基于INS/GNSS紧耦合组合的逐步诱导式欺骗检测算法研究

传统惯性辅助GNSS欺骗信号检测方法对小于纯惯导误差漂移的逐步拉偏不敏感。针对这一问题,提出了一种基于INS/GNSS紧耦合组合的逐步诱导式欺骗信号检测方法。基于短时间内纯惯性导航结果和短时间惯导系统位置误差传播模型,利用惯导提供的位置和速度对伪距和伪距率时间序列进行预测估算,并结合伪距、伪距率实际测量结果,分别构造位置/伪距和速度/伪距率时间序列模型做参数拟合。基于真实信号得到的模型参数都是由惯导系统误差造成的,具有一致性;而基于逐步诱导式欺骗信号得到的模型参数还与欺骗策略的设定、载体飞行轨迹的观测以及干扰源的位置有关,具有不一致性。通过对比模型参数可判别欺骗信号的存在,对于真实信号,采用紧耦合组合导航修正INS输出;对于欺骗信号,继续惯性导航并采取相应措施。最后,根据逐步诱导式欺骗原理进行实验仿真,验证了算法的可行性和有效性。     

Italian low cost GNSS/INS system suitable for mobile mapping

The first studies for the mobile mapping and creation of a vehicle for this kind of research was carried out by Canadian Researchers in the 1980s. Since then, these vehicles have been widely employed in several applications (road cadastre maps, terrestrial photogrammetry, road sign recognition, etc.) for both commercial and research purposes throughout the world. Many GNSS/INS vehicles which can be equipped in different ways with one or more GPS, inertial sensors, and one or several cameras, have been realized. A characteristic shared by most of these devices concerns the high costs of the sensors, of the realization, and of the maintenance. For this reason, a GNSS/INS system, that is suitable for any vehicle, made up of low-cost devices (two GPS receivers, an INS, and a camera rigidly placed on a metallic bar), have been designed and built by our research group. Two tests run at different velocities have been carried out to evaluate the reliability of the system. After a presentation of the system, the differences that were witnessed during the application of these calibration methods are explained herein.     

部分模糊度固定方法在GNSS/INS紧组合中的应用研究

针对动态环境下GNSS/INS导航定位模糊度固定难的问题,提出了一种基于部分模糊度固定的GNSS/INS紧组合导航定位算法,通过选择模糊度的最优子集进行固定,并利用实测车载实验进行了算法验证.实验结果表明:在开阔环境下,基于部分模糊度固定的GNSS/INS紧组合与基于全模糊度固定的GNSS/INS紧组合算法的定位精度相...     

基于场景检测的城市环境GNSS/INS组合定位方法研究

城市复杂环境下,采用GNSS/INS组合定位方法能有效提升GNSS信号部分或全部被遮挡情况下的车辆连续定位能力。GNSS信号受遮挡的程度具有随机性和突变性,给GNSS/INS组合算法的架构设计和参数设置带来了挑战。基于此,设计了一套基于场景检测的GNSS/INS组合定位策略与方法,提出了以多星GNSS观测量的八类特征为输入,利用支持向量机分类思想将定位场景分为室外开阔、室外遮挡和室内三种类型,并建立了与之相适应的组合滤波量测误差估计模型,进而实现了GNSS/INS组合定位。实测数据验证表明,提出的方法能够有效提升车辆组合定位精度。     

GNSS/INS深组合技术研究进展与展望

在GNSS/INS组合导航领域,深组合是最深层次的组合方式,随着航空、航天、军事等应用对导航系统性能要求的提升,深组合技术逐步成为国内外研究的重点。通过对GNSS/INS深组合的技术起源与结构发展过程的梳理,总结出当前对深组合概念理解的两种立场。按照接收机环路跟踪结构与信息处理方式不同,将深组合结构分为标量深组合、相干矢量深组合以及非相干矢量深组合3种类型,其中相干矢量深组合又可以分为级联式和集中式两种结构。综述了国内外深组合技术的研究现状并指出了当前研究中存在的问题,最后结合实际应用需求对深组合的发展进行了展望。     

基于铱星/INS组合定位技术在船舶中的应用研究

GNSS拒止环境下惯性/GNSS组合导航系统的性能会严重恶化,通过利用并提取机会信号中的有用观测量,可以实现机会信号和惯性系统的联合动态定位。提出了利用铱星/INS组合定位技术实现船舶的动态定位。首先深入研究了铱星的信号体制,建立了利用铱星瞬时多普勒频移进行定位的算法模型;然后,提出了利用基于扩展卡尔曼滤波(EKF)技术的铱星机会信号与INS组合定位算法;最后,通过船舶航行实测数据对所提算法进行了试验验证。结果表明,提出的利用铱星机会信号和INS组合定位方法可以有效改善无GNSS信号条件下的INS定位精度,在GNSS信号拒止环境下解决了船舶定位问题,具有重要的研究意义和实用价值。     

