基于VB-EKF的GPS/INS松组合导航定位算法

针对应用在无人机(Unmanned Aerial Vehicle,UAV)中的全球定位系统/惯性导航系统(GPS/INS)松组合导航非线性系统受到外界噪声干扰导致量测噪声在滤波时不断变化,从而造成滤波精度下降等问题,提出一种变分贝叶斯扩展卡尔曼滤波(VB-EKF)算法。该算法利用EKF(Extended Kalman Filter)将非线性系统中的状态函数和量测函数展开为线性方程,并将两个不同的导航系统数据进行融合,避免了单系统导航定位发散的问题。考虑到组合系统中量测噪声的时变特性,引入变分贝叶斯算法进行改进,有效解决了系统滤波精度下降问题。仿真结果表明,VB-EKF较EKF算法可有效提高滤波稳定性,进而提高系统导航定位精度。

DESIGN & REALIZATION ON GPS/INS INTEGRATED NAVIGATION SYSTEM

This paper deals with the research of the GPS/INS integrated navigation system applying Extended Kalman Filter, which involves integrated principles, scheme and technology of combining with real INS and GPS receiver data. Emphases are placed on the modeling of system errors and implementation of the integrated system. Both loose and tightly coupled GPS/INS integrated in schemes are analyzed. On the basis of our experience accumulated in the research of GPS/INS for many years, the GPS/INS integrated navigation developing system is developed. It can be put into efficient and economic use in the study and design of integrated navigation system. It plays an important role in the aeronautical and astronautical fields in China. This system is not only a computer aided design software but also a semi physical simulation system by obtaining real INS and GPS receiver data. So the key software unit of the developing system could be conveniently transferred into practical engineering software in actual hardware integrated system. The application of this system shows that the design ideas and integrated scheme of this development system are successful, and can achieve good navigation result.

GPS/BDS组合导航系统的精密单点定位模型

为了改善单卫星导航系统由于卫星数量较少,导致定位误差高的问题,设计全球定位系统(GPS)/北斗卫星导航系统(BDS)组合导航系统的精密单点定位模型:线性组合处理GPS与BDS的伪距和载波相位观测值,并构建GPS/BDS组合导航系统的组合观测值;接下来利用协方差成形自适应卡尔曼滤波方法,对组合导航系统导航过程中的卫星钟差、电离层延迟等误差实施滤波;再利用滤波处理后组合导航系统的广播星历,获取卫星轨道以及钟差;然后利用经验模型修正对流层延迟,获取相位观测值与伪距的综合改正数;最后利用综合改正数修正组合导航系统的观测方程,构建精密单点定位模型。实验结果表明,GPS/BDS组合导航系统采用所构建模型进行精密单点定位,不同方向定位误差均低于10 cm,证明了提出模型的有效性。

GPS/INS组合导航终端的全向位置驱离算法研究

随着微惯性导航系统技术的发展,越来越多的无人平台装备了GPS/INS组合导航终端并具备了一定的抗欺骗能力,但现有的卫星导航欺骗方法难以满足对欺骗目标任意方向的位置驱离需求。为解决这一问题,提出了一种GPS/INS组合导航终端的全向位置驱离算法,可用于对非法无人平台管控的场景。该方法以卫星欺骗信号的设计为突破口,首先分析了卫星导航欺骗对组合导航位置和状态参数的影响,接着将卫星导航欺骗对组合导航状态参数的影响量作为求取欺骗信号的约束条件,进而确定位置驱离所需卫星欺骗信号的欺骗量,接着利用确定的欺骗量建立全向位置驱离模型,最终利用建立的模型生成对应的欺骗信号实现对组合导航终端的全向位置驱离任务。试验验证了本文设计的算法能够实现对组合导航终端360°任意方向的位置驱离。

基于GPS差分定位的变电站电磁干扰位置识别

由于变电站中各种设备的增加,会导致大量的电磁干扰产生,严重影响变电站的正常运行。为解决这一问题,设计一种基于全球定位系统(Global Positioning System,GPS)差分定位技术的变电站电磁干扰位置识别方法。设计电磁干扰采集平台,实现变电站电磁干扰信号的采集,并进行消噪处理与时域滤波处理。通过GPS差分定位技术实现变电站电磁干扰信号的位置识别。测试结果表明,该方法的单一干扰源平均定位误差低于20 cm,能够实现多干扰源的定位,同时对于较远距离的多干扰源有着较低的定位误差。

