A fast O(N) multiresolution polygonal approximation algorithm for GPS trajectory simplification

Recent advances in geopositioning mobile phones have made it possible for users to collect a large number of GPS trajectories by recording their location information. However, these mobile phones with built-in GPS devices usually record far more data than needed, which brings about both heavy data storage and a computationally expensive burden in the rendering process for a Web browser. To address this practical problem, we present a fast polygonal approximation algorithm in 2-D space for the GPS trajectory simplification under the so-called integral square synchronous distance error criterion in a linear time complexity. The underlying algorithm is designed and implemented using a bottom-up multiresolution method, where the input of polygonal approximation in the coarser resolution is the polygonal curve achieved in the finer resolution. For each resolution (map scale), priority-queue structure is exploited in graph construction to construct the initialized approximated curve. Once the polygonal curve is initialized, two fine-tune algorithms are employed in order to achieve the desirable quality level. Experimental results validated that the proposed algorithm is fast and achieves a better approximation result than the existing competitive methods.     

基于小波的全局多源遥感图像信息融合方法

提出的图像信息融合方法用于解决传统方法在空间分辨率等方面的不足。原始图像经过小波变换，分解成子图像，再进行分块处理，高、低分辨率图像根据全局方差准则分别计算融合的权值系数，进行图像融合重建，然后，对图像采用全局法进行信息融合，实验表明，方法切实可行，能使低分辨率图像接近于高分辨率图像。     

压缩感知SAR成像中的运动补偿

由于其具有压缩采样特性,压缩感知在高分辨SAR成像技术中得到了广泛应用。然而作为一种参数化的成像方法,基于压缩感知的成像方法对位置误差非常敏感。位置误差会造成图像偏离真实位置、散焦、甚至根本不能成像。该文针对SAR压缩成像系统中存在的运动误差,分析了平台非理想运动对回波信号的调制机理和运动相位误差对信号稀疏表征的影响,提出了基于传感器测量数据进行运动补偿的压缩感知SAR成像方法,通过在稀疏矩阵中引入附加项完成空不变运动误差的补偿。该方法不仅能以少量的测量孔径和测量数据获得重建目标空间的足够信息而且能有效降低运动误差对成像质量的影响,实现高分辨成像。     

基于相干化处理的步进频率ISAR成像算法研究

在步进频率高分辨ISAR成像中,传统的参数估计方法往往不能准确地估计出运动目标的速度和加速度值,其补偿后存在的相位误差对宽带合成ISAR图像有较大的影响。因此,该文提出了一种基于相邻相关法和相位相干化的步进频率高分辨ISAR成像技术,即通过相邻相关法估计运动目标的径向运动参数,在对回波数据包络进行补偿后,利用相位相干化对各子脉冲的相位误差进行校正,再利用频带拼接技术获取目标的合成高分辨1维距离像。之后,利用RD算法实现目标的高分辨ISAR成像。该方法具有精确相位误差补偿精度和高运算效率的优点。仿真和实测数据验证了该方法的有效性。     

Mapping performance of curved-path SAR

Synthetic aperture radar (SAR) mapping is usually performed along a straight path. Curved paths away from the target area will increase the mapping rate significantly. Drawbacks are more complex signal processing and decreased azimuth resolution due to the reduced dwell time. In this paper, curved SAR mapping is analyzed in more detail, including squinted beam geometry. Relationships are derived how the SAR resolution and mapping rate are influenced by the curved SAR path. The nonlinear phase error, which defocuses the SAR image, is more accentuated than for straight-line SAR, in particular at squinted observation angles. Simulation examples show how the nonlinear phase error depends on side acceleration and mapping geometry after scene center motion compensation.     