复杂城市环境下GNSS/INS轻轨轨道中线精密测量方法CSCD

在城市轻轨线路的中线精密测量中,传统的基于GNSS的测量方式往往受高楼、站台、上跨桥及声屏障等复杂环境信号遮挡影响,甚至无法接收到GNSS信号,难以得到满足精度要求的轨道中线坐标;而基于全站仪的测量方式需建立轨道控制网,作业效率低下。为了满足城市轻轨中线精密测量高精度和高效率的需求,采用GNSS/INS轨道中线精密测量方法,基于Kalman滤波将惯导、GNSS数据进行融合,并根据轨道检测仪在轨道上不发生垂向和侧向运动的特点,采用运动约束算法,以提升组合导航系统测量精度。同时设计了基于新息滤波的抗差检测,以剔除定位质量差的GNSS数据。通过将里程计比例因子误差增广到状态向量的方式进行参数估计,以减小里程计测量误差。通过集成惯导、GNSS、里程计等传感器的轨检小车,采集城市轻轨轨道测量数据。经数据处理和对比分析,在GNSS信号较差的复杂场景下能够得到厘米级的轻轨轨道中线坐标,且测量效率大大提升。     

基于对偶四元数的INS/GPS组合导航算法研究

在基于对偶四元数的捷联惯导解算方法的基础上,推导了以惯性系作为导航系的惯导误差方程,在此基础上设计了卡尔曼滤波组合导航算法。通过激光惯导跑车采集数据,进行了仿真分析,试验结果表明,该组合导航算法能有效的消除惯导累积的速度误差和位置误差,相比于目前广泛应用的INS/GPS组合导航算法,本文描述了INS/GPS组合导航的另一种实现方式,获得了相当的精度,具有一定的工程应用价值。     

激光捷联惯性/卫星组合导航系统基本原理及应用情况

激光捷联惯性/卫星组合导航系统是国外飞机上普遍采用的一种导航设备,但在国内飞机上的应用则刚刚起步。本文简要介绍了激光捷联惯性/卫星组合导航系统的基本原理及应用情况。     

Cubature Kalman filter with closed-loop covariance feedback control for integrated INS/GNSS navigation

Cubature Kalman Filter (CKF) offers a promising solution to handle the data fusion of integrated nonlinear INS/GNSS (Inertial Navigation System/Global Navigation Satellite System) navigation. However, its accuracy is degraded by inaccurate kinematic noise statistics which originate from disturbances of system dynamics. This paper develops a method of closed-loop feedback covariance control to address the above problem of CKF. In this method, the posterior state and its covariance are fed back to the filtering process to constitute a closed-loop structure for CKF covariance propagation. Subsequently, based on the maximum likelihood principle, a control scheme of the prior state covariance is established by using the feedback state and covariance within an estimation window and further adopting a proportional coefficient to amplify the feedback terms in recent time steps for the full use of new information to reflect actual system characteristics. Since it does not directly use kinematic noise covariance, the proposed method can effectively avoid the adverse impact of inaccurate kinematic noise statistics on filtering solutions. Further, it can also guarantee the prior state covariance to be positive semi-definite without involving extra measures. The efficacy of the proposed method is validated by simulations and experiments for integrated INS/GNSS navigation.     

Balloon gravimetry using GPS and INS

Measurement of the horizontal components of gravity at altitude using balloon-borne instrumentation consisting of a Global Positioning System (GPS) receiver and a strapdown inertial navigation system (INS) is discussed. GPS data are to be used primarily to determine the total inertial acceleration of the balloon, while the INS accelerometers sense all nongravitational accelerations. A covariance analysis based on the Kalman filter shows that conventional gravity estimation from GPS-aided INS data is possible only if external attitude updates are also available. An alternative technique is explored that attempts to estimate at least part of the gravitational spectrum without modeling the gravity disturbance as a state variable or relying on external attitude updates, while, at the same time, admitting uncorrected (long-wavelength) attitude errors. Simulations based on a model for typical balloon motion are used to discuss this possibility     

