基于两层均匀媒质的GPEN SAR地下目标成像方法及其性能分析

地表穿透合成孔径雷达(Ground PENetration SAR,GPEN SAR)为了探测掩埋在地下的目标,通常工作在多层媒质的环境中。传统成像模型是建立在同一均匀媒质的假设上,不再适合于GPEN SAR的实际情况。本文首先建立了两层分区均匀媒质中的成像模型,然后利用后向投影(BP)算法定量分析了成像几何参数、土壤参数等对成像的影响,进而提出了一种修正的后向投影(MBP)算法。MBP算法不仅能够校正两层分区均匀媒质对成像定位的影响,还能估计目标的掩埋深度,提供目标三维位置坐标。仿真结果验证了MBP算法在不同信噪比环境下,对多目标的三维定位精度能满足实际的需要。     

Range Assignment for Biconnectivity and k-Edge Connectivity in Wireless Ad Hoc Networks

Depending on whether bidirectional links or unidirectional links are used for communications, the network topology under a given range assignment is either an undirected graph referred to as the bidirectional topology, or a directed graph referred to as the unidirectional topology. The Min-Power Bidirectional (resp., Unidirectional) k-Node Connectivity problem seeks a range assignment of minimum total power subject to the constraint that the produced bidirectional (resp. unidirectional) topology is k-vertex connected. Similarly, the Min-Power Bidirectional (resp., Unidirectional) k-Edge Connectivity problem seeks a range assignment of minimum total power subject to the constraint the produced bidirectional (resp., unidirectional) topology is k-edge connected. The Min-Power Bidirectional Biconnectivity problem and the Min-Power Bidirectional Edge-Biconnectivity problem have been studied by Lloyd et al. [23]. They show that range assignment based the approximation algorithm of Khuller and Raghavachari [18], which we refer to as Algorithm KR, has an approximation ratio of at most 2(2 – 2/n)(2 + 1/n) for Min-Power Bidirectional Biconnectivity, and range assignment based on the approximation algorithm of Khuller and Vishkin [19], which we refer to as Algorithm KV, has an approximation ratio of at most 8(1 – 1/n) for Min-Power Bidirectional Edge-Biconnectivity. In this paper, we first establish the NP-hardness of Min-Power Bidirectional (Edge-) Biconnectivity. Then we show that Algorithm KR has an approximation ratio of at most 4 for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity, and Algorithm KV has an approximation ratio of at most 2k for both Min-Power Bidirectional k-Edge Connectivity and Min-Power Unidirectional k-Edge Connectivity. We also propose a new simple constant-approximation algorithm for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity. This new algorithm applies only to Euclidean instances, but is best suited for distributed implementation. A preliminary version of this work appeared in the proceedings of the 2nd International Conference on AD-HOC Network and Wireless (Adhoc-Now 2003). Research performed in part while visiting the Max-Plank-Institut fur Informatik. Gruia Calinescu is an Assistant Professor of Computer Science at the Illinois Institute of Technology since 2000. He held postdoc or visiting researcher positions at DIMACS, University of Waterloo, and Max-Plank Institut fur Informatik. Gruia has a Diploma from University of Bucharest and a Ph.D. from Georgia Insitute of Technology. His research interests are in the area of algorithms. Peng-Jun Wan has joined the Computer Science Department at Illinois Institute of Technology in 1997 and has been an Associate Professor since 2004. He received his Ph.D. in Computer Science from University of Minnesota in 1997, M.S. in Operations Research and Control Theory from Chinese Academy of Science in 1993, and B.S. in Applied Mathematics from Tsinghua University in 1990. His research interests include optical networks and wireless networks.     

个性化公开密钥系统的设计

论文提出利用用户提供的个性化信息来随机产生关联大素数,保证了素数选取的随机化、个性化,提高了RSA算法的安全性。     

一种基于无理数加密算法的数字签名方案

为了提高现代网络信息传输的安全性,利用无理数小数点后数字的无穷性、无规律性、分布均匀性,提出一种全新的加密算法,并用它所产生的密钥流进行数字签名,实现身份验证不可抵赖、信息传输无篡改,确保信息传输的完整性、真实性,达到提高加密效率、相互认证的效果。     

人工免疫原理在网络入侵检测系统中的研究

文章分析了人工免疫系统的原理,简单建立了一种基于否定选择算法的网络入侵检测系统,引入了一种用于异常事件识别的r-字符块匹配规则,并对规则存在的漏洞进行了分析。     

分组空时块码系统中的排序最大信噪比检测算法

提出并比较了应用于分组空时块码（G—STBC）系统中两种不同信道模型的排序最大信噪比（MaxSNR）检测算法。该系统在发端对发射天线分组，每组进行独立的空时块码编码；在收端应用排序最大信噪比算法进行检测。由于空时块码提供了额外的时域约束，所以可以利用这个约束对信道模型进行变换，得到一个等效信道模型，然后再使用排序MaxSNR检测；当然也可以直接利用原有的信道模型，即非等效信道模型进行检测。仿真结果表明：当接收天线数不少于发射天线数的一半时，采用等效信道模型下的排序MaxSNR算法，系统的误码曲线就能保持陡降性；并且在收发天线数相同时，其性能总是优于非等效信道模型。     

并行算法在软件无线电多DSP平台的应用

近年来，随着软件无线电的发展，用于软件无线电平台中的多DSP并行结构受到越来越多的关注，因为这种结构能提高数字信号处理的速度。提出了一种适合在该平台上并行运算的算法，以多阶FIR滤波器为例，验证了算法，并探讨算法的性能，给出了该算法在多处理器条件下，与单处理器处理结果的比较。对选取合适的软件无线电中频处理多处理器平台具有一定的参考价值，并对舰载软件无线电的实现提供了科学参考。     

IP网络上电路倍增设备的研究

简要介绍了通过IP网络上电路倍增设备(IP CME)的数据流的处理过程;IP CME中的复用技术;控制IP包发送的激活算法;网络发生拥塞丢包的处理方法;并在传输效率和信令处理2个方面与VOIP进行比较,可以看出IP CME具有很大的优越性和良好的发展前景。     

语音信号的线性预测分析在DSP上的优化实现

语音信号的线性预测分析是语音压缩中的一个重要环节，占据语音压缩计算中的大部分时间，为提高语音压缩的速度，在C54x系列DSP上用汇编语言实现了语音信号的线性预测分析，并对其进行优化。最终可以使代码的运行时间减少到原来的5％左右。     

径向基函数神经网络的再学习算法及其应用

为了应用径向基函数神经网络逐步地识别待研究系统,文章针对径向基函数神经网络的再学习算法开展了深入的研究.应用严格的数学推理方法,将径向基函数神经网络的再学习问题转化为矩阵求逆的附加运算.详细给出了径向基函数神经网络再学习算法中增加新训练样本和增加新基函数的数学公式,同时对如何获取新的训练样本进行了研究.