毕业论文（设计）GPS∕INS紧组合导航系统(英文).pdf

摘要由于全球定位系统（GPS 与惯性导航系统（INS 具有很好的相互补偿特性，其 二者组合形成的组合导航系统具有精度高、更新率高、抗干扰性强等优点。在GPS信号可用时，GPS/INS组合导航系统通过GPS观测值更新INS的位置和速 度输出值，可以抑制位置、速度误差发散，因此GPS/INS组合是一种有效的组合方式。目 前，GPS/INS组合导航系统已经广泛应用于各种导航任务中。本论文详细论述了 GPS/INS 紧组合导航系统基本原理，并通过对四阶段卫星运载火箭（SLV 真实轨迹进行仿真分析,验证了紧组合导航系统的优良特性。紧组合导航系统的设计是以GPS接收机和惯导系统为基础的。由于在开始进行研 究时，缺乏GPS接收机和惯导系统的数据，一切工作必须从零开始。首先需要设计轨迹 发生器，它能针对给定轨迹计算出IMU的实时数据，通过选择合适的IMU误差模型，可 以进行仿真验证惯导算法。然后设计了基于此IMU数据的捷联惯导算法，可以计算出轨 迹的运行时间、位置、速度和姿态，该捷联惯导系统将用于与GPS组合。紧组合导航系 统要求使用GPS的原始数据伪距、伪距、伪距率进行计算，所以必须设计GPS软件 接收机得到这些原始数据。本文详细设计了一个GPS软件接收机，并用于组合导航系统 进行了验证。最后,本文设计了 GPS/INS紧组合导航系统并对应用于四阶段SLV系统的 组合导航系统特性进行了分析。关键词：GPS/INS组合导航系统，紧组合导航系统，轨迹发生器，惯性测量单元，捷联惯性导航系统，GPS软件接收机，GPSIF信号仿真器，SLV导航，卡尔曼滤波ABSTRACTComplementary characteristics of Global Positioning System(GPS)and Inertial Navigation System(INS)urge to fuse both navigation systems in a way to improve the navigation system with limiting the navigation errors and make it available for continuous and uninterrupted.The integration of GPS and INS is an efficient way of limit the INS derived position,velocity and attitude errors by using the GPS measurements as update to the position and velocity whenever it is available.There are numerous GPS/INS integrated navigation systems depending upon the specific mission and requirements.In this thesis tightly coupled GPS/INS integrated navigation system is discussed in detail and a case study of four stages SLV has been done to check the performance of tightly coupled integrated navigation system.Tightly coupled integrated navigation system requires a baseline of GPS receiver realization and inertial navigation system.Since starting of this work,there was no baseline so it was required to work from scratch.So initially an Inertial Sensors Simulator has been designed in order to get the real IMU data for a given trajectory then using an appropriate IMU error model one can check the performance of inertial navigation algorithm.A Strapdown Inertial Navigation algorithm was developed to acquire the runtime position,velocity and attitude information based upon the IMU data provided to it.This Strapdown Inertial Navigation simulator was then used to integrate with GPS.Since the tightly coupled GPS/INS integrated navigation system needs the raw measurement of GPS i.e.,pseudorange,delta pseudorange&pseudorange rate,so it was also required to make a software GPS receiver to take out the raw measurement fbr integrated navigation system.A detailed software GPS receiver was then designed and verified for using it in integrated navigation system.In the end a tightly coupled GPS/INS integrated navigation system was described and performance of integrated navigation fbr four stages SLV was analyzed.Key words:GPS/INS integrated navigation,tightly coupled integrated navigation,inertial sensors simulator,IMU,strapdown inertial navigation,SINS,software GPS receiver,IF GPS signal simulator,SLV navigation,Kalman FilterTABLE OF CONTENTS摘要.iABSTRACT.IITABLE OF CONTENTS.IllLIST OF