MIMO雷达发射方向图匹配和波形优化方法

为了匹配MIMO雷达系统给定的发射方向图,采用半正定规划(SDP)来优化发射信号的协方差矩阵．基于该协方差矩阵,利用循环算法(CA)和极小极大法,通过优化波形相位设计出了具有低空域和时域副瓣的恒模发射信号．此外,又提出了用凸规划设计空域失配滤波器和时域失配滤波器的方法,进一步降低了空域和时域副瓣．     

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。     

Transmit beampattern synthesis and waveform design for 2-D wideband MIMO radar

For matching the desired transmit beampattern of the two dimensional(2-D) wideband MIMO radar system, a new transmit beampattern synthesis and waveform design algorithm is proposed based on the frquency invariant beamforming. In this algorithm, to eliminate any dependency on frequency of the emiting waveform, the 2-D fourier relationship between uniform rectangular array(URA) transmit beampattern and spectrum of emiting waveform is used. Then the cost function of waveform matching frequency response is established, which imposes a constraint on constant modulus. Finally, the alternating matrix fitting method is used to design unimodular sequences. The proposed method effectively mitigates frequency dispersion of the 2-D wideband MIMO radar transmit beampattern. Numerical simulations have proved the validity of this 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.     

MIMO雷达波达方向估计的性能分析

针对单基地多输入多输出雷达波达方向估计精度问题,推导了单目标情况下波达方向估计的克拉美罗界．结果表明波达方向估计精度取决于收发阵列的导向矢量以及发射信号的相关矩阵,当发射阵元间距为半波长时,多输入多输出雷达波达方向估计的克拉美罗界在大部分角度范围内优于相控阵雷达．多输入多输出雷达还能够通过增大发射阵元间距来得到更小的克拉美罗界,从而获得远优于相控阵雷达的波达方向估计性能．     

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．     

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.     

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: An Overview

Waveform or code design is an important topic in many applications, which has continuously attracted attention during the past several decades. The development of waveform design has been significantly advanced since the emergence of multiple-input multiple-output(MIMO) technique. Compared to the single-waveform design for conventional radars, the multi-waveform design enables extra degrees of freedom(DOFs) for modern radars, which therefore triggers a series of relevant studies on MIMO radar. In this paper, we provide an overview on the main techniques of MIMO radar waveform designs developed in recent years, wherein the state-of-the-art methods are reviewed in terms of different designing criteria, including the minimization of auto-and cross-correlation levels(or equivalently, the integrated sidelobe level), the information theoretic, ambiguity function shaping, and signal-to-interference-plus-noise ratio maximization-based criteria, etc.Moreover, we give detailed comments on the main issues of different waveform designs, and also provide the possibly emerging directions toward the research on MIMO radar waveform design and potential challenges.     

双基地MIMO雷达相干源角度估计方法

针对双基地多输入多输出(MIMO)雷达的相干源角度估计问题,分别在空间高斯白噪声和空间高斯色噪声背景下提出基于降维波达方向(DOA)矩阵的角度估计方法.首先对MIMO雷达相干目标的回波进行解相干处理;然后分别在两种噪声背景下构造DOA矩阵,并利用其与信号子空间的关系得到降维DOA矩阵,有效降低了原DOA矩阵法的运算量.之后利用降维DOA矩阵的特征参数与待估参数间的特定关系实现目标离开方向(DOD)和波达方向(DOA)的联合估计.该方法无需二维谱峰搜索,在两种不同噪声背景下均能有效估计相干源的二维角度并实现自动配对,且在接收阵列为非等距线阵的条件下仍具有适用性.仿真实验验证了该方法的有效性.     

MIMO radar waveform design in the presence of clutter and colored noise

The existing MIMO radar waveform design methods only deal with the optimization of radar waveform with the presence of clutter or colored noise, and unfortunately can not get the optimal waveform with the scenario when the clutter and colored noise coexist, which is more realistic in practical applications. To address this problem, a novel MIMO radar waveform design method based on mutual information in the presence of clutter and colored noise is proposed. The proposed scheme considers the influence of the target's response, clutter and colored noise on the optimization of the radar waveform. The mathematical expression for the transmit waveform matrix is achieved by theoretical derivation. What is more important, an optimal pairing of the eigenvectors of the target, clutter and colored noise is given and the power allocation for each antenna is optimized by the water-filling method. Simulation results show that when the total transmit power is 10dB, the proposed method's MI is 8bit and 4bit more than that of the general water-filling method and the method which only considers the pairing of the target's response and noise, respectively.     

