水下成像的现状和发展动向

本文以下水成像在军事，海洋开发工程应用为基础，论述了水下观测和成像中采用微光电视摄像机和激光器件及其系统的技术现状和发展动向。     

Research progress in terahertz quantum cascade lasers

The terahertz(THz)quantum cascade laser(QCL)is a coherent THz source based on intersubband transitions of unipolar carriers.As semiconductor lasers,THz QCLs are solid-state,electrically pumped,tunable,and can be easily integrated.This paper reviews the state of the art for the design,operation temperature,and output power of THz QCLs.Their applications in THz communication and imaging are also discussed.     

基于去调频技术的斜视聚束SAR成像方法

针对具有方位谱混叠现象的斜视聚束式合成孔径雷达(SAR)成像问题,本文研究了一种基于去调频技术的成像方法.文中首先分析了斜视聚束SAR中的方位谱混叠现象,从理论上找出了斜视角影响方位粗聚焦的根本原因.基于分析结果,引入了回波信号非线性相位校正预处理法,彻底消除了斜视角的影响,从而得到正确的粗聚焦结果.然后基于斜视成像模型,推导了预处理回波信号的方位粗聚焦和精聚焦处理过程.在精聚焦的方位滤波处理中,针对非线性相位校正预处理导致的场景聚焦深度限制问题,提出了一种改进的非线性调频变标(NLCS)算法,实现了回波信号的高精度方位压缩.仿真实验结果证明了文中理论分析的正确性和所提方法的有效性.     

Sparse synthetic aperture radar imaging with optimized azimuthal aperture

To counter the problem of acquiring and processing huge amounts of data for synthetic aperture radar(SAR)using traditional sampling techniques,a method for sparse SAR imaging with an optimized azimuthal aperture is presented.The equivalence of an azimuthal match filter and synthetic array beamforming is shown so that optimization of the azimuthal sparse aperture can be converted to optimization of synthetic array beamforming.The azimuthal sparse aperture,which is composed of a middle aperture and symmetrical bilateral apertures,can be obtained by optimization algorithms(density weighting and simulated annealing algorithms,respectively).Furthermore,sparse imaging of spectrum analysis SAR based on the optimized sparse aperture is achieved by padding zeros at null samplings and using a non-uniform Taylor window.Compared with traditional sampling,this method has the advantages of reducing the amount of sampling and alleviating the computational burden with acceptable image quality.Unlike periodic sparse sampling,the proposed method exhibits no image ghosts.The results obtained from airborne measurements demonstrate the effectiveness and superiority of the proposed method.     

Diffusion tensor interpolation profile control using non-uniform motion on a Riemannian geodesic

Tensor interpolation is a key step in the processing algorithms of diffusion tensor imaging (DTI), such as registration and tractography. The diffusion tensor (DT) in biological tissues is assumed to be positive definite. However, the tensor interpolations in most clinical applications have used a Euclidian scheme that does not take this assumption into account. Several Rie-mannian schemes were developed to overcome this limitation. Although each of the Riemannian schemes uses different metrics, they all result in a ‘fixed’ interpolation profile that cannot adapt to a variety of diffusion patterns in biological tissues. In this paper, we propose a DT interpolation scheme to control the interpolation profile, and explore its feasibility in clinical applications. The profile controllability comes from the non-uniform motion of interpolation on the Riemannian geodesic. The interpolation experiment with medical DTI data shows that the profile control improves the interpolation quality by assessing the reconstruction errors with the determinant error, Euclidean norm, and Riemannian norm.     

虚拟红外成像器件的模拟输出电路设计

虚拟红外成像器件是能输出红外图像数据源的器件,在调试图像采集系统的硬件和软件时能替代非制冷红外焦平面阵列。虚拟成像器件的输出具有很好的线性度和精度,可作为图像采集电路的标定器件。文设计了虚拟红外成像器件的模拟输出电路,根据UL03401性能参数,设计了信号调理电路,通过在FPGA上使用ROM中查表方式校正模拟端口输出误差,在实际应用中表现了良好的精确性。     

一种新的SAR图像斜距多普勒定位模型的直接解法

斜距多普勒定位模型是实现SAR图像无控制点定位的基本模型,因此如何高效准确地获得RD方程组的解成为实现SAR图像无控制点几何定位的根本问题,也是实现SAR自动图像定位的关键。首先利用地固坐标系下目标速度为零的特性,简化RD模型并整理为一元四次方程,然后利用一元四次方程求根方法,推导出斜距多普勒定位模型的明确数学解析解,并与常用的数值迭代求解方法进行比较分析,仿真结果验证了推导的正确性。新解法具有无需设置初始值,易于编程实现,鲁棒性高的特点。     

Bayesian network based general correspondence retrieval method for depth sensing with single-shot structured light

This study reinvestigated one of the most fundamental problems in structure light depth sensing field: correspondence retrieval of features between patterns and images. We formulate the global optimum correspondence retrieval by maximizing a conditional probability of correspondence given observed features, which is depicted by a Bayesian network. Different from traditional “code-only” based correspondence retrieval methods, the proposed Bayesian network based method exploits the positional correlations of correspondences of neighboring features, namely, the correspondences of poorly detected features are estimated with the aid of the correspondences of well detected features. The method performs especially well on challenging scenes with rich depth variations, abrupt depth changes, edges, etc. Experiments show that the proposed method increase the correspondence accuracy by about 40% on challenging scenes, compared with traditional “code-only” based correspondence retrieval methods.