AD9361中文资料
AD9361中文资料，内容讲述了9361的使用，希望对射频开发者有用，AD9361规格除非另有说明,电气特性在 VDD GPO=33V, VDD INTERFACE=18V,所有其他VDDx引脚=1.3V,T=25°C下测得。表1参数符号最小值典型值最大值件测试条件/注释接收器,一般中心频率706000增益最小值最大值74.5800MH73.02300 MHZ(RX1A, RX2A)72.02300 MHz (RX1 B, RX1CRX2B, RX2C)65.55500 MHZ( RX1A, RX2A)增益步进接收信号强度指示器档位dB准确度dB接收器,800MHz噪声系数最大RX增益三阶输入交调载点IIP318dBrn最大RX增益二阶输入交周载点lP2最大RX增益本振(LO泄漏122dBmRX前端输入正交增益误差0.2%相位误差度调制精度(EVM)192MHz参考时钟输入S10巛1至RX2隔离R×1A至RX2A,RX1C至RX2CX1B至RX2B55RX2至RX1隔离RX2A至RX1A,RX2C至RX1CRX2B至RX1B接收器,2.4GHz噪声系数最大RX增益三阶输入交调载点lP314dBm最大RX增益阶输入父调载点lIP 2d bm最大RX增益本振(LO泄漏110dBm接收器前端输入正交增益误差相位误差0.2度调制精度(∈VM)4240MHz参考时钟输入5110RX1至RX2隔离RX1A至RXZA,RX1C至RX2CRX1B至RX2BRX2至RX1隔离RX2A至RX1A,RX2C至RX1CRX2B至RX1BRev. D Page 3 of 36AD9361参数符号最小值典型值最大值件测试条件注释接收器:55GHz噪声系数NF38最大RX增益三阶输入交调载点lP3d Bm最大RX增益二阶输入交调载点lP2dBm最人RX增益本振LO泄漏dBmx前端输入正交增益误差0.2相位误差度调制精度(EVM)40MHz参考时钟针对RF频率合成器内部加倍)输入51RX1A至RX2A隔离RXA至RX1A隔离5dB发射器一一般中心频率000z功率控制范围dB功率控制分辨率0.25发射器:800MHz输出S2最大输出功率dBm1MH信号音509负载)调制精度(EVM)192MHz参考时钟三阶输出交调载点OIP3dBm载波泄漏dBc0dB衰减40dB衰减本底噪声-157dBm/Hz90MHz偏移隔离1至TX2TX2至T×150dB发射器.24GHz输出SdB最大输出功率7.5dBm1MHz信号音(50Ω负载)调制精度(VM)dB40MHZ参考时钟三阶输出交调载点OIP319dbm载波泄漏0dB衰减3240dB衰减本底噪声156dBm/H290MHz偏移隔离TX1至TX2TX2至TX1dB发射器,5.5GHz输出S最大输出功率6.5dBm|7M信号音50负载)调制精度(EvM)3640MHz参考时钟(针对RF频率合成器内部加倍)三阶输出交调载点OIP317d Bm载波泄漏dBo0dB衰减40dB衰减本底噪声151dBm/Hz90MHz偏移隔离TX1至TX2TX2至TX150Rev. d Page 4 of 36AD9361参数1符号最小值典型值最大值件测试条件注释TX监控器输人(X_MON1,最大输入电平dBm动态范围准确度dBLO频率合成器O频率阶跃2.4 GHz. 40 MHz参考时钟积分相位噪声800 MHZrm100Hz至100MHz,3072MHz参考时钟(针对RF频率合成器内部加倍)24 GHz0.37rm100Hz至100MHz,40MHz参考时钟5.5 GHzrms100Hz至100MHz,40MHz参考时钟(针对R频率合成器内部加倍)参考时钟( REF CLKREF CLK要么为 XTALPXTALN引脚的输入要么为直接连接XTALN引脚的线路输入频率范围50品振输入外部振荡器信号电平Vpp|交流耦合外部振荡器辅助转换器ADO分辨度位输入电压最小值最大值VDDAIP3 BB-005DAO分辨度位输出电压最小值最大值VDD GPO-03输出电流mA数字规格(MOS)逻辑输入输人电压高VDD INTERFACE XO.8VDD INTERFACE低VDD INTERFACE×02V输入电流低+10逻辑输输出电压局VDD INTERFACE XO. 8低VDD_INTERFACE X0.2V数字规格(LVDS)逻辑输入输人电压范围8251575对中的各差分输入输入差分电压阈值100+100接收机差分输入阻抗100Rev. D Page 5 of 36AD9361参数符号最小值典型值最大值件测试条件/注释逻辑输出输出电压高低3751025输出差分电压150Vvvv可分75mV个阶跃编程输出失调电压1200通用输出输出电压高低VDD GPO×08VDD GPO×0.2输出电流SP|时序VDD INTERFACE= 1.8 VSPI CLK周期脉冲宽度SPI ENB建立至第一 SPI CLK上升沿最后 SPI CLK下降沿至0SPI ENB保持SPI DI数字输入建立至SP⊥CLKts数据输入保持至 SPI CLKnsSPI CLK上升沿至输出数据延迟4线模式3线模式ns总线周转时间,读BBP驱动最后地址位后总线周转时间,读0tco(max)nsAD9361驱动最后数据位后数字数据时序(CMOS),VDD INTERFACE=1.8VDATA CLK时钟周期1627661.44 MHZDATA CLK和 FB CLK脉冲宽度t的45%tcp的556TX数据TX FRAME,P0_D和建立至FB_CLK保持至 FB CLKHIX0DATA CLK至数据总线输出延迟toax01.5DATA_CLK至 RX FRAME延迟1.0脉冲宽度使能TXNRXFDD独立ENSM模式TXNRX建立至 ENABLEt0nsTDD ENSM模式总线周转时间RX前2×toTDD模式RX后2×tcpTDD模式容性负载3容性输入pRev. d Page 6 of 36AD9361参数符号最小值典型值最大值件测试条件注释数字数据时序(CMOS)VDD INTERFACE=2.5VDATA CLK时钟周期16.27661.44 MHzDATA CLK和 FB CLK脉冲宽度tcp的45%tc的55%TX数据TX FRAME,POD和P1 D建立至FB_CLK保持至 FB CLKDATA CLK至数据总线输出延迟tox0DATA CLK至 RX FRAME延迟tODDy脉冲宽度使能IXNRXXNRXPW trpFDD独立ENSM模式IXNRX建立至 ENABLEtTXNRXSU OIDD ENSM模式总线周转时间RX前2×toTDD模式tRusT2×tTDD模式容性负载容性输入数字数据时序LvDS)DATA_CLK时钟周期4.069245.76MHzDATA_CIK和FB_CK脉冲宽度t的45t的59TX数据IX HRAM和XD建立至 FB CLK保持至FB_CLKDATA CLK至数据总线输出延迟|tox025DATA CLK至 RX FRAME延迟0.25脉冲宽度使能FDD独立ENSM模式TXNRX建立至 ENABLE0TDD ENSM模式总线周转时间RX前2RX后容性负载容性输入pl电源特性13V电源电压1.2671.33VDD INTERFACE电源额定设置2.5LVDS1.82.5VDD INTERFACE容差+5%容差适用于任何电压设置VDD GPO电源标称设置3.3未用时,必须设为13VVDD GPO容差5%容差适用于任何电压设置电流消耗VDDx,休眠模式所有输入电流之和VDD GPO50A无负载指参数中多功能引脚的单个功能时,只会列出引脚名称中与规格相关的部分。