计方法

针对多输入多输出(MIMO)雷达波形设计中空域合成信号的时域特性较差的情况,提出了一种空时联合优化的MIMO雷达波形设计方法．该方法在波形设计中对波形的空域功率分布以及空域合成信号的自相关特性进行了联合考虑．基于空域信号的自相关旁瓣电平以及各阵元信号间的相关性,对集中式MIMO雷达的正交波形设计与具有特定方向图的波形设计建立了统一的优化模型,并采用序列二次规划方法与加权迭代方法求解．仿真结果表明,文中所设计的波形不仅能够很好地逼近期望方向图,而且空域合成信号具有较好的自相关特性．     

均匀直线阵下通用信号模型稳健波束形成算法

针对非相干散射信号源稳健波束形成问题,提出了一种均匀直线阵下通用信号模型稳健波束形成算法．该算法通过引入数据共轭重排理论,利用定义的两个转换矩阵,重新构造信号协方差矩阵,给出了最优权矢量的实值闭式表达式,减少了算法的计算复杂度．仿真分析了期望信号信噪比、指向误差、快拍数及失配约束参数对输出信干噪比的影响．仿真实验表明,通过对接收数据的共轭重排再利用,提高了算法在快拍数有限、存在有用信号失配及其他失配等非理想条件下的输出性能．     

信号稀疏表示下的空域-极化域参数估计

为提高二维波达方向(DOA)和极化参数的估计精度,利用入射电磁波信号在空域分布的稀疏性,提出了一种基于信号稀疏表示的空域-极化域参数估计新方法。首先,利用基于中心共点的偶极子和磁环对阵列接收到的电场分量和磁场分量,构建了不包含极化参数的新的协方差矩阵。然后,将该协方差矩阵矢量化,得到其矢量形式的稀疏表示模型,并通过稀疏重构算法获得了波达方向估计结果。最后,结合电场数据分量与磁场数据分量的互协方差矩阵,构建包含极化参数的矢量化观测数据模型,并采用全局最小二乘法计算得到入射信号的极化参数估计结果。计算机仿真结果表明,本文算法可以有效地估计入射信号的波达方向和极化参数,具有较高的估计精度和较强的角度分辨能力。     

直扩分层空时结构在下行衰落相关MIMO中的应用

为了提高分层空时结构在下行衰落相关多输入多输出系统中的传输性能,提出了一种结合了特征波束形成的直扩分层空时结构．发射机利用信道空域协方差矩阵的特征矢量,对每一层发射码元进行扩频和特征波束形成加权,形成正交的空域特征波束来承载扩频后的信号码元;接收机则通过解扩处理分离来自不同波束上的信号,有效地抑制了共信道干扰．新结构的优点是无需设计扩频序列并且可以应用于下行传输,其代价是要占用一定的扩频频谱资源．实验结果表明,新结构明显优于基于迫零算法的分层空时结构．     

机载雷达非正侧面阵近程杂波抑制新方法

根据机载雷达非正侧面阵的近程杂波随距离快变的特性,提出了俯仰向空域滤波子阵合成的算法．该算法利用平面阵列天线在俯仰向的自由度,先对近程杂波进行滤除,然后再在方位空域和时域做空时自适应处理．这样就增强了远程杂波的距离平稳性,很容易准确地估计协方差矩阵,从而提高了空时自适应处理抑制非正侧面阵杂波的性能．仿真结果证明了无误差时改善因子可以提高约30dB．     

矢量阵自适应零陷强干扰抑制目标方位估计方法

针对方位范围未知的远场强干扰背景下声呐弱目标信号的检测与方位估计问题，本文提出了将自适应空域矩阵滤波技术、矢量信号处理技术及平面波方位估计技术结合的方法。通过最小化滤波后矢量阵信号输出功率以及约束滤波器通、阻带响应，产生自适应零陷干扰抑制效果，并利用二阶锥凸优化的方法首次求解得到了矢量阵自适应空域滤波器。仿真及试验结果表明：矢量阵自适应空域滤波器空域特性相比声压阵自适应空域滤波器更优，矢量阵数据自适应预滤波后再进行方位估计，方位未知的远场强干扰能够被更有效地自适应抑制，进而能够提升矢量线列阵声呐远程弱目标被动探测性能。     

稳健的MIMO雷达发射波形和接收滤波器联合优化设计

针对杂波条件下目标反射信号方向不确定的情况,提出一种稳健的MIMO雷达发射波形和接收滤波器联合优化设计方法.在考虑各阵元发射功率相等的约束条件下,利用发射加权矩阵构造不确定集范围内关于输出信干噪比(SINR)的Maxmin优化模型;在此基础上,利用序列优化、半正定松弛和Charnes-Cooper转换,将非凸的联合优化问题转化为关于发射波形和接收滤波器的凸优化问题进行迭代求解;最后通过随机向量合成方法计算最终发射波形和接收滤波器,并对算法计算复杂度和收敛性给出分析和证明.所提方法在满足阵元发射功率一致的约束条件下,提高了算法稳健性并降低了计算复杂度.仿真实验证明了算法的有效性.     

