MIMO雷达波形设计与杂波仿真
这是一篇论文，系统介绍了MIMO雷达的基本原理、波形设计，并对杂波做了建模和仿真。分类号密级UDC注1学位论文MIMO雷达波形设计与杂波仿真(题名和副题名)陈翔(作者姓名)指导教师李军副教授电子科技大学成都(姓名、职称、单位名称)申请学位级别硕士学科专业信号与信息处理提交论文日期2015.3.30论文答辩日期2015.56学位授予单位和日期电子科技大学2015年6月答辫委员会主席评阅人注1:注明《国际十进分类法UDC》的类号WAVEFORM DESIGN FORMIMO RADAR AND CLUTTER SIMULATIONA Master thesis submitted toUniversity of Electronic Science and Technology of chinaMajor: Signal and Information ProcessingAuthor.Chen Xiangadvisor:Li JunSchoolSchool of Electronic Engineering独创性声明本人声明所呈交的学位论文是本人在导师指导下进行的研究工作及取得的研究成果。据我所知,除了文中特别加以标注和致谢的地方外,论文中不包含其他人已经发表或撰写过的研究成果,也不包含为获得电子科技大学或其它教育机构的学位或证书而使用过的材料。与我·同工作的同志对本研究所做的任何贡献均已在论文中作了明确的说明并表示谢意。作者签名:日期:年月日论文使用授权本学位论文作者完全了解电子科技大学有关保留、使用学位论文的规定,有权保留并向国家有关部门或机构送交论文的复印件和磁盘,允许论文被查阅和借阅。本人授权电子科技大学可以将学位论文的仝部或部分内容编入有关数据库进行检索,可以采用影印、缩印或扫描等复制手段保存、汇编学位论文(保密的学位论文在解密后应遵守此规定)作者签名导师签名:日期:年月日摘要摘要多输入多输出( Multiple- nput multiple- Output,MMo)雷达是一种近十几年才发展起来的新体制雷达,它发射的是彼此相互正交的信号,这样MIMO雷达的信号类型与可控参数就比传统相控阵雷达更为丰富与复杂。良好的波形设计能够充分利用MIMO○雷达丰富的空时频资源,能够提高日标的探测、跟踪性能并且降低被敌方截获的概率。因此,正交波形设计是研究MMO雷达系统的关键之处,优化波形的优劣将直接决定MMO雷达性能的好坏。本文主要针对MMO雷达背景研究了两种新的正交波形优化设计方法,并结合实际工程应用背景和需求,优化改进了多相编码序列的优化算法。同吋,对MIMO雷达的地杂波进行建模分析,给出了双基地MIMO雷达的地杂波的仿真。木文涉及的内容主要包含下面几点:1.对MIMO雷达的基本结构、工作原理及特点分别进行阐述,讨论了MIMO雷达正交波形的类型和形式2.研究了基于新循环算法(CAN, Cyclic algorithm-ncw)来设计正交波形通过将相关峰值旁辦水平的最小化问题等价为一个频域最小化问题,进而转化为一个二次函数的最小化问题,并对这一二次函数不断循环优化,最终获得最优值。该算法具有很强的计算能力,能够满足雷达对超长编码的需求,冋时设计出的正交波形具有较低的相关特性,最后对该算法的相关特性进行分析。3.研究了基于序列二次规划算法()设计的连续相位编码信号,并通过在目标函数中添加严格正交约束条件使得设计出的信号具有严格正交性,提升了杂波对消的效果,能够有效的提升目标的探测性能。同时将“和信号”相关旁辦引入到目标函数之中,改善了“和信号”的相关输出。通过相位量化过程使得设计出的信号满足工程上对离散相位的要求,并对量化特性以及参数约束条件对相关峰值旁瓣量的影响让行了分析4.对MIMO雷达地杂波进行仿真,通过对两种不同幅度分布的杂波仿真分别对零记忆非线性变换法和球不变随机过程法进行研究分析,并对这两种杂波仿真方法进行比较与总结,同时对双基地MIMO雷达地杂波进行建模与仿真并进行分析关键词:MIMO雷达,正交波形设计,“和信号”相关旁瓣,严格正交性,杂波仿真ABStRaCtABSTRACTMultiple-input multiple-output (MIMO) radar as a new radar system wasdeveloped in the last decade and it has become the focus of the current internationaresearch. MIMO radar transmitter signals are mutually orthogonal to cach other, so thetype of mimo radar signal with richer controllable parameters and more complex thanthe conventional phased array radar. a good waveform designed can take full advantageof MIMO radar rich space-frequency and code resources, it could also improve targetdetection, tracking performance and reduce the probability of being intercepted by theenemy. Therefore, orthogonal waveform design is the key point of mimo radar systemsOrthogonal waveform design will directly determine the performance of MIMO radarare good or badThe main content about this article is researched two new orthogonal waveformdesign optimization methods, combined with practical engineering background andneeds, improved and optimization multi-phase coding sequence algorithms. meanwhileMIMO radar clutter is modeled by analyzing the bistatic MIMO radar cluttersimulationContents of this