FIGURES.VILIST OF TABLES.IXCHAPTER 1 INTRODUCTION.11.1 GLOBAL POSITIONING SYSTEM.11.2 INERTIAL NAVIGATION SYSTEM.21.3 INTEGRATED NAVIGATION SYSTEM.21.4 THESIS OUTLINE.2CHAPTER 2 INERTIAL SENSORS SIMULATOR.42.1 COORDINATE FRAMES.52.1.1 Earth Centered Inertial(I)Frame.62.1.2 Earth Centered Earth Fixed(E)Frame.62.1.3 Geographic(G)Frame.62.1.4 Navigation(N)Frame.62.1.5 Body(B)Frame.72.2 TRAJECTORY GENERATION.72.3 INERTIAL SENSORS DATA GENERATION SOFTWARE.92.3.1 Angular Velocity.102.3.2 Specific Force.122.4 ELLIPSOID MASS ATTRACTION GRAVITY.122.5 RESULT.14CHAPTER 3 STRAPDOWN INERTIAL NAVIGATION SIMULATOR.163.1 CALCULATION OF ATTITUDES.163.2 CALCULATION OF VELOCITIES AND POSITION.173.3 SIMULATOR VALIDATION.183.4 RESULT.193.5 SENSOR MODELS.193.6 RESULT.213.7 DESIGNED TRAJECTORY.213.7.1 Spin-Cone trajectory for coning compensation algorithm evaluation.21CHAPTER 4 GPS RECEIVER REALIZATION.234.1 GPS MAJOR SEGMENTS.234.1.1 Space Segment.234.1.2 Control Segment.244.1.3 User Segment.254.2 GPS SIGNAL.254.2.1 Signal Structure.254.2.2 GPS C/A Code Signal Structure.284.2.3 C/A Code Generator.29III4.2.4 C/A Code Auto-correlation and Cross-correlation.324.3 SOFTWARE GPS RECEIVER.334.3.1 Front End.334.3.2 Acquisition.344.3.3 Tracking.364.4 NAVIGATION DATA.494.4.1 Navigation Bits.504.4.2 Tracking Outputs to Navigation Data.514.4.3 Matching the Subframe&Parity Check.524.4.4 Obtaining Ephemeris Data.534.4.5 Position Calculation from Ephemeris Data.554.5 PSEUDORANGE.574.6 RESULT.58CHAPTER 5 DESIGN&IMPLEMENTATION OF SOFTWARE GPS RECEIVER.605.1 GPS IF SIGNAL SIMULATOR.605.1.1 GPS Signal Simulator Design Parameters.605.1.2 GPS Signal Simulator Implementation.615.2 SIMULATED SIGNAL RESULT.625.2.1 Acquisition Result.635.2.2 Tracking Result.665.3 VERIFICATION OF SOFTWARE GPS RECEIVER WITH REAL GPS DATA 675.3.1 Obtaining Real GPS Data.675.3.2 Necessary Hardware.685.3.3 Obtained GPS Signal Result.695.3.4 Acquisition Result.705.3.5 Tracking Result.725.3.6 Decoded Navigation Bits&Matching of Subframe-1.745.3.7 Calculation of Pseudorange.755.4 RESULT.76CHA PTER 6 INTEGRATED NAVIGATION SYSTEM.776.1 INTRODUCTION.776.2 ARCHITECTURES OF GPS/INS INTEGRATION.786.2.1 Loosely Coupled Integration.786.2.2 Tightly Coupled Integration.796.2.3 Ultra Tightly Coupled Integration.796.2.4 Loosely Coupled Vs.Tightly Coupled Integration.806.3 GPS RECEIVER.816.3.1 GPS Satellite Constellation.826.3.2 GPS Measurements.836.3.3 GPS Measurement Model.836.4 INS NAVIGATION EQUATIONS.926.4.1 INS Error Equations.936.5 KALMAN FILTER FORMULATION.966.6 TIGHTLY COUPLED GPS/INS INTEGRATED NAVIGATION FOR SLV.97IV6.6.1 SLV Trajectory&IMU Outputs.986.6.2 Result of Navigation Filter using Chinese Method.1016.6.3 Result of Navigation Filter using Ohlmeyer Method.1046.6.4 System Performance.107CHAPTER 7 CONCLUSION&FUTURE WORK.1107.1 CONCLUSION.1107.1.1 Inertial Sensors Simulator.1107.1.2 Strapdown Inertial Navigation Simulator.1107.1.3 GPS IF Signal Simulator.1107.1.4 Software GPS Receiver.Ill7.1.5 Tightly Coupled GPS/INS