基于稀疏随机阵列配置的CS-MIMO雷达感知矩阵构造

压缩感知(CS)理论中的感知矩阵在观测数据获取和信号重建过程中起关键性作用。目前,大部分研究通过引入高斯随机矩阵作为测量矩阵实现压缩观测,这类测量矩阵对硬件要求很高,工程实现困难。提出了一种基于稀疏随机阵列配置的压缩感知-多输入多输出(CS-MIMO)雷达中的感知矩阵构造方法,当MIMO雷达阵元配置为满足某种概率分布的稀疏随机阵列时,发射与接收导引矢量的Kronecker积能够起到压缩测量的作用。从理论上分析了所构造的感知矩阵的归一化互相关系数、Gram矩阵以及阵列方向图之间的内在联系,并证明了当随机阵元位置满足均匀分布时所构造的感知矩阵满足压缩感知重构条件。在这种稀疏随机阵列配置方式下,既可以避免额外引入随机测量矩阵,又能减少所需的阵元个数,从而大大降低CS-MIMO雷达系统复杂度。仿真实验表明,该方法具有较低的感知矩阵归一化互相关系数,与满阵CS-MIMO雷达相比能够在减少阵元个数的同时获得良好的重构性能,且使重构所需运算量大大降低。     

一种步进频率信号认知雷达波形优化设计方法

认知雷达常用于完成探测、跟踪、成像及识别等多重任务,为提高其综合性能,需兼顾多方面因素研究其波形优化设计问题。基于此,提出一种基于压缩感知（CS）RIPless准则的步进频率信号认知雷达波形优化设计方法。首先,建立了目标回波信号稀疏模型,分析了其与发射信号模糊函数之间的关系。其次,根据模型中观测矩阵的构造,基于RIPless准则,将波形设计问题转化为概率分布的互相干参数及其协方差矩阵的条件数的优化问题,从而通过自适应寻优算法,获得优化的步进频率信号脉冲重复时间间隔序列和子脉冲频率序列。相较于传统方法,所提方法在信号发射与接收之间形成了信息实时反馈和信号优化重构的闭环,在高概率准确重构目标径向一维距离像的同时,也实现了发射信号模糊函数的优化。最后,仿真计算验证了所提方法的有效性。     

激光探测“猫眼”效应目标识别算法

提出了一种基于压缩感知理论的＂猫眼＂效应目标识别算法,应用随机采样矩阵将原始二维图像线性投影为一维测量向量,通过对一维测量向量的处理提取出＂猫眼＂效应目标信息,进而通过压缩感知理论的恢复算法重建仅包含＂猫眼＂目标的图像。对应于此算法亦提出了一种相应的激光主动成像探测系统,以获取主被动图像序列。应用此算法,将传统的基于原...     

基于RIPless理论的层析SAR成像航迹分布优化方法

层析合成孔径雷达成像(TomoSAR)是通过同一观测区域不同入射角的多幅二维合成孔径雷达(SAR)图像在高程向进行孔径合成,从而实现三维成像。近年来,压缩感知(CS)被用于高程向稀疏场景的重建,高程向重建质量取决于观测矩阵的性质,而航迹分布是影响观测矩阵重构性能的重要因素。相比于度量观测矩阵重构性能的其他约束条件,RIPless理论具有有效、直观和计算简单等优点。提出了一种基于RIPless理论的压缩感知层析SAR成像航迹分布优化准则,从而在航迹数目一定的情况下,获取最优分布以实现高程向优化重建。最后,通过仿真和实验验证了所提优化准则的有效性。     

基于马尔科夫链的单站SAR海面场景宽幅高分成像算法

针对单站合成孔径雷达(SAR)实现海面场景高分辨率宽测绘带(HRWS)成像问题,结合海面目标相对整个场景的稀疏特性,提出了一种基于马尔科夫链的单站SAR宽幅高分成像算法。算法将宽幅的海面场景分为不同子测绘带,首先发射少量脉冲对各子测绘带进行距离向成像,利用距离向成像结果获取场景内感兴趣目标的数量信息。然后计算雷达波束指向的马尔科夫状态转移概率,并按此概率控制雷达对不同测绘带进行扫描。获得不同测绘带的稀疏子孔径后进行压缩感知成像。提出的算法可以在相同合成孔径时间内实现多个测绘带的宽幅高分成像,最后的仿真实验验证了所提算法的有效性。     