一种超宽带10 GHz微波光子雷达包络与相位联合运动误差估计方法

由于运动误差严重的2维空变性,对于10 GHz超宽带微波光子SAR,传统的直接从相位进行运动误差估计的方法估计精度不高。因此,该文提出一种包络与相位联合的超高分辨运动误差估计方法,能够在没有惯导信息时实现运动误差的精确估计。该方法首先在距离徙动矫正(RCMC)之前,通过对包络对齐算法(RAA)提取的包络信息采用最小二乘算法(LSA)与梯度下降算法(GDA)获得近似的3维运动误差。接着,对粗补偿与RCMC之后的数据,先消除方位相位空变,然后采用两维空变的相位误差估计方法获得剩余运动误差的精确估计。仿真和车载微波光子雷达实测数据验证了该方法的有效性。

     

Resolution limits in signal recovery

Resolution analysis for the problem of signal recovery from finitely many linear measurements is the subject of this paper. The classical Rayleigh limit serves only as a lower bound on resolution since it does not assume any recovery strategy and is based only on observed data. We show that details finer than the Rayleigh limit can be recovered by simple linear processing that incorporates prior information. We first define a measure of resolution based on allowable levels of error that is more appropriate for current signal recovery strategies than the Rayleigh definition. In the practical situation in which only finitely many noisy observations are available, we have to restrict the class of signals in order to make the resolution measure meaningful. We consider the set of bandlimited and essentially timelimited signals since it describes most signals encountered in practice. For this set, we show how to precompute resolution limits from knowledge of measurement functionals, signal-to-noise ratio, passband, energy concentration regions, energy concentration factor, and a prescribed level of error tolerance. In the process, we also derive an algorithm for high-resolution signal recovery. We illustrate the results with examples in one and two dimensions     

一种改进的SAR反投影图像相位梯度自聚焦方法

反投影(BP) 算法是一类经典的合成孔径雷达(SAR)成像处理方法。BP在已知航迹条件下可以实现数据的高精度聚焦。但是,BP重建图像中,运动误差导致的目标散焦通常沿着不同的方向存在,残留距离徙动不能严格限制在一个距离分辨率单元内,运动补偿困难。文中提出了一种修正投影栅格的子带宽相位梯度自聚焦(PGA)处理方案。其中,基于数据采集平面的非均匀栅格重建图像,完全去除了目标散焦方向的空变特性。然后,对子带宽分解的反投影数据进行PGA运动补偿并拼接得到全分辨率图像。最后,点目标仿真验证了该方法的有效性。     

Geoid undulation accuracy

For use in oceanographic applications the geoid is ideally needed to a high accuracy and to a high resolution. In 1979 the cumulative geoid undulation error to spherical harmonic degree 20 was ±1.4 m for the GEM10 potential coefficient model. Today the corresponding value has been reduced to ±25 cm for GEM-T3 or ±11 cm for the OSU91A model. Similar improvements are noted in harmonic degree (wavelength) and in resolution. The accuracy of the determination of the geoid is discussed from several points of views. Some comparisons are made with information available 12 years ago and that now available in the time framework of the TOPEX launch. It is noted that the accuracies described are subject to constant improvement. This is especially true as new satellite tracking data (e.g. DORIS data) are used in the potential coefficient models and more satellite altimeter data become available from the ERS-1 and TOPEX/Poseidon missions     

Choice of low resolution sample sets for efficient super-resolution signal reconstruction

In applications such as super-resolution imaging and mosaicking, multiple video sequences are registered to reconstruct video with enhanced resolution. However, not all computed registration is reliable. In addition, not all sequences contribute useful information towards reconstruction from multiple non-uniformly distributed sample sets. In this paper we present two algorithms that can help determine which low resolution sample sets should be combined in order to maximize reconstruction accuracy while minimizing the number of sample sets. The first algorithm computes a confidence measure which is derived as a combination of two objective functions. The second algorithm is an iterative ranked-based method for reconstruction which uses confidence measures to assign priority to sample sets that maximize information gain while minimizing reconstruction error. Experimental results with real and synthetic sequences validate the effectiveness of the proposed algorithms. Application of our work in medical visualization and super-resolution reconstruction of MRI data are also presented.     

