基于stolt插值的微波近场成像方法研究

提出了一种毫米波成像方法,并对该成像算法做了详细的推导。同时,对该算法进行了计算机仿真,并通过改变仿真参数着重分析了天线扫描范围、目标之间的间隔以及天线与目标之间的距离对成像空间分辨率的影响。仿真结果表明：利用该算法不但可以准确重建目标的二维像,而且具有良好的分辨率。     

自旋目标高效参数化超分辨成像研究北大核心CSCD

给出一种自旋目标高效参数化超分辨成像方法,该方法不仅能对高速自旋目标超高分辨二维成像,而且该算法得到的二维图像分辨率高、旁瓣低,运算量仅为原来的1/4。首先,通过对宽带回波去冗余信息处理来大大减少运算量;其次,基于Burg谱估计算法对每个去冗余的宽带回波进行频谱外推,从而提高分辨能力;再次,对自旋目标运动参数进行估计;最后,利用基于反投影成像技术对高速旋转目标稳健二维成像,理论仿真和实测数据都验证了其成像效果和运算效率。     

基于CLEAN 算法的毫米波全息二维像研究

针对近程毫米波全息成像算法过程中的点函数扩散以及旁瓣过宽问题,提出了基于加窗的二维自适应CLEAN 算法。该算法提取所得“脏图冶的最亮像素点,减去该像素点以及周围小目标的部分能量,之后在清洁图像上重建目标处的精准信息,有效抑制点函数扩散与旁瓣展宽。区别于传统CLEAN 算法,二维自适应CLEAN 算法根据当前图像的能量均值实时更新减去因子,具有很强的自适应性,此外,依据图像最暗目标像素点动态获取全局噪声门限,提高了目标提取速度。通过对多个单目标进行一维与二维方位像的仿真实验,证明了算法的有效性。     

基于弹跳射线法的海面舰船目标三维散射中心快速建模方法

海面舰船目标3维散射中心的快速建模对雷达目标信号快速仿真、特征提取与分类识别等应用具有重要意义。该文结合目标-海面耦合散射的“4路径”模型、随机海面散射修正Fresnel反射系数模型,以及基于射线管积分的快速3维成像等模型与方法,提出一种舰船-海面复合的快速3维成像方法,并通过CLEAN算法建立一种3维散射中心快速建模算法。该算法由于实现了单频、单视角条件下的目标3维成像,并且采用简化的海面模型避免了大量海面面元的构建,因而大大提高了3维散射中心建模的计算效率,从而满足实际工程应用的需求。典型海面舰船目标仿真实验结果表明,与传统基于FFT的3维成像算法相比,在典型计算条件下该算法的计算效率可提高4个数量级。不同海情下,3维散射中心重建的与直接仿真计算的1维距离像历程图和2维像的对比结果,也验证了算法的计算精度。      

基于二维小波变换的激光成像雷达目标识别算法

提出了基于二维小波变换的激光成像雷达目标识别算法,首先对激光成像雷达目标的距离像进行二维小波变换;然后从近似分量和细节分量中提取奇异值特征,利用遗传算法对支持向量机参数进行智能优化;最后应用支持向量机对三种地面目标进行识别.仿真实验表明,该方法与直接应用距离像奇异值特征进行识别的方法相比,在高载噪比20dB时的平均识别...     

基于RWT的旋转微动目标二维ISAR成像算法

本文针对旋转微动目标的二维ISAR成像问题,首先,分析了目标旋转微动及刚体部件在距离-慢时间域的回波特性;其次,提出了基于解正弦调频RWT的旋转微动部件成像算法,同时,提取旋转微动散射点的位置参数并滤除其回波,对剩余回波采用基于RWT方法进行刚体回波重建,并利用传统RD算法获得刚体ISAR像;最后,仿真结果证明了本文算...     

基于散射中心模型的雷达目标成像研究

雷达目标数据是验证和评估各种算法的基础,数据仿真由于不受条件和环境制约,是获取数据的重要途径,开展数据仿真研究具有重要的现实意义。研究了一种基于多散射中心模型的目标成像方法,仿真获得了坦克目标的一维距离像和二维SAR像,针对传统成像方法分辨率低的问题,将基于最小二乘—旋转不变技术的参数估计技术应用于雷达目标一、二维成像中,大大改善了雷达图像的分辨率和成像质量。     

一种基于幅度和相位迭代重建的四维合成孔径雷达成像方法

4维合成孔径雷达获取的观测数据在基线-时间平面非均匀分布。若采用传统成像方法来获取目标散射体的高度-速率维像,则因强副瓣存在,成像效果不理想。当信号具有稀疏性时,压缩感知技术能够利用少量的信号投影值就可实现信号的准确或近似重构。然而标准的压缩感知成像方法是针对实数据进行处理,4维合成孔径雷达成像处理的数据为复数据。因此该文提出了一种基于幅度和相位迭代重建的4维合成孔径雷达成像方法。将4维合成孔径雷达高度-速率成像问题转化为目标复散射系数的幅度和相位联合重建问题,通过在成像过程中引入相位信息来改善成像质量。仿真结果验证了该算法的有效性。      

