协同作战能力简析

协同作战能力(CEC)是一种充分利用网络技术的新型海岸防空技术，给系统的作战能力带来了革命性的交破。本文对协同作战能力的产生、功能、组成以及未来的发展趋势作了详细的介绍，阐述了CEC系统的总体设计思想。在此基础上，将CEC系统与传统的作战系统的性能和设计思想在各方面进行了比较，交出了CEC系统各方面的优越性能。协同作战能力是现代和未来作战系统的发展方向，CEC系统的发展必将成为衡量各国国防科技现代化的重要指标。     

飞行目标3维姿态测量的新方法

针对传统光测方法通常用于测量目标的点运动轨迹,而难以获得目标的3维姿态参数的情况,提出用数字图像处理手段,对目标图像建立特征点,结合特定的算法,得出目标的俯仰角、偏航角、滚动角、漂移量等3维参数,从而获取更多的目标姿态参数的新方法。     

A New Approach for Built‐in Self‐Test of 4.5 to 5.5 GHz Low‐Noise Amplifiers

This paper presents a low‐cost RF parameter estimation technique using a new RF built‐in self‐test (BIST) circuit and efficient DC measurement for 4.5 to 5.5 GHz low noise amplifiers (LNAs). The BIST circuit measures gain, noise figure, input impedance, and input return loss for an LNA. The BIST circuit is designed using 0.18 μm SiGe technology. The test technique utilizes input impedance matching and output DC voltage measurements. The technique is simple and inexpensive.     

子空间方法盲多用户检测技术分析与探索

着重分析了基于子空间跟踪的盲线性多用户检测算法 ,并对其内部算法模块进行了仿真比较 ,最后对算法性能改善方法提出了自己的新思路     

海杂波中基于混沌预测的目标检测方法改进

基于记忆库非线性预测的NP-CFAR方法是目前混沌海杂波背景中目标检测的一种典型而先进的方法.考虑到海杂波功率与特征的时变不稳定性,本文提出运用旋转超盒分类取代这一方法中的NP-CFAR进行目标检测,并探讨了运用盒维数特征提取进行预处理以节省运算开销的问题.仿真实验验证了本文所提改进方法的有效性.     

Signal Integrity: Fault Modeling and Testing in High-Speed SoCs

As we approach 100 nm technology the interconnect issues are becoming one of the main concerns in the testing of gigahertz system-on-chips. Voltage distortion (noise) and delay violations (skew) contribute to the signal integrity loss and ultimately functional error, performance degradation and reliability problems. In this paper, we first define a model for integrity faults on the high-speed interconnects. Then, we present a BIST-based test methodology that includes two special cells to detect and measure noise and skew occurring on the interconnects of the gigahertz system-on-chips. Using an inexpensive test architecture the integrity information accumulated by these special cells can be scanned out for final test and reliability analysis.     

A Combined Antenna Array and Multi-User Detection DS-CDMA Receiver in Single-Path and Multi-Path Fading Channels

An adaptive antenna array is incorporated into a decorrelatingmulti-user detector to effectively increase the DS-CDMA system capacity.Capacity improvement is due to beamforming gain, spatial diversity gain(assuming large angle spread), and the decorrelating effect. Thereceiver has been analyzed for the cases of sufficiently andinsufficiently spaced receiving antennas. The receiver consists of afront-end beamformer for every user in the cell and has knowledge of allusers' signature sequences. The beamformer estimates the desired userchannel vector, enhancing its signal and reducing the co-channelinterference from other directions. The multi-user detection, exploitingknowledge of other users, rejects those interferers whose arrival anglesare close to that of the desired user. The average uncoded Bit ErrorRate (BER) as a function of the number of in-beam active users, theaverage antenna Signal-to-Noise Ratio (SNR), and the number of receivingantennas is examined in both single-path and multi-path Rayleigh fadingchannels. Analysis shows an increase in system capacity proportional tothe number of receiving antennas.     

一种新颖的表面等离子谐振效应光波导水质传感技术

光学表面等离子谐振（ＳＰＲ）效应是一种很有效的水质检测技术，经过详细的理论推导，同了ＳＰＲ反射光强的普遍适用公式。在纯水与受污染水两种情况下，根据一些已知参数计算出结果。由计算结果数据一出的曲线比较表明，ＳＰＲ效应在两种情况下有明显差别，这也正是ＳＰＲ效应用于水质检测的理论根据。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

纳米级精度分光路双频干涉度量系统的设计

为完成快速、精确的外观轮廓度量,设计了一种新型纳米级精度分光路双频干涉度量系统。系统由低频差双频激光干涉度量模块和微探头及二维工作台两部分组成。微探针以轻敲式接近样品至几十纳米时,受原子力作用发生偏转,利用双频干涉模块度量其纵向偏转量,并对样品进行梳状式度量得到外观形貌。根据双频激光的实际光源,对原有双频干涉度量理论进行了改进提高。进行了系统组建和实验验证。结果表明:系统具有纳米级精度,可用于超精样品外观轮廓度量。