基于实波束扫描的相控阵雷达前视成像

实现机载或弹载雷达正前方目标区域高分辨力成像对提高着陆安全性或制导精度有着重要的意义,基于相控阵雷达(PAR)工作原理,建立前视扫描过程中的回波信号模型,对目前广泛研究的解卷积前视成像方法进行了深入分析,指出其未能有效提高方位分辨力的原因,并在此基础上提出了一种基于压缩感知理论的扫描雷达前视成像方法。该方法通过对大时宽带宽积信号的脉冲压缩获得径向高分辨,并基于场景中的强散射中心分布具有稀疏性(可压缩)这一事实,利用压缩感知最优化方法获得高的方位分辨力,仿真结果证明了所提方法的有效性,分析了基于压缩感知前视成像方法的性能。该方法同样适用于机械扫描雷达的前视成像。     

高光谱图像压缩感知投影与复合正则重构

压缩感知理论提供了一种新的数据获取和压缩思路,能有效地把计算负担从编码端转移到解码端。高光谱数据具备数据稀疏性、空间相关性和谱间相关性,结合这3类先验知识,提出了一种基于复合正则化的高光谱图像压缩感知投影与重构方法。该方法的编码端只需要一个简单的投影操作;在重构算法实现中,基于变量分裂的思想,把具备多个正则项的优化问题转化成多个简单的优化问题,并用迭代方式求解。实验结果表明,本文算法在高光谱图像重构上能获得更高的峰值信噪比和更好的重构效果。该方法具备极低的编码复杂度,适用于资源受限的机载和星载高光谱成像平台。     

宽带认知雷达低峰均比波形快速设计算法

发射波形设计是宽带认知雷达系统的关键技术。为了提高宽带认知雷达系统对距离扩展目标的检测性能,建立了目标检测模型,分析了系统的检测性能,在此基础之上研究了基于最大输出信干噪比(SINR)的低峰均比(PAR)波形设计算法。通过将原波形优化问题等效为接收权值与低峰均比波形的联合优化问题,同时利用循环优化的思想,提出了一种低峰均比波形快速设计算法。相比于现有的梯度法以及凸优化算法,该算法所设计的恒模波形信干噪比与二者相当,但算法实现难度明显变小,计算复杂度明显降低。仿真结果证实了算法的有效性。     

基于复近似消息传递的前视雷达成像分辨率增强算法

当机载/弹载雷达工作在前视状态时,由于成像场景内不同角度处目标的多普勒差异很小,很难得到 高的角度分辨率。针对海面舰船目标的前视成像应用,利用成像区域具有明显稀疏性的特点,提出一种基于复 近似消息传递压缩感知处理的前视成像角度分辨率增强算法,建立前视成像的线性观测信号模型,给出复近似 消息传递的迭代计算过程,以及多通道雷达前视成像的处理流程。通过仿真数据和 X 波段雷达实测数据的处 理结果验证了该方法的有效性。     

基于压缩感知的多级风扇周向声模态重构

基于风扇单音噪声周向声模态在叶片通过频率下稀疏的特性,研究压缩感知方法在多级风扇周向主导声模态识别和幅值重构中的应用。开展多级风扇试验器的声场测量试验,利用压缩感知方法对管道周向声模态进行准确识别与分解。建立声模态重构的压缩感知模型,实现少数传声器对主导声模态的阶数识别和幅值精确重构,同时研究传声器数量和布局策略对重构精度的影响。试验结果表明:对于确定声场,当压缩感知常量C大于3.6时,随机布局的传声器有90%以上的概率可以以较高精度重构主导声模态幅值;建立压缩感知模型观测矩阵时应避免传声器的均匀和近似均匀布局,均匀布局的感知模型难以精准重构声模态。      

Adapitive waveform design for distributed OFDM MIMO radar system in multi-target scenario

In order to improve detection and estimation performance of distributed Orthogonal-Frequency-Division Multiplexing (OFDM) Multiple-Input Multiple-Output (MIMO) radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design (AWD) based on a constrained Multi-Objective Optimization (MOO). The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.     