基于Kronecker压缩感知的宽带MIMO雷达高分辨三维成像

在宽带多输入多输出(MIMO)雷达3维成像中,MIMO雷达收发阵元数量和空间分布的限制会导致图像的2维横向分辨率难以满足实际需求。该文利用压缩感知(CS)理论来实现图像在2维横向上的超分辨。考虑到对信号的每一维分别进行超分辨会损失各维间的耦合信息,提出一种基于Kronecker CS(KCS)的2维联合超分辨方法;为解决KCS在多维高分辨应用中存储量大、计算效率低的问题,进一步提出了一种基于低分辨3维图像先验信息的降维KCS方法。仿真和实测数据实验验证了方法的有效性。     

条带模式合成孔径激光雷达不依赖PGA的高分辨率成像演示

合成孔径激光雷达(SAL)能实现远距离目标的高分辨率成像.然而,由于所用激光波长很短,SAL系统中微小机械振动都可能在目标回波信号中引入巨大相位误差,所以,SAL很难实现稳定的相位史数据,高分辨率SAL图像的形成往往要应用额外的相位误差消除技术,特别是相位梯度自聚焦(PGA)技术.演示了一个运转良好的条带模式SAL实验室成像装置.采用一台1 550 nm波段的线性调波长激光器作为探测光源,该装置能够形成聚焦良好的高分辨率图像.通过细致的系统设计,基本抑制了在回波信号中产生相位误差的各种振动.该装置产生的相位史数据非常稳定,高分辨率图像的形成仅需简单遵照标准的SAL成像理论,无需额外借助PGA.采用点目标定标,测量得到该成像装置的方位和距离分辨率接近其理论估计.详细给出了2.4 m距离上多种目标的良好聚焦图像及相应的稳定相位史数据.     

A robust algorithm for reduction of truncation artifact in chemical shift images

A new iterative technique to reduce the ringing artifacts in chemical shift images due to the truncation of the high spatial frequency is presented. In this approach the authors extrapolate the high spatial frequency data guided by the edge information obtained from a high resolution anatomic image of the region of interest. The fact that the edge information obtained from the anatomic image can be off by a few pixels (due to factors such as chemical shift artifact, error in edge detection or misregistration) is taken into account by assuming a confidence interval of several pixels around the anatomic edges. The algorithm is validated on simulated and in vivo data, and excellent results were obtained.     

Automatic labeling and characterization of objects using artificial neural networks

Existing NASA supported scientific databases are usually developed and managed by a team of database administrators whose main concern is the efficiency of the databases in terms of normalization and data search constructs. The populating of the database is usually done in a manual fashion by row and column as the data become available, and the data dictionary is usually defined by the same team (at times with little input from the end science user). This process is tedious, error prone and self-limiting in terms of what can be described in a relational Data Base Management System (DBMS). The next generation Earth remote sensing platforms [i.e., Earth Observing System (EOS)] will be capable of generating data at a rate of over 300 Megabits per second from a suite of instruments designed for different applications. What is needed is an innovative approach that creates object-oriented data-bases that segment, characterize, and catalog, and are manageable in a domain-specific context, and whose contents are available interactively and in near-real-time to the user community. This paper describes work in progress that utilizes an artificial neural net approach to characterize satellite imagery of undefined objects into high-level data objects. The characterized data is then dynamically allocated to an object-oriented database where it can be reviewed and accessed by a user. The definition, development, and evolution of the overall data system model are steps in the creation of an application-driven knowledge-based scientific information system.     

Passive Error Concealment for Wavelet-Coded I-Frames With an Inhomogeneous Gauss–Markov Random Field Model

In video communication over lossy packet networks (e.g., the Internet), packet loss errors can severely damage the transmitted video. The damaged video can largely be repaired with passive error concealment, where neighboring information is used to estimate missing information. We address the problem of passive error concealment for wavelet coded data with dispersive packetization. The reported techniques of this kind have many problems and usually fail in the reconstruction of high-frequency content. This paper presents a novel locally adaptive error concealment method for subband coded I-frames based on an inhomogeneous Gaussian Markov random field model. We estimate the parameters of this model from a local context of each lost coefficient, and we interpolate the lost coefficients accordingly. The results demonstrate a significant improvement over the reported related methods both in terms of objective performance measures and visually. The biggest improvement of the proposed method compared to the state-of-the-art in the field is the correct reconstruction of high-frequency information such as textures and edges.      