基于改进阻塞矩阵的DMA小信号主瓣保形与导向失配恢复方案

传统阵列天线在运用阻塞矩阵预处理对抗主瓣强干扰过程中，期望小信号会出现主瓣失真，峰值偏移和旁边电平上升，造成一定的信息损失，影响阵列天线接收信号的输出信干噪比(Signal-to-Interference-Noise Ratio, SINR)。为解决这个问题，提出一种基于改进阻塞矩阵的动态超材料天线(Dynamic Metamaterial Antenna, DMA)小信号主瓣保形与导向失配恢复方案。首先，基于DMA结构特性设计改进阻塞矩阵，对接收信号进行预处理；其次，采用权矢量补偿方法对小信号的导向矢量进行变换；最后，通过自适应空域滤波算法设计求解DMA的方向图状态向量，在天线射频前端实现了空域滤波小信号匹配接收。仿真结果表明，经过阻塞矩阵预处理后的DMA比传统天线具有更好的空域波束赋形能力。所提方案能够有效对抗主瓣存在强干扰的情况，降低主瓣失真，恢复小信号主瓣峰值偏移的导向矢量，进一步提高期望小信号的接收增益，证明所提算法的有效性以及优于传统天线阵列波束形成方法的优势。     

滚动轴承早期故障诊断的时域新方法

信号的时域平均方法适合于滚动轴承的故障诊断,但在实际应用中它要求精确地确定感兴趣周期分量的周期,否则效果不佳．一种新的信号时域平均分析方法——梳状滤波矩阵法,以类似扫描的方式,通过绘制二维灰度图,能精确计算出信号中感兴趣周期分量的周期,为信号时域平均方法的工程应用铺平了道路．首先介绍一般梳状滤波器理论及梳状滤波矩阵法的具体实现方法,最后给出了仿真和实验实例．     

MIMO雷达空时编码和接收权联合稳健设计

针对基于多进多出雷达的空时自适应处理方法的检测性能对目标参数估计误差敏感从而导致系统检测概率稳健性较差的问题,提出一种改善多进多出空时自适应检测性能的发射波形和接收权联合稳健设计方法。首先推导了多进多出空时自适应输出信干噪比的数学表达,而后构建了目标空时频导向矢量估计误差模型。在此误差模型、波形恒模特性、旁瓣以及杂波抑制等约束下,基于最大化最差情况下输出信干噪比准则,提出了改善多进多出空时自适应检测性能的发射波形相关阵和接收权联合稳健优化问题。为求解所得复杂非线性优化问题,提出一种迭代方法,其中每一步都可转化为半定规划问题,因而可获得高效求解。仿真结果表明,与现存主要的稳健方法、非稳健方法及不相关波形相比,所提方法可显著改善多进多出空时自适应检测概率的稳健性能。     

MIMO radar waveform design method via low sidelobe beampattern modification

In the design of the multiple-input multiple-output(MIMO) radar waveform, decreasing transmit beampattern sidelobes could reduce the energy of clutters and false targets from sidelobes and increase the received signal to noise ratio (SNR) so as to improve the angle estimation property. Motivated by this idea, a transmit waveform design method based on low sidelobe beampattern modification is proposed for MIMO radar. First, the transmit waveform cross-correlation matrix can be obtained by the semidefinite relaxation (SDR) technique. Then the essence of our method is to establish an optimization modification model to reduce the beampattern sidelobe by changing the non-diagonal elements of the waveform cross-correlation matrix. Finally, the corresponding transmit beamforming weight matrix is obtained by this modified matrix, and the ESPRIT algorithm is used for the direction of arrival (DOA) estimation. Meanwhile, the feasibility of our method is demonstrated. Simulation results show the superiorities of our method in sidelobe suppression, DOA estimation accuracy and angle resolution.     

Wideband interference suppression based on space-time filter

Based upon the diagonal loading technique and the structure of the space-time adaptive processors,a novel anti-jamming method of satellite navigation is proposed. According to matrix inverse theorem,the range of the diagonal loading values for space-time adaptive wideband signal processing structure is deduced,and the optimum equation of diagonal loading beam forming algorithm of space-time structure is obtained. Then,by the analysis of two-dimensional oriented vector in direction of the perturbation interference,the wideband interference covariance matrix obtained in the weights training period is modified. Finally,the optimum weight of multi-linear constrained space-time adaptive beam-forming alogrithm is derived for anti-interference filter processing. The new method effectively widens the null steering beams when discrepancy happens. The computer simulation results prove the robustness of the proposed method.     