Sensitivity of MIMO STAP Radar with Waveform Diversity

Space-time adaptive processing (STAP) is an effective method adopted in airborne radar to suppress ground clutter. Multiple-input multiple-output (MIMO) radar is a new radar concept and has superiority over conventional radars. Recent proposals have been applying STAP in MIMO configuration to the improvement of the performance of conventional radars. As waveforms transmitted by MIMO radar can be correlated or uncorrelated with each other, this article develops a unified signal model incorporating waveforms for STAP in MIMO radar with waveform diversity. Through this framework, STAP performances are expressed as functions of the waveform covariance matrix (WCM). Then, effects of waveforms can be investigated. The sensitivity, i.e., the maximum range detectable, is shown to be proportional to the maximum eigenvalue of WCM. Both theoretical studies and numerical simulation examples illustrate the waveform effects on the sensitivity of MIMO STAP radar, based on which we can make better trade-off between waveforms to achieve optimal system performance.     

基于OTR和SHT的射频隐身雷达信号设计

为了提高雷达的射频(RF)隐身性能,结合最优匹配照射-接收机(OTR)理论与序贯假设检验(SHT)方法,提出了一种新的射频隐身雷达信号设计方法。通过发射信号了解外界环境信息,然后反馈这些信息给雷达系统,系统根据这些信息自适应设计雷达发射信号,形成一个闭环系统。以雷达目标识别为具体应用,实验仿真表明,设计的雷达信号自适应变化,减小了信号间的相关性,并且减少了照射次数,降低了辐射功率,从而实现了雷达系统的射频隐身性能。     

Radar Waveform Selection-A Simplified Approach

Radar measurement and resolution performance, as well as target detection in clutter, depend largely on the transmitted waveform. This explains the sizable effort that has gone into studies of radar waveforms, including attempts at the synthesis of optimum waveforms. This paper shows that, despite the unlimited variety of radar signals, waveform selection is a straightforward process. There are only four classes of waveforms, each with distinct resolution properties. When the target environment is analyzed for a particular application, it is rather evident which of these classes will fit the situation best. Choice of the specific waveform within the selected class then is merely a matter of practical implementation. Although the facts used in developing the unified theory of this paper are not new, it is demonstrated that these facts can be combined into an extremely simple theory of waveform design. Much of today's work is guided by past approaches to a particular problem, and when a design is completed there may be a question as to how close to the optimum it is. The theory presented here permits a systematic approach to waveform selection, with the important benefit that the designer knows exactly where and how much he may have deviated from the best design, and why this was done.     

A novel target detection approach based on adaptive radar waveform design

To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.     

Experimental study on pulse radar target probing in RFS based on interrupted transmitting and receiving

Radar target probing and measurement are challenging tasks for Radio Frequency Simulation (RFS) with pulse radar signal. Due to the long-time duration of pulse radar signal and the limited space of anechoic chamber, the reflected signal returns before pulse radar signal is fully transmitted in RFS. As a consequence, the transmitted and reflected signals are coupled at the receiver. To handle this problem, the Interrupted Transmitting and Receiving (ITR) experiment system is constructed in this paper by dividing the pulse radar signal into sub-pulses. The target echo can be obtained by transmitting and receiving the sub-pulses intermittently. Furthermore, the principles of ITR are discussed and the target probing experiments are performed with the ITR system. It is demonstrated that the ITR system can overcome the coupling between the reflected and transmitted signals. Based on the target probing results, the performance of pulse radar target probing and measurement can be verified in RFS with the ITR system.