article are mainly involved in the following areas1. The basic structure of MiMo radar and the basic working principles aredescribed, discussed the types and forms of MIMO radar orthogonal waveform2. Research based on Can algorithm design orthogonal waveforms, by equivalentcorrelation peak sidelobe level minimization problem is a frequency-domainminimization problem, and then transformed into a quadratic function minimizationproblem and loop optimization sub-problems, and ultimately got the best value. Thealgorithm has a strong computing power, able to meet the demand for long- coded radarand the orthogonal waveforms has a low correlation characteristic. Finally, analyzed therelevant characteristics about this algorithm3. Research based on sequential quadratic programming algorithm design ofcontinuous phase encoded signals, and in the objective function by adding stringentconstraints make orthogonal design with strictly orthogonal signals, thereby improvinthe noise cancellation effect, it can effectively enhance the target detection accuracyMeanwhile, the sum-signal"associated sidelobe being introduced into the objectiveABSTRaCTfunction, improve the"sum-Signal"of the correlation output. Such that the quantizationprocess on the phase of a signal designed to meet the engineering requirements of thediscrete phase, and the quantization characteristics and parameter constraints on theamount of side lobe correlation peaks are analyzed4. Research on MIMO radar ground clutter modeling and simulation, through zeromemory nonlinearity simulation Weibull distribution clutter and through sphericallyinvariant random processes simulation K distribution clutter, and compared andsummarized this two methods. Meanwhile, for bistatic MiMo radar ground clutter hasbeen simulated and analyzedKeywords: MIMO radar, orthogonal waveform design, sum-signal"correlationsidelobe, strict orthogonal, clutter modeling目录目录第一章绪论……1.1研究背景与意义1.2研究动态与发展现状….·······1.2.1MIMO雷达波形设计现状223122MIMO雷达动态及发展状况1.3主要工作及内容安排第二章MMO雷达原理及波形设计概述2.1MIMO雷达基本原理及其特点2. I MIMO雷达基木原理2L2MIMO雷达特点22MMO雷达波形分类及设计特点2,21MIMO雷达正交波形设计特点222MIMO雷达波形分类23本章小结第三章基于CAN算法的MIMO雷达波形设计143.1MIMO雷达正交波形设计原理.酯音音看。普音DD音音番音音垂音看看3.2于CAN算法的正交波形设计;垂..看看看垂垂D垂垂·垂.垂。垂。着看垂音垂非·垂。垂非看153.2.1问题模型描述……153.2.2设计方法及设计流程…………173.23设计结果3.3基于CAN算法相关特性分析.233.3.1编码长度对相关峰值旁辦的影响233.3.2信号个数对相关峰值旁瓣的影响2434本章小结25第四章基于序列二次规划算法的MMO雷达波形设计264.1序列二次规划的数学描述264,2连续相位编码信号设计.274.2.1设计方法及设计流程1看看274.2.2设计结果。,看音音着着;音音DD看垂音音音自看看垂。垂DD音音音,音垂看看垂294.3量化及量化后相关特性分析…
- 2021-05-06下载
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网络ns2仿真实验分析(RED、丢包率、端到端延迟、吞吐量)附源码