Adaptive Federal Kalman Filtering for SINS/GPS Integrated System

A new adaptive federal Kalman filter for a strapdown integrated navigation system/global positioning system (SINS/GPS) is given. The developed federal Kalman filter is based on the trace operation of parameters estimation's error covariance matrix and the spectral radius of update measurement noise variance-covariance matrix for the proper choice of the filter weight and hence the filter gain factors. Theoretical analysis and results from simulation in which the SINS/GPS was compared to conventional Kalman filter are presented. Results show that the algorithm of this adaptive federal Kalman filter is simpler than that of the conventional one. Furthermore, it outperforms the conventional Kalman filter when the system is undertaken measurement malfunctions because of its possession of adaptive ability. This filter can be used in the vehicle integrated navigation system.

Hybrid Kalman and unscented Kalman filters for INS/GPS integrated system considering constant lever arm effect

In inertial navigation system(INS) and global positioning system(GPS) integrated system, GPS antennas are usually not located at the same location as the inertial measurement unit(IMU) of the INS, so the lever arm effect exists, which makes the observation equation highly nonlinear. The INS/GPS integration with constant lever arm effect is studied. The position relation of IMU and GPS's antenna is represented in the earth centered earth fixed frame, while the velocity relation of these two systems is represented in local horizontal frame. Due to the small integration time interval of INS, i.e. 0.1 s in this work, the nonlinearity in the INS error equation is trivial, so the linear INS error model is constructed and addressed by Kalman filter's prediction step. On the other hand, the high nonlinearity in the observation equation due to lever arm effect is addressed by unscented Kalman filter's update step to attain higher accuracy and better applicability. Simulation is designed and the performance of the hybrid filter is validated.

INTEGRATED GPS/INS OF PSEUDO-RANGE DELTA-RANGE SEM I-PHYSICAL SIMULATION SRESEARCH

In orderto furtherstudy theperform ance oftightly integrated navigation system ofGPS/ INS, a sem i-physicalsim ulation oftightly coupled system has been done based on the data gathered from the experim entof integrated system ofGPSand INS. The closed-loop Kalm an Filter and U-D discom pose algorithm have been used. The sim ulation results associated to four integrated m odels of pseudo-range, delta-range, pseudo-range and delta-range alternation, and pseudo-range and delta- range synthesis have been provided, and the actualeffects of variously integrated m odels have been analyzed. The results show that the pseudo-range and delta-range synthesis coupled m odelis the m osteffective to im provethe coupled system perform anceand the individualdelta-rangecoupled m od- elhad betterbe avoided in application.

A Map-Matching Algorithm forGPS/DR Integrated Navigation Systems Basedon Dempster-Shafer Evidence Reasoning

GPS (Global Positioning System) has been widely used in car navigation systems. Most car navigation systems estimate the car position from GPS and DR (dead reckoning). However, the unknown GPS noise characteristic and the unbounded DR accumulation of errors over time make the position information with undesirable position errors. The map matching can improve the position accuracy and availability of the vehicular position system. In this paper, general principle of map matching is investigated according to segmentation and feature extraction, and a map matching algorithm based on D-S (Dempster-Shafer) evidence reasoning for GPS integrated navigation system is proposed, which can find the exact road on which a car moves. For the experiments, a car navigation system is developed with some sensors and the field test demonstrates the effectiveness and applicability of the algorithm for the car location and navigation.

Integrated Data Processing Method for GPS and INS Field Test over Rocky Mountain

The method of integrated data processing for GPS and INS(inertial navigation system) field test over the Rocky Mountains using the adaptive Kalman filtering technique is presented. On the basis of the known GPS outputs and the offset of GPS and INS, state equations and observations are designed to perform the calculation and improve the navigation accuracy. An example shows that with the method the reliable navigation parameters have been obtained.