要了解多功能引脚的仝部引脚名称,请参见引脚配置和功能描述"部分。Rev. D Page 7 of 36AD9361功耗一vDD_ INTERFACE表2 VDD INTERFACE=12V参数最小值典型值最大值件测试条件/注释休眠模式加电,器件禁用1RX 1TX DDRLTE10单端口2.9mA3072MHz数据时钟,CMOS双端∏2.7mA1536MHz数据时钟,CMOSLTE20双端口5.2mA3072MH数据时钟,CMOS2RX, 2TX, DDRLTE双端口1.3DA768MHz数据时钟,CMOSLTE10单端口4.6mA6144MHz数据时钟,CMOS双端口5.0mA3072MHz数据时钟,CMOSLTE20双端口8.2mA6144MHz数据吋钟,CMOSGSM双端口0.21.08MHz数据时钟,CMOSWiMAX 8.75双端口3.320MHz数据时钟,CMOSWiMAX 10单端口TDD RX0.5mA224MHz数据时钟,CMOSTDD TX3.6A224MHz数据时钟,CMOSFDD3.8448MHz数据吋钟,CMOSWiMAX 20双端口FDD6.7mA448MHz数据时钟,CMOS表3vDD| NTERFACE=18V参数最小值典型值最大值件测试条件/注释休眠模式加电,器件禁用1RX 1X DDRLTE10单端口4.5A3072MHz数据时钟,CMOS双端口4.1mA1536MHz数据时钟,CMOSLTE20双端口8.0mA30.72MHz数据时钟,CMoS2RX.2TX DDRLTE双端口2.0mA768MHz数据时钟,CMOSLTET0单端口8.0A6144MHz数据时钟,CMOS双端口7.5mA3072MHz数据时钟,CMOSLTE20双端口140mA6144MHz数据时钟,CMOSGSM双端口0.3A1.08MHz数据时钟,CMOSWiMAX 8.75双端口5.0MA20MHz数据时钟,CMOSRev. d Page 8 of 36AD9361参数最小值典型值最大值件测试条件/注释WiMAX 10单端口I DD RX07mA224MHz数据时钟,CMOTDD TX5.6mA224MHz数据时钟,CMOSFDD60448MHz数据时钟,CMOSWIMAX 20双端口FDD107mA448MHz数据时钟,CMOSP-P5675mV差分输出140mA240MHz数据时钟,LVDS300m差分输出350A240MHz数据时钟,LVDS450mV差分输出470mA240MH数据时钟,LVDS表4 VDD INTERFACE=25V参数最小值典型值最大值件测试条件/注释休眠模式150A加电,器件禁用1RX, 1TX DDRLTE10单端口6.5mA3072MHz数据时钟,CMOS双端口6.0A1536MHz数据时钟,CMOSLTE20双端口115nA3012MHz数据时钟,CMOS2RX, 2TX DDRLTE双端口30mA768MHz数据时钟,CMOsLTE10单端口115mA6144MHz数据时钟,CMOS双端口A3072MHz数据时钟,CMOSLTE20双端口2006144MHz数据时钟,CMOSGSM双端口0.5A1.08MHz数据时钟,CMOWiMAX 8.75双端口7.3A20MHz数据时钟,CMOSWIMAX 10单端TDD RX224MHz数据时钟,CMOSTDDTX8.0mA224MHz数据时钟,CMOSFDD8.7mA448MHz数据时钟,CMOSWiMAX 20双端口FDD153A448MHz数据时钟,CMOSP-P5675mV差分输出26.0240MHz数据时钟,LVDS300mV差分输出450mA240MHz数据时钟,LVDS450mV差分输出mA240MHz数据时钟,LVDSRev. D Page 9 of 36AD9361功耗一—vDDD1P3_DG和vDDA(全部13V电源组合)表5800MHz,TDD模式参数最小值典型值最大值件测试条件/注释1 RX5MHz带宽180nA连续RX10MHz带宽210A迕续RX20MHz带宽260MA连续RX2RX5MHz带宽265MA连续RX10MHz带宽315A连续RX20MHz带宽405mA连续RX1TX5MHz带宽dBl340nA连续TX-27dBmA连续TX10MHz带宽7 dBm360A连续TX27 dBm220MA连续TX20MHz带宽7 dBm400连续TX-27 dBm250mA连续TX5MHz带宽7 dBm550连续TX27 dB260连续TX10MHz带宽7 dBmA连续TX2 dBm310A连续TX20MHz带宽7 dBm660nA连续TX-27 dBm370mA连续TXRev. D Page 10 of36
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MATLAB在卡尔曼滤波器中应用的理论与实践Kalman
MATLAB在卡尔曼滤波器中应用的理论与实践KalmanKALMAN FILTERINGTheory and Practice Using MATLABThird editionMOHINDER S GREWALCalifornia State University at FullertonANGUS P. ANDREWSRockwell Science Center (retired)WILEYA JOHN WILEY & SONS, INC. PUBLICATIONCopyright 2008 by John Wiley sons, Inc. All rights reservedPublished by John Wiley sons, InC, Hoboken, New JerseyPublished simultaneously in CanadaNo part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or byany means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permittedunder Section 107 or 108 of the 1976 United States Copyright Act, without either the prior writtenpermission of the Publisher, or authorization through payment of the appropriate per-copy fee to theCopyright Clearance Center, Inc, 222 Rosewood Drive, Danvers, MA 