Integrated Navigation System.1127.2 FUTURE WORK.112GLOSSARY.114REFERENCES.117ACKNOWLEDGEMENT.120VLIST OF FIGURESFIGURE 1：INERTIAL FRAME(I),EARTH FRAME(E)&GEOGRAPHIC FRAME(G).6FIGURE 2：GEOGRAPHIC FRAME(G)&NAVIGATION FRAME(N).7FIGURE 3：BODY FRAME(B).7FIGURE 4：TRAJECTORY GENERATION RESULT.9FIGURE 5：GEOCENTRIC&NAVIGATION FRAMES.14FIGURE 6：OUTPUT OF ACCELEROMETERS.15FIGURE 7：OUTPUT OF GYROS.15FIGURE 8：SIMULATOR VALIDATION.18FIGURE 9：ERROR IN ATTITUDES AND VELOCITY.19FIGURE 10：IMU ERRORS.20FIGURE 11：SPIN-CONE GEOMETRY.22FIGURE 12：GPS MAJOR SEGMENTS.23FIGURE 13：GPS SPACE SEGMENT.24FIGURE 14：GPS CONTROL SEGMENT.24FIGURE 15：LI SIGNAL STRUCTURE.26FIGURE 16:SIMPLIFIED GPS SATELLITE NAVIGATION PACKAGE.26FIGURE 17：THE EFFECT OF BPSK MODULATION OF THE LI CARRIER WAVE WITH THE C/A CODE AND THENAVIGATION DATA FOR ONE SATELLITE.27FIGURE 18：GPS CARRIER MODULATION SIGNALS.28FIGURE 19：GPS SIGNAL STRUCTURE IN FREQUENCY DOMAIN.29FIGURE 20：C/A CODE GENERATOR.30FIGURE 21：AUTOCORRELATION AND CROSS-CORRELATION GOLD CODES OF GPS.33FIGURE 22：A TYPICAL GPS LI FRONT END.34FIGURE 23：DFT-BASED ACQUISITION METHOD.35FIGURE 24：THE BLOCK DIAGRAM OF THE COMBINED DLL&PLL TRACKING LOOP.37FIGURE 25：A BASIC PHASE-LOCKED LOOP.38FIGURE 26：DELAY LOCK LOOP.40FIGURE 27：CODE CORRELATION PHASES：(A)REPLICA CODE 1/2-CHIP EARLY,(B)REPLICA CODE 1/4-CHIPEARLY,(C)REPLICA CODE ALIGNED,AND(D)REPLICA CODE 1/4-CHIP LATE.41FIGURE 28：CODE DISCRIMINATOR OUTPUT VERSUS REPLICA CODE OFFSET.42FIGURE 29：BASIC GPS RECEIVER TRACKING LOOP BLOCK DIAGRAM.43FIGURE 30：COSTAS LOOP USED TO TRACK THE CARRIER WAVE.43VIFIGURE 31：BLOCK DIAGRAMS OF：(A)FIRST-,(B)SECOND-,AND(C)THIRD-ORDER ANALOG LOOP FILTERS.45 FIGURE 32：BLOCK DIAGRAMS OF：(A)ANALOG,(B)DIGITAL BOXCAR,AND(C)DIGITAL BILINEARTRANSFORM INTEGRATORS.47FIGURE 33：BLOCK DIAGRAMS OF(A)FIRST-,(B)SECOND-,AND(C)THIRD-ORDER DIGITAL LOOP FILTERSEXCLUDING LAST INTEGRATOR(THE NCO).48FIGURE 34：THE BLOCK DIAGRAM OF A COMPLETE TRACKING CHANNEL IN THE SOFTWARE GPS RECEIVER.49FIGURE 35：GPS FRAME FORMAT.50FIGURE 36：GPS DATA MESSAGE.51FIGURE 37：TELEMETRY(TLM)WORD FORMAT.52FIGURE 38：HAND-OVER-WORD(HOW)WORD FORMAT.52FIGURE 39：RELATIVE PSEUDORANGE.58FIGURE 40：SIMULATED GPS SIGNAL IN TIME DOMAIN.62FIGURE 41：FFT OF SIMULATED SIGNAL(WITHOUT NOISE).63FIGURE 42：ACQUISITION RESULT-SATELLITE#1.63FIGURE 43：ACQUISITION RESULT-SATELLITE#16.64FIGURE 44：ACQUISITION RESULT-SATELLITE#21.64FIGURE 45：ACQUISITION RESULT-SATELLITE#29.65FIGURE 46：DLL&PLL DISCRIMINATOR OUTPUT.66FIGURE 47：CORRELATORS OUTPUT.66FIGURE 48：NAVIGATION BITS OUTPUT.67FIGURE 49：HARDWARE COMPONENTS NEEDED TO OBTAIN REAL GPS DATA.68FIGURE 50:REAL GPS DATA IN TIME DOMAIN(2-BITS QUANTIZATION).69FIGURE 51：FFT OF REAL GPS DATA.69FIGURE 52：ACQUISITION RESULT WITH REAL GPS DATA(SATELLITE#7).70FIGURE 53：ACQUISITION RESULT WITH REAL GPS DATA(SATELLITE#21).70FIGURE 54：ACQUISITION RESULT WITH REAL GPS DATA(SATELLITE#26).71FIGURE 55：ACQUISITION RESULT WITH REAL GPS DATA(SATELLITE#29).71FIGURE 56：DLL&PLL DISCRIMINATOR OUTPUT WITH REAL GPS DATA.72FIGURE 