APPLYINGSUCCESSIVEORTHOGONALIZATIONDECENTRALIZEDKALMANFILTERTOGPS／INSINTEGRATEDNAVIGATIONSYSTEM

The Successive Orthogonalization Decentralized Kalman Filter (SODKF ) is a new method which is used for large system state estimation. It can be applied not only to large system decentralization, but also to precision realization at approximately the same level of the global filter, thus, making possible the engineering operation as well as shortening the computing time. This paper discusses the principles and features of SODKF when used in GPS/INS integrated navigation system. The system will be firstly divided into three subsystems and then corrected in both open and closed loops. The system simulation results by two integrated patterns show that SODKF is efficient and realizable. While the three subsystems are simulated in series, the computing speed doubles that of the global system. In addition, its optimal estimating precision remains unchanged. It can be concluded from this paper that large integrated navigation systems with GPS, INS, Terrain Match, Loran C, Doppler Radar and Radio Altimeter can be made more efficient by this multi subsystem of navigation.

Position and attitude determination by integrated GPS/SINS/TS for feed support system of FAST

This paper presents a new measurement system based on integration method that can provide all-weather dependability and higher precision for the measurement of FAST's feed support system.The measurement system consists of three types of measuring equipments,and a processing software with the core data fusion algorithm.The Strapdown Inertial Navigation System(SINS)can autonomously measure the position,speed and attitude of the carrier.Its own shortcoming is that the measurement data diverge rapidly over time.SINS must combine the Global Positioning System(GPS)and the Total Station(TS)to obtain high-precision measurement data.The Kalman filtering algorithm is adopted for the integration measurement system,which is an optimal algorithm to estimate the measurement errors.A series of tests are carried out to evaluate the performance.For the feed cabin,the maximum RMS of the position is 14.56 mm,the maximum RMS of the attitude is 0.095,these values are less than 15 mm and 0.1°as the precision for measuring the feed cabin.For the Stewart manipulator,the maximum RMS of the position is 2.99 mm,the maximum RMS of the attitude is 0.093°,these values are less than 3 mm and 0.1°as the precision for measuring the Stewart manipulator.As a result,the new measurement meets the requirement of measurement precision for FAST's feed support system.

Low-Cost GPSIINS Integrated Land-Vehicular Navigation System for Harsh Environments Using Hybrid Mamdani AFISIKF Model

Nowadays, GPS （global positioning system） receivers are aided by INS （inertial navigation systems） to achieve more precision and stability in land-vehicular navigation. KF （Kalman filter） is a conventional method which is used for the navigation system to estimate the navigational parameters, when INS measurements are fused with GPS data. However, new generation of INS, which relies on MEMS （micro-electro-mechanical systems） based low-cost IMUs （inertial measurement units） for the land navigation systems, decreases the accuracy and the robustness of navigation system due to their inherent errors. This paper provides a new method for fusing the low-cost IMU and GPS measurements. The proposed method is based on KF aided by AF1S （adaptive fuzzy inference systems） as a promising solution to overcome the mentioned problems. The results of this study show the efficiency of the proposed method to reduce the navigation system errors in comparison with KF alone.

GPS与INS组合的便携式轨道类游乐设施轨迹研究

为检测轨道类游乐设施运行速度和轨迹,利用安卓智能手机内置的惯性导航系统(INS)、卫星导航系统(GPS)进行轨道类游乐设施运行加速度、角速度等数据进行采集分析;采用捷联惯性导航系统,建立轨道类游乐设施轨迹姿态解算模型,以卡尔曼滤波器为基础,在Matlab软件中构建松耦合模式的组合导航系统,对INS输出的速度、位置数据进行校正;在试验场地对游乐设施数据进行采集并进行处理,基于UG NX二次开发实现轨道游乐设施姿态信息显示、轨迹拟合。实验结果验证了使用安卓智能手机内置的INS\GPS组合导航系统采集轨道类游乐设施数据、运行轨迹的可行性,弥补了轨道类游乐设施姿态和轨迹测量相关研究的不足。