INS/GNSS组合导航系统空中快速对准方法

针对机载惯性/全球导航卫星系统(INS/GNSS)组合导航系统地面静基座对准时间较长、航向对准精度较低以及惯导空中故障重启后无法快速得到精确姿态信息重新进入导航状态等问题,提出一种快速初始对准方法。该对准方法基于惯性导航比力方程,利用GNSS的定位、测速信息与惯性测量组件(IMU)的输出信息解算载体姿态信息,并结合遗传-牛顿算法与求和自回归滑动平均(ARIMA)模型卡尔曼滤波信号降噪技术提高姿态信息的解算精度。基于实测飞行数据的解算验证了该方法的有效性、对准精度以及在实际工程应用中的优越性。     

惯性／卫星组合导航开发平台的可视化仿真和实现

对惯性/卫星组合导航开发平台的可视化仿真及其实现进行了研究。该开发平台采用Visual++6.0语言进行编程,可进行实时导航动画显示,对惯性导航、GNSS及多种组合模态进行仿真运行,其结构和参数可由操作者根据实际情况选择或自行设定;特别针对不同的应用对象,可灵活地设置航迹和航路点,因此有较高的应用价值和实用意义,不失为设计组合导航系统的有力工具,在实际应用中对惯性/卫星组合导航系统研制和设计具有前瞻性和指导性。同时,模块化设计使该软件中的核心算法已方便地移植应用于实际工程组合导航系统中,收到了很好的效果。     

Fuzzy corrections in a GPS/INS hybrid navigation system

A new concept regarding GPS/INS integration, based on artificial intelligence, i.e. adaptive neuro-fuzzy inference system (ANFIS) is presented. The GPS is used as reference during the time it is available. The data from GPS and inertial navigation system (INS) are used to build a structured knowledge base consisting of behavior of the INS in some special scenarios of vehicle motion. With the same data, the proposed fuzzy system is trained to obtain the corrected navigation data. In the absence of the GPS information, the system will perform its task only with the data from INS and with the fuzzy correction algorithm. This paper shows, using Matlab simulations, that as long as the GPS unavailability time is no longer than the previous training time and for the scenarios a priori defined, the accuracy of trained ANFIS, in absence of data from a reference navigation system, is better than the accuracy of stand-alone INS. The flexibility of model is also analyzed.     

GPS/INS integration on the Standoff Land Attack Missile (SLAM)

The Standoff Land Attack Missile (SLAM) is a worldwide, all-weather, precision-strike weapon system deployed from carrier-based aircraft. In the primary mode of operation, target location and other mission data are generated from intelligence sources available on the aircraft carrier and loaded into the missile prior to aircraft takeoff. After missile launch, the SLAM inertial navigation system (INS) guides the missile along the planned trajectory. Updating the missile INS from the Global Positioning System (GPS) during flight provides precise midcourse navigation and enhances target acquisition by accurate, on-target pointing of the SLAM Maverick seeker. The GPS/INS avionics and software integration used for SLAM are described in detail, along with some of the design tradeoffs that led to the approach. The avionics configuration integrates the Harpoon midcourse guidance unit, which includes a strapdown inertial sensor package and digital processor, with a Rockwell-Collins single-channel, sequential GPS receiver processor unit (RPU), a derivative of the GPS phase-III user equipment. In addition to the GPS receiver elements the RPU contains the navigation processor, which executes the SLAM navigation, Kalman filter algorithms, and other guidance algorithms including seeker pointing. Flight-test results of the SLAM GPS-aided INS are also included     

基于Starlink机会信号/INS的组合导航方法

针对全球卫星导航系统(GNSS)因频点单一、落地功率低、易受电磁干扰以及存在覆盖较差区域等潜在的被拒止或被干扰导致的导航系统性能降低甚至失效的问题,提出了一种基于星链(Starlink)机会信号融合惯性导航系统(INS)的飞行器动态组合导航方法。首先分析了星链信号体制,建立了基于星链星座卫星下行机会信号的瞬时多普勒定位观测模型,设计了一种基于频率细分的快速最大似然多普勒频率估计方法,然后建立了基于扩展卡尔曼滤波(EKF)的Starlink机会信号/INS的组合导航模型,并对该导航方法进行了实验及分析。结果表明,该方法可为飞行器提供长航时、连续、高精度的导航。动态飞行情况下,该方法可实现平均优于25 m的三维定位精度和平均优于0.1 m/s的速度估计精度,比相同观测时间下的惯导精度提高了1～2个数量级,显著提高了飞行器的导航精度,可为战略导航提供方法和技术支撑。     