57：CORRELATORS OUTPUT WITH REAL GPS DATA.73FIGURE 58：NAVIGATION BITS OUTPUT WITH REAL GPS DATA.73FIGURE 59：DECODED NAVIGATION BITS.74FIGURE 60：TLM WORD OF SUBFRAME-1.74VIIFIGURE 61：GPS/INS SYSTEM WITH LOOSELY COUPLED INTEGRATION.78FIGURE 62：GPS/INS SYSTEM WITH TIGHTLY COUPLED INTEGRATION.79FIGURE 63：GPS/INS SYSTEM WITH ULTRA-TIGHTLY COUPLED INTEGRATION.80FIGURE 64：KALMAN FILTER CYCLE.96FIGURE 65：SLV VELOCITY PROFILE.98FIGURE 66:SLV ATTITUDES PROFILE.99FIGURE 67：OUTPUT OF ACCELEROMETERS(UN-ERRONEOUS).99FIGURE 68：OUTPUT OF GYROS(UN-ERRONEOUS).100FIGURE 69：OUTPUT OF ACCELEROMETERS(ERRONEOUS).100FIGURE 70：OUTPUT OF GYROS(ERRONEOUS).101FIGURE 71：SLV-GPS/INS LATITUDE(CHINESE METHOD).101FIGURE 72：SLV-GPS/INS LONGITUDE(CHINESE METHOD).102FIGURE 73：SLV-GPS/INS HEIGHT(CHINESE METHOD).102FIGURE 74：SLV-GPS/INS VELOCITY-VX(CHINESE METHOD).103FIGURE 75：SLV-GPS/INS VELOCITY-VY(CHINESE METHOD).103FIGURE 76：SLV-GPS/INS VELOCITY-VZ(CHINESE METHOD).104FIGURE 77：SLV-GPS/INS LATITUDE(OHLMEYER METHOD).105FIGURE 78：SLV-GPS/INS LONGITUDE(OHLMEYER METHOD).105FIGURE 79:SLV-GPS/INS HEIGHT(OHLMEYER METHOD).105FIGURE 80：SLV-GPS/INS VELOCITY-VX(OHLMEYER METHOD).106FIGURE 81：SLV-GPS/INS VELOCITY-VY(OHLMEYER METHOD).106FIGURE 82：SLV-GPS/INS VELOCITY-VZ(OHLMEYER METHOD).107VIIILIST OF TABLESTABLE 1：EXAMPLE OF FLIGHT PROFILE DATA.8TABLE 2：IMU ERROR CHARACTERISTICS.19TABLE 3：BINARY REPRESENTATION OF DIGITAL SIGNAL.27TABLE 4：CODE PHASE ASSIGNMENTS.31TABLE 5:COMMON DELAY LOCK LOOP DISCRIMINATOR.42TABLE 6：COMMON COSTAS LOOP DISCRIMINATOR.44TABLE 7：LOOP FILTER CHARACTERISTICS.46TABLE 8：EPHEMERIS PARAMETERS IN SUBFRAME-1.53TABLE 9：EPHEMERIS PARAMETERS IN SUBFRAME-2.54TABLE 10：EPHEMERIS PARAMETERS IN SUBFRAME-3.54TABLE 11：GPS SIGNAL SIMULATOR PARAMETER.62TABLE 12：SIMULATED SIGNAL ACQUISITION RESULT.65TABLE 13：REAL GPS SIGNAL ACQUISITION RESULT.72TABLE 14：COARSE RELATIVE PSEUDORANGE(TIME).75TABLE 15：GPS CONSTELLATION PARAMETERS.108TABLE 16:GPS RECEIVER ERRORS.108IX北京航空航天大学硕士学位论文CHAPTER 1 INTRODUCTIONPosition and attitude information is an important component in surveying,navigation,control and guidance of moving platforms.Traditionally,this information has been provided by an Inertial Navigation System(INS),a self-contained measuring unit which provides position,velocity and attitude information at a high output rate.The system,however,has time-dependent error characteristics when operated in a stand-alone mode,without in-flight alignment.In contrast,GPS provides accurate position,velocity and time data without any impact of mission length or time since update.The main factor limiting the use of GPS is the requirement fbr line-ofsight between the receiver antenna and the satellites.Additional shortcomings include the low data output rate and the need to deploy more than one GPS antenna in order to obtain attitude information.Integrated GPS/INS systems have been developed in order to overcome the inherent drawbacks of each system.1.1 Global Positioning SystemThe NAVSTAR Global Positioning System(GPS)is