用混沌序列降低MIMO雷达波形自相关旁瓣和互相关

基于混沌序列的良好相关性和随机性,提出了一种使用混沌序列降低多输入多输出雷达波形自相关旁瓣和互相关的方法.通过不同初值迭代得到混沌序列,然后经过相应的量化和四相编码得到混沌波形.由于不同混沌波形的自相关旁瓣不相关,同时,不同混沌波形的互相关也不相关,因此通过多脉冲压缩积累能够有效地降低自相关旁瓣和互相关在多输入多输出雷达中的影响.输出结果具有较低的旁瓣峰值,从而提高了检测性能。     

Robust adaptive beamforming with the two level nested array

For the beamforming problem in the two level nested array under the condition of signal model mismatch, this paper proposes a robust adaptive beamforming algorithm based on efficient interference-plus-noise covariance matrix reconstruction and semi-definite programming(SDP). Firstly, by using the diagonal growth-curve(DGC) model of the received signal and the search-free ESPRIT method, we reconstruct the interference-plus-noise covariance matrix of the virtual array precisely; then, the interference-plus-noise covariance matrix and a little prior information are applied to construct the optimization problem in robust adaptive beamforming, which can effectively decrease the performance degradation of the traditional MVDR filter in nonideal signal circumstances; finally, the optimization problem can be approximately expressed as an SDP problem by using the SDP relaxation method, and we can resort to the convex optimization software to solve it. Simulation results demonstrate that the proposed method achieves a higher output SINR under different input SNRs or sampling snapshots circumstances as compared to traditional methods.     

降维STAP中稀疏恢复的角度多普勒通道选择方法

在机载雷达信号处理中,高强度的地杂波严重影响信号检测性能,而空时自适应处理(STAP)是一种有效抑制杂波的技术。实际处理中,由于杂波的非均匀性,空时自适应处理往往面临着可用有效样本数较少的问题,同时机载雷达处理的信号维度极为庞大。为了解决这些问题,提出了一种基于稀疏恢复的降维STAP通道选择方法。利用少量样本通过稀疏恢复的方法估计出全维度的杂波协方差矩阵(CCM),并以此为依据评估各个通道的重要性,选择合适的通道构造出降维后的杂波协方差矩阵并进行STAP处理,解决了有效样本较少的问题,同时保证了降维算法的性能。数值仿真验证了算法有效且比典型的稀疏STAP算法效果更好,讨论了在不同样本数下,输出性能与通道数的关系,结论具有工程应用意义。     

双基地MIMO雷达波形解相关算法

The auto-correlation and cross-correlation properties of transmit waveforms have great effects on the performance of MIMO radar systems. However, it is difficult to design waveforms that have ideal auto-correlation properties as well as cross-correlation ones. In this paper, an MMSE based waveform de-correlation algorithm is proposed to cancel the effects of the auto-correlation and cross-correlation of transmit waveforms in the receiver. The received signal model of bistatic MIMO radars is first derived. Then, the de-correlation filters are derived by using the MMSE method to reduce the influences of colored noise enhancement. Finally, the polynomial expansion method is used to simplify the computational complexity of the proposed de-correlation filters. The performance of the proposed method is verified by applying it to bistatic MIMO radar multi-target localization. Simulation results demonstrate the effectiveness of the proposed algorithm.     

Waveform Design for MIMO Radar with One-Bit DACs via Block-Sparse Semidefinite Relaxation

Multiple-input multiple-output (MIMO) systems which deploy one-bit DACs are at-tractive in many fields, such as wireless communications and radar. In this paper, the problem of transmit waveform design in MIMO radar system with one-bit DACs is investigated. By appropri-ately designing the transmitted QPSK signal waveforms, the majority of radiated energy can be fo-cused into the mainlobe region(s) by minimizing the integrated sidelobe to mainlobe ratio (ISMR) of beampattern, such that the intensity of backscattered signals from targets can be enhanced. However, the resulting optimization problem which consists of constrained fractional quadratic problem (CFQP) is noconvex. To tackle this problem, a block-sparse semidefinite relaxation meth-od is first utilized to reformulate the CFQP into a reduced convex semidefinite programming (SDP). Further, a customized interior point algorithm (IPA) is developed to solve the small-scale SDP. Finally, the desirable one-bit transmit waveform sequence can be properly synthesized by us-ing Gaussian randomization method. Numerical simulation results demonstrate that the proposed method offer better performance than the state-of-the-art algorithms.     

阵列估计误差和扰动误差引起方向图畸变的校正

针对由于取样协方差矩阵估计误差和导向矢量扰动误差的存在,使波束形成器产生高的旁瓣和畸变的主波束,提出了用代价函数校正导向矢量扰动误差引起的方向图畸变。当两种误差同时存在且为非白色高斯扰动时,可用联合处理法来校正方向图畸变。计算机仿真结果表明,这种校正方法是有效的。