穿墙雷达平面多层媒质二维衍射层析成像算法

为了解决多层介质墙体后隐蔽目标探测的问题,提出了一种穿墙雷达平面多层媒质二维衍射层析成 像算法。所提成像算法基于一阶Born 近似理论,通过平面多层媒质的格林函数谱域展开式和快速傅里叶变换技术, 实现对多层墙体后隐蔽目标的快速准确成像重建。基于时域有限差分法产生的仿真数据处理结果验证了此成像算 法的有效性和准确性。     

一种高分辨力雷达扩展目标模拟系统设计与实现

针对高分辨力雷达扩展目标回波模拟，文中设计并实现了一种高分辨力雷达扩展目标模拟系统。建立了一维距离像目标、二维面目标、三维体目标的目标回波模型，结合宽带射频接收机技术、大瞬时带宽基带回波信号产生技术、目标RCS(Radar Cross Section)数据获取与调制技术以及宽带捷变频率合成器等关键技术完成了高分辨力雷达扩展目标模拟系统的设计与实现。使用该系统对某典型战斗机目标进行了射频仿真和二维成像处理，并将射频仿真和二维成像处理结果与使用RadBase仿真软件对该典型战斗机目标的仿真结果进行对比，验证了该系统的有效性。验证结果表明，该系统的射频仿真二维成像处理结果和RadBase仿真软件的仿真结果基本一致。     

High-Resolution 3-D Imaging Algorithm With an Envelope of Modified Spheres for UWB Through-the-Wall Radars

Through-the-wall imaging techniques with ultrawideband (UWB) radars are promising candidates for non-destructive testing and reliable human detection, especially in disaster areas, where victims are buried under collapsed walls. These applications require high-resolution target imaging to identify the object shape, such as a human body. We have already proposed a high-quality 3-dimensional (3-D) imaging algorithm in the form of Envelope, that is aimed at near field sensing for non-contact measurement or target identification for robots. Envelope achieves real-time accurate 3-D imaging with group mapping from multiple observed ranges to target points, and offers a reliable image even in noisy situations. However, this method does not maintain its quality for through-the-wall imaging because an observed range shift due to wall penetration causes a serious distortion in the image. This paper presents a high-resolution 3-D imaging algorithm by modifying the original Envelope, and which gives a more accurate object shape behind a wall. Furthermore, to enhance the resolution of the estimated images, this method is combined with a direct waveform compensation method, known as spectrum offset correction. Numerical simulations and an experiment verify that our proposed method achieves high-resolution 3-D imaging for through-the-wall radar applications.      

A cone-beam reconstruction algorithm for circle-plus-arc data-acquisition geometry

In cone-beam computerized tomography (CT), projections acquired with the focal spot constrained on a planar orbit cannot provide a complete set of data to reconstruct the object function exactly. There are severe distortions in the reconstructed noncentral transverse planes when the cone angle is large. In this work, a new method is proposed which can obtain a complete set of data by acquiring cone-beam projections along a circle-plus-arc orbit. A reconstruction algorithm using this circle-plus-arc orbit is developed, based on the Radon transform and Grangeat's formula. This algorithm first transforms the cone-beam projection data of an object to the first derivative of the three-dimensional (3-D) Radon transform, using Grangeat's formula, and then reconstructs the object using the inverse Radon transform. In order to reduce interpolation errors, new rebinning equations have been derived accurately, which allows one-dimensional (1-D) interpolation to be used in the rebinning process instead of 3-D interpolation. A noise-free Defrise phantom and a Poisson noise-added Shepp-Logan phantom were simulated and reconstructed for algorithm validation. The results from the computer simulation indicate that the new cone-beam data-acquisition scheme can provide a complete set of projection data and the image reconstruction algorithm can achieve exact reconstruction. Potentially, the algorithm can be applied in practice for both a standard CT gantry-based volume tomographic imaging system and a C-arm-based cone-beam tomographic imaging system, with little mechanical modification required.     

互相关算法在运动目标距离选通激光三维成像中的应用

在微光成像中,距离选通成像是一种获取目标三维信息的有效手段。对于静止目标而言,可以通过对目标切片成像,获得不同选通距离的目标图像,进而通过二值化算法或质心算法获得目标的三维图像。而对于运动目标而言,在切片成像的同时,目标的空间位置会发生变化,因此需要对不同选通距离的目标图像进行配准,而后才能获得目标的三维图像。搭建了基于像增强电荷耦合器件(ICCD)的距离选通实验系统,提出了一种基于像质评价的互信息配准算法配准激光图像目标的空间位置,然后对配准后的激光图像通过互相关算法获得三维图像,并在保证一定的三维精度基础上,逐渐减少激光图像的像幅数,最后与二值化算法和质心算法三维重构进行了实验对比,实验结果表明,互信息配准算法能够有效配准激光图像,互相关三维成像算法精度高于二值化法和质心法,最少采用2幅图像即可获得目标的三维点云图像,大大降低了对运动目标三维成像的难度。     