低轨星座/惯导紧组合导航技术研究CSCD

现有低轨(LEO)卫星导航研究主要以低轨星座独立导航定位和增强全球卫星导航系统(GNSS)导航定位为主,对低轨卫星和惯性导航系统(INS)组合导航技术研究较少。本文面向应用较小规模低轨星座资源实现米级定位精度的需求,提出了一种低轨星座/惯导紧组合导航方法,系统性地分析了不同规模低轨星座、不同精度级别惯导器件以及不同导航信号播发频度下组合导航定位的性能,并利用构建的仿真试验系统进行了低轨星座/惯导紧组合导航方法的仿真试验验证。试验结果表明,相较于低轨星座独立导航,低轨星座/惯导紧组合导航在星座不满足四重覆盖时仍能达到米级定位精度,并且在低轨星座规模较小和导航信号播发频度较低时,惯导测量精度对组合导航定位精度影响明显。研究结果表明,在利用低轨卫星进行导航时,通过引入惯性观测辅助低轨卫星导航,可有效提高导航效能和精度,为低轨星座和导航信号播发方式设计带来更多的选择。     

Rapid development of tightly-coupled GPS/INS systems

This paper addresses the question: “Why aren't tightly-coupled OPS/INS systems everywhere, on aircraft, ships and land vehicles?” Two barriers to the widespread use are cited. One is the high cost of the INS, and the other is the cost and complexity of tightly-coupled OPS/INS integration. One of those two barriers has recently been diminished drastically with the development of a standardized software package for tightly-coupled integration. In the past, only the largest corporations have been able to pay the initial development cost for tightly-coupled OPS/INS integration, usually with funding from a large defense program. Using the new software package, integration and van test can be accomplished in a matter of days, and this has been demonstrated with field trials. The package is intended primarily for small companies that otherwise would not be able to build tightly-coupled OPS/INS systems at all. What would have been a prohibitive 3- or 4-man year development effort is reduced to a few man weeks. To accomplish an integration, the system integrator has to find a way, through serial interfaces or by some other means, to get the INS measurements of acceleration (accumulated velocity change ΔV) and attitude rate (accumulated angle change Δ&thetas;) into a processor, along with the raw data of a GPS receiver. He also has to find a way to time tag the INS ΔV, Δ&thetas; with GPS time. The rest of tightly-coupled OPS/INS integration is predominately accomplished in the standardized software package. That leaves the cost of the INS as the only remaining barrier to the very widespread use of OPS/INS, and invites new development of low cost inertial sensors. The focus of this paper is on the software package, and how it achieves standardization and ease of use while retaining the flexibility to produce optimal results with a variety of INS and GPS receiver types     

A novel optimal data fusion algorithm and its application for the integrated navigation system of missile

For Inertial Navigation System(INS)/Celestial Navigation System(CNS)/Global Navigation Satellite System(GNSS) integrated navigation system of the missile, the performance of data fusion algorithms based on the Cubature Kalman Filter(CKF) is seriously degraded when there are non-Gaussian noise and process-modeling errors in the system model. Therefore, a novel method is proposed, which is called Optimal Data Fusion algorithm based on the Adaptive Fading maximum Correntropy generalized high-degree...     

GPS/BDS/INS tightly coupled integration accuracy improvement using an improved adaptive interacting multiple model with classified measurement update

An Extended Kalman Filter (EKF) is commonly used to fuse raw Global Navigation Satellite System (GNSS) measurements and Inertial Navigation System (INS) derived measurements. However, the Conventional EKF (CEKF) suffers the problem for which the uncertainty of the statistical properties to dynamic and measurement models will degrade the performance. In this research, an Adaptive Interacting Multiple Model (AIMM) filter is developed to enhance performance. The soft-switching property of Interacting Multiple Model (IMM) algorithm allows the adaptation between two levels of process noise, namely lower and upper bounds of the process noise. In particular, the Sage adaptive filtering is applied to adapt the measurement covariance on line. In addition, a classified measurement update strategy is utilized, which updates the pseudorange and Doppler observations sequentially. A field experiment was conducted to validate the proposed algorithm, the pseudorange and Doppler observations from Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) were post-processed in differential mode. The results indicate that decimeter-level positioning accuracy is achievable with AIMM for GPS/INS and GPS/BDS/INS configurations, and the position accuracy is improved by 35.8%, 34.3% and 33.9% for north, east and height components, respectively, compared to the CEKF counterpart for GPS/BDS/INS. Degraded performance for BDS/INS is obtained due to the lower precision of BDS pseudorange observations.