01923,(978)750-8400, fax(978)750-4470,oronthewebatwww.copyright.com.RequeststothePublisherforpermissionshouldbe addressed to the Permissions Department, John Wiley Sons, Inc, lll River Street, Hoboken, NJ07030,(201)748-6011,fax(201)748-6008,oronlineathttp://www.wiley.com/go/permissionimit of liability Disclaimer of Warranty: While the publisher and author have used their best efforts inpreparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability orfitness for a particular purpose. No warranty may be created or extended by sales representatives orwritten sales materials. The advice and strategies contained herein may not be suitable for your situationYou should consult with a professional where appropriate. Neither the publisher nor author shall be liablefor any loss of profit or any other commercial damages, including but not limited to special, incidentalconsequential, or other damagesFor general information on our other products and services or for technical support, please contact ourCustomer Care Department within the United States at(800)762-2974, outside the United States at(317)572-3993 or fax(317)572-4002Wiley also publishes its books in a variety of electronic formats. Some content that appears in print maynot be available in electronic format. For more information about wiley products, visit our web site atwww.wiley.comLibrary of Congress Cataloging- in-Publication DataGrewal. Mohinder sKalman filtering: theory and practice using MATLAB/Mohinder S. GrewalAngus p. andrews. 3rd edIncludes bibliographical references and indexISBN978-0-470-17366-4( cloth)1. Kalman filtering. 2. MATLAB. I. Andrews, Angus P. II. TitleQA402.3.G69520086298312—dc22200803733Printed in the United States of america10987654321CONTENTSPrefaceAcknowledgmentsXIIIList of abbreviationsXV1 General Information1.1 On Kalman Filtering1.2 On Optimal Estimation Methods, 51. 3 On the notation Used In This book 231. 4 Summary, 25Problems. 262 Linear Dvnamic Systems2. 1 Chapter focus, 312.2 Dynamic System Models, 362. 3 Continuous Linear Systems and Their Solutions, 402.4 Discrete Linear Systems and Their Solutions, 532.5 Observability of Linear Dynamic System Models, 552.6 Summary, 61Problems. 643 Random Processes and Stochastic Systems3.1 Chapter Focus, 673.2 Probability and random Variables (rvs), 703.3 Statistical Properties of RVS, 78CONTEN3.4 Statistical Properties of Random Processes(RPs),803.5 Linear rp models. 883.6 Shaping Filters and State Augmentation, 953.7 Mean and Covariance propagation, 993.8 Relationships between Model Parameters, 1053.9 Orthogonality principle 1143.10 Summary, 118Problems. 1214 Linear Optimal Filters and Predictors1314.1 Chapter Focus, 1314.2 Kalman Filter. 1334.3 Kalman-Bucy filter, 1444.4 Optimal Linear Predictors, 1464.5 Correlated noise Sources 1474.6 Relationships between Kalman-Bucy and wiener Filters, 1484.7 Quadratic Loss Functions, 1494.8 Matrix Riccati Differential Equation. 1514.9 Matrix Riccati Equation In Discrete Time, 1654.10 Model equations for Transformed State Variables, 1704.11 Application of Kalman Filters, 1724.12 Summary, 177Problems. 