一种毫米波全息成像系统方案及其仿真

提出了一种双频毫米波全息成像系统方案。该方案不仅可以准确地测定目标与成像雷达天线口径的距离,而且可以对一定距离但事先未知的目标进行全息成像。相比于需要放置在预知位置的美国太平洋西北国家实验室研究的单频和宽带毫米波全息成像系统,该方案具有更为广泛应用的潜力,不仅可以用于个人携带的藏匿武器或者违禁物品的检查,还可以作为毫米波成像雷达用于军事目的。文中根据该成像系统确定了毫米波全息成像方法,建立了相应算法,给出了成像仿真结果。该方案可对实际系统设计提供一定参考。     

A new fast method for the reconstruction of 2-D microwave images ofrotating objects

The problem of microwave imaging of rotating objects is approached from a digital signal processing point of view. Attention is focused on the reconstruction of the two-dimensional (2-D) image of an object obtained by processing complex samples of the continuous wave (CW) signal return received for different object aspect angles covering a 2pi total variation. The effects of a polar sampling of the Fourier transform (FT) of the target reflectivity function on the impulse response of the imaging system are analyzed. A criterion for the choice of the angular sampling interval in order to control the image blurring is given. Finally, a new and fast digital signal processing method for image reconstruction is proposed. This method reconstructs high resolution images of rotating targets illuminated by a CW electromagnetic signal or by a large bandwidth transmitted signal. This algorithm is suitable for processing wideband received signal of targets observed for a large variation of the viewing angle, so it is very attractive for the reconstruction of very high spatial resolution target images in SAR/ISAR systems. To show the performance of the method we finally present and discuss the results obtained by applying the proposed technique on simulated and experimental data.     

导数法峰值锐化算法提高磁感应成像图像分辨率

磁感应成像(MIT)是一种利用电磁感应原理重构生物组织电导率分布的非接触式电阻抗成像技术。该文利用亥姆霍兹线圈和20个检测线圈搭建了旋转式磁感应成像系统,利用滤波反投影算法重构图像。分别利用2阶和4阶导数法峰值锐化算法处理单目标和双目标检测线圈的测量数据,通过3个客观参数对比处理前后的重构图像结果。结果证明磁感应成像中导数法峰值锐化能够有效地增加图像质量。     

幅度和相位估计的ISAR超分辨成像方法

传统距离多普勒(Range Doppler, RD)成像方法分辨率取决于发射信号的带宽和信号在方位向积累的多普勒带宽。超分辨成像可以在给定带宽条件下,获得比RD方法更优的分辨率。给出一种基于幅度和相位估计(Amplitude and Phase Estimation, APES)的逆合成孔径雷达(Inverse Synthetic Aperture Radar, ISAR)超分辨成像方法,该方法根据回波数据构造自适应滤波器对目标散射点进行重建,仿真和实测ISAR数据成像结果验证了基于APES的ISAR超分辨成像算法的有效性。相比其他超分辨成像方法,该方法重建的散射点幅度更为精确,副瓣更低,图像对比度和图像信噪比增加,整体成像效果较佳。     

Noninvasive imaging of bioimpedance distribution by means of current reconstruction magnetic resonance electrical impedance tomography

We have developed a novel magnetic resonance electrical impedance tomography (MREIT) algorithm-current reconstruction MREIT algorithm-for noninvasive imaging of electrical impedance distribution of a biological system using only one component of magnetic flux density. The newly proposed algorithm uses the inverse of Biot-Savart Law to reconstruct the current density distribution, and then, uses a modified J-substitution algorithm to reconstruct the conductivity image. A series of computer simulations has been conducted to evaluate the performance of the proposed current reconstruction MREIT algorithm with simulation settings for breast cancer imaging applications, with consideration of measurement noise, current injection strength, size of simulated tumors, spatial resolution, and position dependency. The present simulation results are highly promising, demonstrating the high spatial resolution, high accuracy in conductivity reconstruction, and robustness against noise of the proposed algorithm for imaging electrical impedance of a biological system. The present MREIT method may have potential applications to breast cancer imaging and imaging of other organs.     

基于块稀疏贝叶斯模型的ISAR成像方法

传统ISAR稀疏成像主要针对独立散射点散射系数的重构问题,然而实际情况下目标散射点之间并不是独立存在的,而是以区域或块的形式存在,在该情形下利用常用的稀疏重构算法并不能完全地刻画块状目标的真实结构,因此该文考虑采用块稀疏重构算法进行目标散射系数重建。基于块稀疏贝叶斯模型和变分推理的重构方法(VBGS),包含了稀疏贝叶斯学习(SBL)方法中参数学习的优点,其利用分层的先验分布来表征未知信号的稀疏块状信息,因而相对于现有的恢复算法能够更好地重建块稀疏信号。该方法基于变分贝叶斯推理原理,根据观测量能自动地估计信号未知参数,而无需人工参数设置。针对稀疏块状目标,该文结合压缩感知(CS)理论将VBGS方法用于ISAR成像,仿真实验成像结果表明该方法优于传统的成像结果,适合于具有块状结构的ISAR目标成像。