基于光学相干层析成像的投影折射率计算机层析成像系统研制

报道了基于光纤型光学相干层析成像(OCT)的投影折射率计算机层析成像(PICT)系统,并利用研制的系统对外径为1.3 mm,内径为0.9 mm的充水玻璃管样品进行了测量。样品以1°的步进角旋转,共采集180个方向上的投影值,然后利用卷积反投影算法进行了折射率分布图像的重建。实验结果表明,系统具有较高的空间分辨率,能够正确区分空气、玻璃和水三种不同折射率的物质,且其边界清晰可辨;由于利用了折射率信息,投影折射率计算机层析图像消除了常规光学相干层析图像中的几何畸变。     

面向6G的高分辨率无线信道频域仿真方法及定位技术研究

为了应对6G无线信道中的小数时延和同步误差给定位系统带来的挑战,该文提出基于频域等效的高分辨率信道方法仿真以及基于到达角(AOA)信息的高分辨率定位技术。前者通过将信道抽头时延转换到频域处理,在降低时域方法带来的高复杂度的同时实现了高分辨率仿真,为时延定位信息的实现提供基础;后者则通过将迭代信道估计、基于首到达径检测的AOA估计算法与基于AOA信息的位置估计算法结合起来,在同步误差下实现高精度定位。数值仿真结果表明,二者均在相应的实际场景下实现了高分辨率特性。     

基于频域信息融合和稀疏贝叶斯学习的高分辨ISAR成像

为了在ISAR成像中更好地压制噪声,消除条纹干扰,提高成像分辨率,本文提出一种基于双向插值处理和频域信息融合的稀疏贝叶斯学习算法,称之为BI?FF SBL算法。该方法首先对回波信号分别进行径向和横向插值预处理,将预处理得到的两份数据通过LA?VB算法进行ISAR成像;然后将得到的两幅ISAR图像通过二维傅里叶变换进入频域,并将两个二维频谱进行信息融合处理,以消除噪声和条纹干扰的相关信息并保留目标结构信息;最后对融合处理后的频谱进行二维傅里叶逆变换,得到最终的ISAR图像。为了验证BI?FF SBL算法的ISAR成像效果,本文进行了基于仿真数据和实测数据的成像实验,并将实验结果与R?D算法、L1?BP算法、LA?VB算法进行对比,发现BI?FF SBL算法在压制噪声和去除条纹干扰方面具有明显的优势,且能提供分辨率更高的ISAR图像。当实验数据信噪比降到0 dB时,BI?FF SBL算法依然能够提供清晰的ISAR图像,明显优于其他三种算法。测试超分辨重构误差的实验结果表明,相比于L1?BP算法和LA?VB算法,BI?FF SBL算法的重构误差更低,在实验数据信噪比为0 dB时,重构信噪比可以达到13.55 dB。     

Accurate estimation of the Fisher information matrix for the PET image reconstruction problem

The Fisher information matrix (FIM) plays a key role in the analysis and applications of statistical image reconstruction methods based on Poisson data models. The elements of the FIM are a function of the reciprocal of the mean values of sinogram elements. Conventional plug-in FIM estimation methods do not work well at low counts, where the FIM estimate is highly sensitive to the reciprocal mean estimates at individual detector pairs. A generalized error look-up table (GELT) method is developed to estimate the reciprocal of the mean of the sinogram data. This approach is also extended to randoms precorrected data. Based on these techniques, an accurate FIM estimate is obtained for both Poisson and randoms precorrected data. As an application, the new GELT method is used to improve resolution uniformity and achieve near-uniform image resolution in low count situations.     

基于距离像长度特征辅助的雷达目标跟踪

传统雷达目标跟踪仅利用角度和距离数据,由于获取的测量信息较少,跟踪精度受限。本文利用现代雷达所具有的距离高分辨能力,提出了一种基于距离像长度特征辅助的跟踪模型,并结合先进的非线性滤波算法得到了一种高性能目标跟踪算法—FAT UKF。该算法将目标的运动状态与距离像长度信息联系起来,通过增加观测量的维数来提高雷达的跟踪能力。对典型实例的计算机仿真结果表明,基于特征辅助的跟踪算法不仅收敛速度快,且能有效突破传统跟踪算法的理论误差下限,大大提高了雷达跟踪系统的整体性能。