1795 Optimal Smoothers5.1 Chapter Focus, 1835.2 Fixed-Interval Smoothing, 1895.3 Fixed-Lag Smoothing, 2005.4 Fixed-Point Smoothing, 2135.5 Summary, 220Problems. 226 Implementation Methods2256. 1 Chapter Focus, 2256.2 Computer Roundoff, 2276.3 Effects of roundoff errors on Kalman filters 2326.4 Factorization Methods for Square-Root Filtering, 2386. 5 Square-Root and UD Filters, 2616.6 Other Implementation Methods, 2756.7 Summary, 288Problems. 2897 Nonlinear Filtering2937.1 Chapter Focus, 2937.2 Quasilinear Filtering, 296CONTENTS7.3 Sampling Methods for Nonlinear Filtering, 3307.4 Summary, 345Problems. 3508 Practical Considerations3558.1 Chapter Focus. 3558.2 Detecting and Correcting Anomalous behavior, 3568.3 Prefiltering and Data Rejection Methods, 3798.4 Stability of Kalman Filters, 3828. 5 Suboptimal and reduced- Order Filters, 3838.6 Schmidt-Kalman Filtering, 3938.7 Memory, Throughput, and wordlength Requirements, 4038.8 Ways to Reduce Computational requirements 4098.9 Error Budgets and Sensitivity Analysis, 4148.10 Optimizing Measurement Selection Policies, 4198.11 Innovations analysis, 4248.12 Summary, 425Problems. 4269 Applications to Navigation4279.1 Chapter focus, 4279.2 Host vehicle dynamics, 4319.3 Inertial Navigation Systems(INS), 4359. 4 Global Navigation Satellite Systems(GNSS), 4659.5 Kalman Filters for GNSS. 4709.6 Loosely Coupled GNSS/INS Integration, 4889.7 Tightly Coupled GNSS /INS Integration, 4919. 8 Summary, 507Problems. 508Appendix A MATLAB Software511A 1 Notice. 511A 2 General System Requirements, 511A 3 CD Directory Structure, 512A 4 MATLAB Software for Chapter 2, 512A. 5 MATLAB Software for Chapter 3, 512A6 MATLAB Software for Chapter 4, 512A. 7 MATLAB Software for Chapter 5, 513A 8 MATLAB Software for Chapter 6, 513A 9 MATLAB Software for Chapter 7, 514A10 MATLAB Software for Chapter 8, 515A 11 MATLAB Software for Chapter 9, 515A 12 Other Sources of software 516CONTENAppendix b A Matrix Refresher519B. 1 Matrix Forms. 519B 2 Matrix Operations, 523B 3 Block matrix Formulas. 527B 4 Functions of Square Matrices, 531B 5 Norms. 538B6 Cholesky decomposition, 541B7 Orthogonal Decompositions of Matrices, 543B 8 Quadratic Forms, 545B 9 Derivatives of matrices. 546Bibliography549Index565PREFACEThis book is designed to provide familiarity with both the theoretical and practicalaspects of Kalman filtering by including real-world problems in practice as illustrativeexamples. The material includes the essential technical background for Kalman filter-ing and the more practical aspects of implementation: how to represent the problem ina mathematical model, analyze the performance of the estimator as a function ofsystem design parameters, implement the mechanization equations in numericallystable algorithms, assess its computational requirements, test the validity of resultsitor the filteThetant attributes ofthe subject that are often overlooked in theoretical treatments but are necessary forapplication of the theory to real-world problemsIn this third edition, we