多径效应对直扩延迟锁定环的影响及消除技术

针对多径环境下直扩(DS-SS)信号的伪码跟踪问题,对延迟锁定环(DLL)进行了研究.在考虑多条路径干扰信号的情况下分析了多径效应对DLL鉴相特性的影响.为了消除DLL中的多径和噪声干扰,采用一种基于卡尔曼滤波的最大似然多径估计方法对DLL进行了改进.该方法通过对最大似然估计的输出进行卡尔曼滤波,得到了较为准确的多径幅...     

无线光电定位网络的设计

为满足非接触化、小型化、集成化、数字化、智能化等现代检测技术的发展要求,从成本、工作原理、灵敏度等方面综合考虑,现采用以光电定位模块为核心的光电定位技术,以无线传感器网络作为数据传输与管理的技术手段,构建了无线光电定位网络,并进行了实验分析.可实现多点实时监测、异地显示测量数据、数据网络化管理等特殊需求;涵盖了多学科领...     

Contourlet变换低通滤波器对图像融合算法影响的讨论

根据Contourlet变换多尺度、多方向的特性以及自然图像的频谱特点, 分析了Contourlet变换低通滤波器对图像融合算法性能和融合结果中伪轮廓的影响, 讨论了低通滤波器与分解层数选取之间的关系. 理论与实验证明, 使用带宽较窄的低通滤波器能够得到较好的融合结果, 当低通滤波器系数均为正数时融合图像的伪轮廓显著减少. 本文比较了使用不同低通滤波器和不同融合准则时得到的融合结果, 实验结果证明, 使用合适的低通滤波器, 可以在选用较简单的融合准则和分解较少层数的情况下, 得到很好的融合结果, 大大减小了融合算法的复杂度.     

无源毫米波成像最大似然频域校正超分辨算法

在无源毫米波成像中, 因为天线孔径大小的限制而导致获取的图像分辨率低, 所以必须采取有效的后处理措施增强分辨率. 本文提出了一种针对无源毫米波成像应用的最大似然频域校正超分辨算法. 该算法首先使用Wiener滤波复原算法恢复图像通带内的频谱分量, 然后运用Richardson-Lucy算法实现频谱外推, 最后通过一种频域校正算法, 用Wiener滤波器恢复的频谱代替通带内的频谱, 保证图像的低频分量不被破坏. 实验结果表明, 该算法改善了收敛速度, 增强了图像的分辨率, 同时能够有效地减轻恢复图像中的振铃波纹, 有利于无源毫米波成像超分辨的实现.     

基于FPGA的全数字上变频系统设计

介绍一种利用新器件特性实现全数字上变频的方法,包括射频频率范围内从基带信号的插值滤波器的设计、载波信号的产生,到针对射频信号高采样率的并行处理方法以及与数模转换器件的接口设计。与传统模拟方案相比,本设计具有更佳的性能、更低的成本和更好的灵活性,可广泛用于电缆调制解调器系统。     

Concurrency control in mobile distributed real-time database systems

This paper presents DMVOCC-2PLV (Distributed Multiversion Optimistic Concurrency Control with Two-Phase Local Validation) protocol for processing mobile distributed real-time transactions in mobile broadcast environments. In DMVOCC-2PLV protocol, transaction validation is performed at two levels: local validation and global validation. Local validation of transactions is performed in two phases: local pre-validation and local final validation. At the MHs (Mobile Hosts), all mobile transactions perform local pre-validation of transactions by using a backward validation mechanism. The local pre-validation process is carried out against committed transactions at the server in the last broadcast cycle. Such an early data conflict detection feature can save processing and communication resources. Transactions that survive in local pre-validation must be submitted to the server for local final validation. In global validation distributed update transactions have to check to ensure distributed serializability in all participants. The protocol can eliminate conflicts between mobile read-only and mobile update transactions, and resolve data conflicts flexibly using multiversion dynamic adjustment of serialization order to avoid unnecessary restarts of transactions. Mobile read-only transactions can be committed with no-blocking, and respond time of mobile read-only transactions is greatly reduced. The tolerance of mobile transactions of disconnections from the broadcast channel is increased. The results of simulation experiment show that the new protocol proposed offers better performance in terms of miss rate, restart rate, commit rate and throughput.     

Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

Space and time localization for the estimation of distributed parameters in a finite element model

In this paper we study the problem of estimating the possibly non-homogeneous material coefficients inside a physical system, from transient excitations and measurements made in a few points on the boundary. We assume there is available an adequate Finite Element (FEM) model of the system, whose distributed physical parameters must be estimated from the experimental data.We propose a space–time localization approach that gives a better conditioned estimation problem, without the need of an expensive regularization. Some experimental results obtained on an elastic system with random coefficients are given.