a satellite navigation system developed as a US Department of Defense joint program in 1973.It became fully operational in 1995 with a minimum of 24 satellites orbiting in six planes at an altitude of approximately 11,000 nmi.GPS is a ranging system;it provides accurate time-ofarrival measurements fbr users to calculate position in three dimensions.GPS accuracy for civilian users is on the order of 10 m.If used differentiallyrequiring a reference station at a known location,GPS accuracies can be better than 10 cm.As an external navigation aid,GPS error sources include signal path delay through the ionosphere and troposphere,satellite clock and ephemeris errors.Multipath and receiver clock errors contribute further to a GPS users error budget.GPS users benefit from very precise,long-term position and velocity information that is available worldwide.However,users may experience short-term GPS outages if there is signal interference,or if the view to satellites is blocked.1Introduction1.2 Inertial Navigation SystemInertial navigation is based on the implementation of Newtons laws of motion.Inertial Navigation Systems(INS)determines position,velocity and attitude by measuring and integrating a users acceleration and angular velocity.Inertial sensors i.e.,accelerometers and gyroscopes were first used for guidance and navigation in the early twentieth century.Inertial navigators are self-contained,non-jammable systems,providing information at high data rates and bandwidth.All INS position and velocity information degrades with time;its accuracy is limited by the quality of its inertial sensors and knowledge of the Earths gravity field and rate.1.3 Integrated Navigation SystemIn integrated navigation system,the short term accuracy of the INS and the long term stability and accuracy of the GPS directly complement each other.GPS is fairly accurate but is available at slower data rate.The INS data has low noise and is generated at high data rates,but is subjected to biases and drifts that cause the errors to grow with time.This suggests an integration approach that utilizes the INS for accurate navigation and guidance,with the GPS used to periodically calibrate the INS and keep its errors bounded.A Kalman Filter is usually used for data fusion of the GPS and INS sensors,and provides a mean of estimating the navigation errors for later correction.Thus,design of the navigation filter is crucial to the performance of the INS.1.4 Thesis OutlineThe remaining parts of this thesis consist of the following chapters:Chapter 2 describes the Inertial Sensors Simulator design and implementation used for generating the IMU data for the given trajectory.Chapter 3 states Strapdown Inertial Navigation Algorithm,used to verify the Inertial Sensors Simulator also provides a basic platform for developing the integrated navigation system.Chapter 4 outlines the GPS receiver realization.This chapter includes the GPS signal structure,software GPS receiver front end,acquisition,t