have included important developments in the implemen-tation and application of Kalman filtering over the past several years, including adaptations for nonlinear filtering, more robust smoothing methods, and develelopingapplications in navigationWe have also incorporated many helpful corrections and suggefrom ourreaders, reviewers, colleagues, and students over the past several years for theoverall improvement of the textbookAll software has been provided in MatLab so that users can take advantage ofits excellent graphing capabilities and a programming interface that is very close tothe mathematical equations used for defining Kalman filtering and its applicationsSee Appendix a for more information on MATLAB softwareThe inclusion of the software is practically a matter of necessity because Kalmanfiltering would not be very useful without computers to implement it. It provides aMATLAB is a registered trademark of The Mathworks, IncEFACEbetter learning experience for the student to discover how the Kalman filter works byobserving it in actionThe implementation of Kalman filtering on computers also illuminates some of thepractical considerations of finite-wordlength arithmetic and the need for alternativealgorithms to preserve the accuracy of the results. If the student wishes to applywhat she or he learns, then it is essential that she or he experience its workingsand failings--and learn to recognize the differenceThe book is organized as a text for an introductory course in stochastic processes atthe senior level and as a first-year graduate-level course in Kalman filtering theory andapplicationIt can also be used for self-instruction or for purposes of review by practi-cing engineers and scientists who are not intimately familiar with the subject. Theorganization of the material is illustrated by the following chapter-level dependencygraph, which shows how the subject of each chapter depends upon material in otherchapters. The arrows in the figure indicate the recommended order of study. Boxesabove another box and connected by arrows indicate that the material represented bythe upper boxes is background material for the subject in the lower boxAPPENDIX B: A MATRIX REFRESHERGENERAL INFORMATION2. LINEAR DYNAMIC SYSTEMSRANDOM PROCESSES AND STOCHASTIC SYSTEMS4. OPTIMAL LINEAR FILTERS AND PREDICTORS5. OPTIMAL SMOOTHERS6. IMPLEMENTATIONMETHODS7. NONLINEAR8. PRACTICAL9. APPLICATIONSFILTERINGCONSIDERATIONSTO NAVIGATIONAPPENDIX A: MATLAB SOFTWAREChapter l provides an informal introduction to the general subject matter by wayof its history of development and application. Chapters 2 and 3 and Appendix b coverthe essential background material on linear systems, probability, stochastic processesand modeling. These chapters could be covered in a senior-level course in electricalcomputer, and systems engineeringChapter 4 covers linear optimal filters and predictors, with detailed examples ofapplications. Chapter 5 is a new tutorial-level treatment of optimal smoothing
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