GPS+BDS与UWB组合定位的Helmert方差分量估计方法

为了提高室内外过渡区定位精度,本文采用GPS+BDS与UWB组合定位,建立GPS+BDS与UWB组合定位模型,并针对GPS与BDS星座结构的不同,以及UWB与GNSS观测值残差差异较大的情况,采用Helmert方差分量估计法分别对GPS、BDS、UWB进行定权;最后通过动态室内外过渡区试验组合模型进行精度验证。结果表明,基于GNSS+UWB定位系统,采用Helmert方差分量方法,在东、北、天3个方向的定位精度均获得了显著提高,静态条件下提高幅度约为20%,动态条件下提高幅度约为10%。

Integrated Design and Accuracy Analysis of Star Sensor and Gyro on the Same Benchmark for Satellite Attitude Determination System

As an important sensor in the navigation systems,star sensors and the gyro play important roles in spacecraft attitude determination system.Complex environmental factors are the main sources of error in attitude determination.The error influence of different benchmarks and the disintegration mode between the star sensor and the gyro is analyzed in theory.The integrated design of the star sensor and the gyro on the same benchmark can effectively avoid the error influence and improves the spacecraft attitude determination accuracy.Simulation results indicate that when the stars sensor optical axis vectors overlap the reference coordinate axis of the gyro in the same benchmark,the attitude determination accuracy improves.

Novel approach to GPS/SINS integration for IMU alignment

Strapdown inertial navigation system（SINS） requires an initialization process that establishes the relationship between the body frame and the local geographic reference.This process,called alignment,is generally used to estimate the initial attitude angles.This is possible because an accurate determination of the inertial measurement unit（IMU） motion is available based on the measurement obtained from global position system（GPS）.But the update frequency of GPS is much lower than SINS.Due to the non-synchronous data streams from GPS and SINS,the initial attitude angles may not be computed accurately enough.In addition,the estimated initial attitude angles may have relatively large uncertainties that can affect the accuracy of other navigation parameters.This paper presents an effective approach of matching the velocities which are provided by GPS and SINS.In this approach,a digital high-pass filter,which implements a pre-filtering scheme of the measured signal,is used to filter the Schuler cycle of discrete velocity difference between the SINS and GPS.Simulation results show that this approach improves the accuracy greatly and makes the convergence time satisfy the required accuracy.

Modified Observation Model in Tightly-Coupled INS/GPS Integration

The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation accuracy and therefore navigation accuracy.Additionally,the conventional observation model（COM）used by the filter may be divergent,which would result into some terrible accuracies of INS/GPS integration navigation in some cases.To improve the navigation accuracy,the linearization accuracy of the COM still needs further improvement.To deal with this issue,the observation model is modified with the linearization of the range and range rate equations in this paper.Compared with COM,the modified observation model（MOM）further considers the difference between the real user position and the position calculated by SINS.To verify the advantages of this model,INS/GPS integrated navigation simulation experiments are conducted with the usage of COM and MOM respectively.According to the simulation results,the positions（velocities）calculated using COM are divergent over time while the others using MOM are convergent,which demonstrates the higher linearization accuracy of MOM.

基于GPS/IMU数据融合的无人车高精度控制方法研究

针对无人车在高速行驶过程中转向动作延迟的问题,提出了一种基于GPS/IMU数据融合的无人车方向提前调整的方法,以提高无人车自主导航的精确性和稳定性。首先,利用GPS获取无人车的位置和方向角信息,建立二维平面运动模型,使无人车在到达预定目标点之前做出方向调整决策,再利用IMU测量车身偏航角并配合PID控制器实现转向控制。验证实验表明:该方法使无人车的行驶轨迹更加贴合预设轨迹,同时规避了因转角突增而翻车的风险;另外,通过提前控制并抵消微控制器程序执行所需时间,确保无人车在实际到达目标点时,可精准快速地做出转向动作,提升了无人车的控制精度和稳定性。

基于车载平台的飞行管理系统DR/GPS导航试验验证

飞行管理系统是民用飞机的关键航空电子系统。飞行管理系统制造商有责任对飞行管理系统开展大量的试验以验证飞行管理系统功能和性能的符合性。考虑数字验证的局限性和飞行试验验证的巨大代价,本文利用车载平台开展飞行管理系统综合导航功能的验证,试验结果表明设计的飞行管理系统DR/GPS导航方法能够满足95%的飞行时间水平方向达到0.1海里的导航精度要求,为实际的飞行测试提供了试验数据参考。