MIMO雷达中的DFCW设计及性能分析

发射信号的正交性好坏是多输入多输出(MIMO)雷达实现的关键,正交离散频率编码波形(DFCW)是MIMO雷达可以利用的正交信号。该文首先分析了DFCW的互模糊函数,在此基础上,对自相关峰值旁瓣及互相关峰值旁瓣电平进行了分析,提出了采用遗传算法对其进行优化,得到了具有更低互相关峰的DFCW。然后将优化得到的DFCW应用于MIMO雷达系统进行仿真分析。通过对信号互相关仿真及对目标回波信号匹配滤波仿真对理论分析进行了验证,证明了理论分析的正确。     

利用压缩感知的分布式高频地波雷达DOA估计

In order to solve the problems of “large position, difficulty with location chosen, low angle resolution, and poor flexibility”, and to improve the performance of DOA estimation, a new design of the distributed high frequency surface wave radar is proposed, based on the technology of distributed antennas array and the MIMO radar system. With the new design, we propose a new DOA estimation method using compressed sensing, this method reduces the complexity of data processing and solves the angle ambiguity due to the distributed array. Discrete stochastic and semi-QR factorization is also used for improving the performance of the new DOA estimation. Theoretical analysis and simulation results show the validity of the proposed method.     

水下多传感器基阵波束域高分辨方位估计方法及实验研究

针对水声设备的实际应用，给出了基于实测基阵阵列流形的波束域高分辨方位估计的MUSIC方法。在预形成多波束时，该方法采用适用于任意阵形的自适应波束优化技术，针对水下实际阵列设计超低旁瓣波束以抑制水面上分布的强干扰。为了减小实际阵列模型和理想阵列模型失配所带来的不利影响，在多波束设计时，利用实测阵列流形代替理想阵列流形进行设计，消声水池实验结果验证了该方法可以有效地降低系统中由于阵列模型失配所造成的波束域MUSIC方位估计方法的性能损失。     

采用OFDM-LFM的MIMO雷达高速目标波形设计

单基地多输入多输出雷达由于其宽发射波束的特性而能有效解决目标高速运动跨越发射波束带来的能量损失问题;但是现有波形对速度容忍性较差,高速目标回波匹配滤波能量损失较大．因此,有必要研究适用于高速目标背景下的多输入多输出雷达波形． 文中提出了一种基于正交频分复用线性调频信号的多输入多输出波形． 该波形不同发射通道分时复用一组不同频段的线性调频信号,从而得到带宽相同的可分离多路多输入多输出雷达波形． 仿真结果表明,文中设计的多输入多输出雷达波形能有效降低高速目标回波匹配滤波的能量损失,适用于高速目标背景．     

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.     

DOA estimation method for two-dimensional hybrid MIMO phased-array radar

Aiming at the direction of arrival(DOA) estimation problem of the Two-Dimensional Hybrid MIMO(Multiple-Input Multiple-Output) Phased-array Radar, an effective solution is proposed based on transmit weight optimization and Unitary ESPRIT of the virtual array. First, we build the receiving signal model. Then a transmit weight vector is designed by convex optimization to simultaneously construct the receiving subarray rotational invariance and control the side lobe of the pattern of Two-Dimensional Hybrid MIMO Phased-array Radar to improve the DOA estimation accuracy. Finally, the Unitary ESPRIT is exploited to estimate the azimuth and elevation of Two-Dimensional Hybrid MIMO Phased-array Radar to decrease the calculation load. Numerical simulations show that our approach can realize DOA estimation of the Two-Dimensional Hybrid MIMO Phased-array Radar.     

联合优化方向图合成与频谱兼容的MIMO雷达波形设计

多发射-多接收雷达发射方向图合成是当前波形设计和合成问题的热点,其目的在于实现将发射能量聚焦在感兴趣的空域方向上。而在复杂的电磁环境中,还必须兼顾考虑在拥堵频段上的频谱兼容性和灵活性,避免影响邻近频段通信系统传输性能。该文提出算法设计MIMO雷达发射波形向目标空域聚焦能量的同时,避开拥堵频段的频率范围。即针对发射波形在空域、频域两类要求而联合优化。联合优化问题被建模为加权均方误差代价函数,优化问题是非凸非平滑的。在算法的每一步迭代优化中,首先更新当前步骤的匹配系数,再对均方误差代价函数进行放缩,构造替代函数;进而优化替代函数,得到较小代价函数值对应的波形。该文提出的迭代优化算法,具有接近理想的方向图合成性能与频谱塑形性能,且运算量小。仿真和数值结果证明了该方法的有效性。     

LFMCW车载雷达解速度模糊测角新方法

LFMCW车载雷达采用MIMO虚拟孔径方法提高角度估计性能,通常将MIMO雷达虚拟孔径角度估计和解速度模糊分成两帧信号处理,这样会降低雷达数据率。该文提出一种解速度模糊测角新方法,采用TDM方式发射不同时宽、带宽相同的锯齿波信号。在一帧信号内先解速度模糊,再进行相位补偿,最后进行MIMO雷达虚拟孔径角度估计。通过仿真和理论分析,该方法能进行高精度角度估计,减少了信号处理时间,提高了雷达数据率。     

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．