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。

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。

GPS与INS的组合定位技术研究

组合定位技术是一种新的导航技术,能够使多个导航系统实现信息的互补性和协同性。其中,GPS和惯导结合是一种较为理想的组合定位系统,而深度融合模式是目前GPS和惯导(INS)联合使用的最佳方式,因此,对深度融合模式的研究显得尤为重要。

复杂环境下GPS+BDS-3 PPP/INS紧组合算法性能分析

针对城市复杂环境下精密单点定位(PPP)连续高精度定位受限的问题,本文基于北斗三号全球卫星导航系统(BDS-3)与全球定位系统(GPS)双系统,利用PPP与惯性导航系统(INS)紧组合算法来改善城市复杂环境下定位性能。通过构建GPS+BDS-3双系统PPP/INS紧组合滤波模型,分别对GPS PPP、GPS+BDS-3 PPP、GPS PPP/INS紧组合、GPS+BDS-3PPP/INS紧组合4种方案在城区开阔、复杂环境下的定位、测速、定姿性能进行了分析和评估。实验结果表明,开阔环境下PPP/INS紧组合相比PPP定位精度略有提升;而在复杂环境下PPP/INS紧组合可显著解决PPP定位结果连续性和有效性较差的问题;引入BDS-3后,PPP/INS紧组合导航性能进一步提升,GPS+BDS-3 PPP/INS紧组合相比GPS PPP/INS紧组合,在东、北、天方向上,开阔环境下定位精度分别提升18.5%、32.7%、43.2%,复杂环境下定位精度分别提升35.9%、49.1%、56.5%。

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.

DESIGN AND REALIZATION OF SINS/TWO-ANTENNA GPS INTEGRATED NAVIGATION SYSTEM

The strapdown inertial navigation system （SINS）/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phase model. The extended Kalman filtering is proposed. And the hardware composition and connection are designed to simulate the SINS/two-antenna GPS integrated navigation system. Results show that the performances of the system, the precision of the navigation and the positioning, the reliability and the practicability are im proved.

Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

Accuracy improvement of GPS/MEMS-INS integrated navigation system during GPS signal outage for land vehicle navigation

To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive （FAR） model- ing, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the tra- ditional adaptive neuro-fuzzy inference system （ANFIS） method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS （SCANFIS） combined with the extended Kalman filter （EKF） is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the effi- ciency of the proposed methods.

A Quaternion Scaled Unscented Kalman Estimator for Inertial Navigation States Determination Using INS/GPS/Magnetometer Fusion

This Inertial Navigation System (INS), Global Positioning System (GPS) and fluxgate magnetometer technologies have been widely used in a variety of positioning and navigation applications. In this paper, a low cost solid state INS/GPS/Magnetometer integrated navigation system has been developed that incorporates measurements from an Inertial Navigation System (INS), Global Positioning System (GPS) and fluxgate magnetometer (Mag.) to provide a reliable complete navigation solution at a high output rate. The body attitude estimates, especially the heading angle, are fundamental challenges in a navigation system. Therefore targeting accurate attitude estimation is considered a significant contribution to the overall navigation error. A better estimation of the body attitude estimates leads to more accurate position and velocity estimation. For that end, the aim of this research is to exploit the magnetometer and accelerometer data in the attitude estimation technique. In this paper, a Scaled Unscented Kalman Filter (SUKF) based on the quaternion concept is designed for the INS/GPS/Mag integrated navigation system under large attitude error conditions. Simulation and experimental results indicate a satisfactory performance of the newly developed model.

DGPS/INS Data Fusion for Land Navigation

The interest for land navigation has increased for the recent years. With the advent of the Global Position System (GPS) we have now the ability to determine the absolute position anywhere on the globe. The problem is that the GPS systems work well only in open environments with no overhead obstructions and they are subject to large unavoidable errors when the reception from some of the satellites are blocked. This occurs frequently in urban environments, forests and tunnels. GPS systems require at least four “visible” satellites to maintain a good position fix. In many situations in which higher level of accuracy is required, the navigation cannot be achieved by GPS alone. This paper discusses the design of a reliable multisensor fusion algorithm using GPS and Inertial Navigation System in order to decrease the implementation cost of such systems on land vehicles. The major contribution of this paper is in the definition of the possible developments and research axes in land navigation.

Three-time rapid transfer alignment method of SINS/GPS navigation system of high-speed marine missile

The transfer alignment of SINS/GPS navigation system of a high-speed marine missile was investigated. With the help of the big acceleration of a high-speed missile, the transfer alignment was changed into a three-time alignment. The azimuth alignment was coarsely finished in 10s in the first time alignment, the horizontal alignment was accurately and rapidly finished in the second time alignment, and the azimuth alignment was accurately finished in the third time alignment. Because the second time alignment and the third time alignment were finished by GPS after the missile was launched, the horizontal alignment and the second azimuth alignment got rid of the influence of the warship body flexibility deforming. The precision and rapidity of the horizontal alignment were prominently increased due to the vertical launch of the marine missile with the big acceleration. Simulation verifies the effectiveness of the proposed alignment method.