网络ns2仿真实验分析(RED、丢包率、端到端延迟、吞吐量)附源码分组的端口号。(10) dst addr:目的地址,格式为 node port,其中node代表分组发送节点的id,pot表示发送分组的端口号。(11) seg num:分组的序列号。(12) okt id:分组的唯标识符。3n2与n3之间的RED队列的半均队列长度与当前队列长度随时间的变化如下图所示:torrent and ave"吧 e PED CueL旧300era已n15000ANA图2平均队列长度与当前队列长度随时问变化的曲线图4运行结果中显示CBR流量总共发包550,丢失16,丢包率为:0.029。丢包率随时间的变化如下图所示:packets of lost rate。045graph自04,03500自020.015图3丢包率随时间变化的关系图5CBR流量的吋延随时间的变化如下图所示:1u彐r10.14心01Q。0图4端到端时延随时间变化的关系图6.节点n2的平均吞吐量随时间的变化如下图所示100T图5节点n2的吞吐量随时间变化的关系头7.结果分析:从RED的图示中,可以看出队列的大小波动变化不是很大,在处理突发的包时冇一定的优势。从丟包率、时延和吞吐量的变化图中,可以看出当丟包率增加时,端到端之问的时延也在增加,而吞吐量则下降,丟包率、时延和吞吐量在表示网络性能的好坏时有一定的关系、相关代码1.络拓扑仿真脚木 simulator:tcl:#Create a simulator objectset ns [new Simulator]#Define different colors for data flows for NAM)Sns color 1 BlueSns color 2#Open the nam trace fileset nt lopen out. nam wSns namtrace-all Snfset nd [open out. tr wISns trace-all Snd#Define a finish procedureproc finish仆}{global ns nf ndSns flush-traceclose Snfclose sndexec nam out. namkit o#Create four nodesset no [Sns node]et n1 [Sns nodelset n2 [Sns nodeset n3 [ns node]#Create links between the nodesSns duplex-link Sn0 Sn2 2Mb 10ms DropTailSns duplex-link Sn1 Sn2 2Mb 10ms DropTailSns duplex- link Sn2 Sn3 1.7Mb 20ms RED#Set queue Size of link (n2-n3 to 100Sns queue-limit Sn2 Sn 3 100#Give node position(for NAm)Sns duplex-link-op SnO Sn2 orient right-downSns duplex-link-op Sn1 Sn2 orient right-upSns duplex-link-op $n2 Sn3 orient right#Monitor the queue for link(n2-n3 .( for NAM)Sns duplex-link-op Sn2 Sn 3 queuePos 0.5#Setup a TCP connectionset tcp new Agent/TCPISns attach-agent Sno Stcpset sink [new Agent/TCPSinkSns attach-agent sn3 SinkSns connect stcp SinkStcp set fid 1#Setup a FTP over TCP connectionset ftp [new Application/FTPlSftp attach-agent StcpSftp set type FTPfsetup a UdP connectionset udp [new Agent/UDP]Sns attach-agent Sn1 udpset null [new Agent/Nul]Sns attach-agent Sn3 SnullSns connect Udp SnullUdp set fid_ 2#Setup a CBr over UDP connectionset cbr [new application/Traffic/ CBRIScbr attach-agent UdpScbr set type CBrScbr set packet size 1000Scbr set rate 1mbScbr set random false#Schedule events for the cbr and ftp agentsSns at0.1 Scbr startSns at 1.0"Sftp start"Sns at 40.0"Sftp stop"Sns at 4.5"Scbr stop"#Detach tcp and sink agentsSns at 50 Sns detach-agent $no stcp; Sns detach-agent sn3 Sink"Sns at 50.0 finish#monitor n2 and n3 queueset redg [[sns link Sn2 Sn3] queueset traceq lopen redQueue tr wSredg trace curgSredg trace aveSredg attach Strace#Run the simulationns rur2.RED的数据处理脚本:SgreparedQueue. tr>averagetrStrep“Q" reqUeuetr> current tr(中 reqUeue tr为跟踪n2和n3队列产生的文件)然后使用 gnuplot工具使用 average tr和 current, tr绘制队列随时间变化的曲线3.丢包率数据awk处理脚本 graph rostRate,awvk#count the packet lost rate of cBri=0;vente=S2;from Node =$3toNode=s4:pitT$7srcAddr=$9dstAddr=$10gNum = $11if (fromNode ==1 & toNode ==2&& event==+i totalNum++timeArr[i=timesrate[i]= float)(drop Num/tif(fid==2&& event==d")dropNum++ENDprintf("#number of packet sent: %od, lost: %d"totalNum, dropNum)printf( #lost rate of packets: %f",dropNum/totalNumfor(j=0; j
- 2020-12-06下载
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