Ground Alignment of Inertial Navigation System with the Aid of GPS Signals

Due to the poor observability of INS ground self alignment, only horizontal alignment is satisfied. This paper proposes using GPS double difference carrier phase as external reference to improve the observability of INS self alignment. Through observability analysis and computer simulation, it is demonstrated that the azimuth alignment is as quick as horizontal alignment, the accuracy of horizontal alignment is improved, and the gyros errors can be estimated quickly and precisely.

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.

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。

基于GPS/INS的无人机物流配送路径控制研究

随着科技的发展,通过利用无线电遥控设备和自备的程序控制装置操纵的无人驾驶的低空飞行器运载包裹,自动送达目的地,其优点主要在于解决偏远地区的配送问题,提高配送效率,同时减少人力成本。本文以GPS/INS技术为基础,通过深入分析无人机的运动轨迹,指出无人机物流配送路径的识别与控制方法,有利于提高无人机的速度和加速度,增加识别精度。

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.

INS-GNSS Integrated Navigation Algorithm Based on TransGAN

With the rapid development of autopilot technology,a variety of engi-neering applications require higher and higher requirements for navigation and positioning accuracy,as well as the error range should reach centimeter level.Single navigation systems such as the inertial navigation system(INS)and the global navigation satellite system(GNSS)cannot meet the navigation require-ments in many cases of high mobility and complex environments.For the purpose of improving the accuracy of INS-GNSS integrated navigation system,an INS-GNSS integrated navigation algorithm based on TransGAN is proposed.First of all,the GNSS data in the actual test process is applied to establish the data set.Secondly,the generator and discriminator are constructed.Borrowing the model structure of generator transformer,the generator is constructed by multi-layer transformer encoder,which can obtain a wider data perception ability.The generator and discriminator are trained and optimized by the production countermeasure network,so as to realize the speed and position error compensa-tion of INS.Consequently,when GNSS works normally,TransGAN is trained into a high-precision prediction model using INS-GNSS data.The trained Trans-GAN model is emoloyed to compensate the speed and position errors for INS.Through the test analysis offlight test data,the test results are compared with the performance of traditional multi-layer perceptron(MLP)and fuzzy wavelet neural network(WNN),demonstrating that TransGAN can effectively correct the speed and position information when GNSS is interrupted,with the high accuracy.

因子图框架下里程计辅助GNSS/INS组合导航算法

在复杂观测环境下,GNSS/INS组合导航系统的GNSS信号易受干扰从而导致INS独立导航精度迅速下降。针对上述问题,本文基于因子图的里程计辅助GNSS/INS组合导航算法,利用里程计观测信息结合非完整性约束构建航向速度约束方程,同时采用能多次线性化计算和多次迭代的因子图优化方法进行参数估计。实际车载试验解算结果表明,在GNSS信号良好时,基于因子图方法比滤波方法具有更快的收敛时间,收敛速度提高了近10倍;在GNSS信号发生中断时,添加里程计辅助后组合导航系统在东向和北向分别提升了83%和89%。与传统的滤波融合手段相比,本文采用因子图优化后在东向和北向的定位精度分别有63%、70%的改善。

GPS/VISNAV integrated relative navigation and attitude determination system for ultra-close spacecraft formation flying

For the improvement of accuracy and better fault-tolerant performance, a global position system （GPS）/vision navigation （VISNAV） integrated relative navigation and attitude determination approach is presented for ultra-close spacecraft formation flying. Onboard GPS and VISNAV system are adopted and a federal Kalman filter architecture is used for the total navigation system design. Simulation results indicate that the integrated system can provide a total improvement of relative navigation and attitude estimation performance in accuracy and fault-tolerance.

GPS Signal Short-Term Propagation Characteristics Modeling in Urban Areas for Precise Navigation Applications

GPS navigation signal includes vital information such as orbital parameters, clock error coefficients etc. This received signal which is extremely weak is affected by several errors during its propagation and is of the order of 10-16 W. The noise floor of this signal is 400 times higher than the transmitted signal. The situation becomes much worse particularly when the GPS receiver is located at urban areas where the multipath effect is predominant in the code and carrier phase measurements. GPS usage is not limited to the aircraft en-route navigation and missile guidance where the user receives the satellite signals from the open sky. At the present time, it has become an essential utility in the car navigation, mobile phones, surveying and aircraft landing application. The signal propagation characteristics particularly the short-term variations severely affect the quality, availability and continuity of the system. In this paper, short-term propagation characteristics of GPS signal are modeled and analyzed. Short-term variations are mainly due to multipath reflections and Doppler shift which degrades the quality of received signal particularly in urban environments. The variation of signal quality with respect to user velocity is observed using Rayleigh and Rician fading models.