Analysis of upgraded GPS internal Kalman filter

GPS receivers with provisions for inertial navigation system (INS) aiding are designed with internal Kalman filters that model generic INSs and process the basic GPS pseudorange and deltarange (range-rate) data to produce an output of inertially-smoothed, “GPS-derived” position and velocity. These Kalman filters model only the basic nine INS errors (position, velocity, and tilt) and do not model any INS gyro or accelerometer errors. It was found that a significant performance improvement could be achieved under conditions of degraded GPS satellite availability by augmenting this type of filter with the six INS gyro and accelerometer bias errors. It is, therefore, recommended that serious consideration be given to incorporating these states into the design of the GPS internal Kalman filter     

一种速度匹配动基座传递对准的方法

介绍了一种速度匹配的动基座传递对准的方法。主子惯导均采用平台系统的指北导航方式,推导了平台对准误差方程,利用主子惯导的速度差信息构建控制回路对子惯导平台的水平失准角进行反馈修正,同时用卡尔曼滤波器估计出方位失准角,从而实现子惯导的初始对准。建立了相应的模型,对该传递对准方法进行了仿真验证,在仿真时考虑了杆臂效应的影响,加入了杆臂效应的算法补偿机制。仿真结果数据跟理论推导基本吻合,验证了方法的可行性。     

Wavelet de-noising for IMU alignment

Inertial navigation system (INS) is presently used in several applications related to aerospace systems and land vehicle navigation. An INS determines the position, velocity, and attitude of a moving platform by processing the accelerations and angular velocity measurements of an inertial measurement unit (IMU). Accurate estimation of the initial attitude angles of an IMU is essential to ensure precise determination of the position and attitude of the moving platform. These initial attitude angles are usually estimated using alignment techniques. Due to the relatively low signal-to-noise ratio of the sensor measurement (especially for the gyroscopes), the initial attitude angles may not be computed accurately enough. In addition, the estimated initial attitude angles may have relatively large uncertainties that may affect the accuracy of other navigation parameters. This article suggests processing the gyro and accelerometer measurements with multiple levels of wavelet decomposition to remove the high frequency noise components. The proposed wavelet de-noising method was applied on a navigational grade inertial measurement unit (LTN90-100). The results showed that accurate alignment procedure and fast convergence of the estimation algorithm, in addition to reducing the estimation covariance of the three attitude angles, could be obtained.     

Error estimation of INS ground alignment through observabilityanalysis

A systematic analysis of the observability of an inertial navigation system (INS) in ground alignment with Bar-Itzhack and Berman's error model is presented. It is shown that the unobservable states are separately contained in two decoupled subspaces. The constraints on the selection of unobservable states are discussed. An estimation algorithm which is derived fully from the horizontal velocity outputs for computing the misalignment angles is provided. It reveals that the azimuth error can be entirely estimated from the estimates of leveling error and leveling error rate, without using gyro output signals explicitly     

高精度陆用惯导零速修正技术研究

零速修正技术是提高陆用惯导定位精度的一项有效手段。在周期性停车过程中,惯导系统除了将速度误差清零外,还能将由陀螺漂移、平台误差角等因素引起的位置误差进行补偿。本文采用离散线性卡尔曼滤波方法,通过连续三个停车时刻的速度误差构造观测向量,对惯导速度误差、加速度误差和陀螺漂移进行估计,进而补偿位置误差。车载试验表明,该零速修正方法位置精度高,且停车时间短,能够满足地面车快速响应的要求。     

主惯导速度误差短周期波动对子惯导传递对准影响分析

随着激光陀螺技术的发展,旋转调制式激光陀螺惯性导航系统逐渐成为舰载主惯导系统,舰载机、舰载武器系统需要旋转调制式激光惯导系统提供的姿态、速度和位置信息进行对准,即主子惯导的传递对准。由于旋转调制式系统中的姿态、速度和位置具有随旋转的短周期波动问题,势必会影响对准时间较短的子惯导对准精度。为了保证传递对准的快速性,一般采用速度匹配方法。定量分析了主子惯导传递对准过程中主惯导速度误差短周期波动对子惯导系统对准精度的影响,首先进行了数字仿真,之后利用双轴激光陀螺惯导、纯捷联光纤陀螺惯导数据进行了半实物仿真,验证了主惯导速度误差的一次项系数与子惯导初始对准水平姿态误差呈线性关系,二次项系数与子惯导初始对准航向误差呈线性关系。     

舰载机惯导动基座传递对准基准系统技术研究

根据舰载机惯导动基座高精度对准的需求,从系统顶层设计的角度,引入数字停机位空间坐标系概念,建立了舰载机惯导动基座传递对准的基准。在此基础上,分析了杆臂效应和船体挠曲变形对基准精度的影响,并给出了相应的处理模型和方法。舰载机可直接引入该基准坐标系下的导航信息进行对准,无须关注舰船性能参数和主导航安装位置等,有利于减少惯导动基座对准技术难度,提高对准效率。     

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     

Fast alignment and calibration algorithms for inertial navigation system

Algorithms for fast estimating the azimuth misalignment angle and calibrating gyro drift rates are approached from the point of view of control theory. By introducing the Lyapunov transformation, the equivalence of Strapdown Inertial Navigation System (SINS) and Gimbaled Inertial Navigation System (GINS) is discussed, and it shows that the analysis results of GINS can be applied to SINS directly by using such kind of equivalence. A similar transformation that based on physical essence is introduced, so that the true states can be replaced by the so-called pseudo-states, and then the observable states of INS can be dynamically decoupled with the unobservable states. Consequently, the best completely observable subsystem model of INS can be obtained. Based on the simplified subsystem model of INS, the algorithms for fast estimating the azimuth misalignment angle and calibrating gyro drift rates are proposed. The proposed algorithms show that the azimuth misalignment angle and gyro drift rates can be estimated from the rates of leveling misalignment angles without using the gyro output signals.     

卡尔曼滤波在弹道组合导航仿真中的应用

根据捷联惯性导航(INS)和GPS导航两个系统不同的特点,通过卡尔曼滤波方法实现了INS/GPS组合导航,以速度差和位置差作为卡尔曼滤波的量测量信息,建立了组合导航的简化滤波方程.在实际陀螺器件含有零偏的情况下,通过在角速度上引入定量的零位偏置来进行弹体模拟投放过程.将仿真导航结果和弹道参数比较,引入的陀螺偏置引起姿态角误差,而速度误差和位置误差比较小,导航计算参数误差在允许范围之内.     

一种新型的伪卫星辅助下的惯导初始对准方法

静基座且已知载体位置的情况下,INS可以快速地完成初始对准,但是在野外环境下通常无法快速地给出初始位置。伪卫星具有铺设简单快捷,不易受到破坏的特点,适合在未知环境下作为GNSS系统的补充来辅助定位。但是在GNSS拒止的情况下,如果单独使用伪卫星(PL)来进行定位会存在定位结果误差较大等问题,难以辅助INS系统完成初始对准。为了解决GNSS拒止情况下伪卫星辅助惯性导航系统进行初始对准存在的问题,提出了以高度传感器辅助下的PL定位算法,利用该算法得到准确的位置信息进而实现GNSS拒止条件下INS系统的初始对准,满足高精度的INS系统在复杂环境下的使用需求。     

惯导系统动基座对准精度试验评估

舰船、飞机武器装备出航前,其装备的惯性导航系统需要进行初始对准,由于实际使用环境的影响,载体可能受到扰动而产生摇摆运动,从而对惯导系统的对准造成干扰.为了提高惯导系统的对准导航精度,需要研究惯导系统在动基座条件下的对准技术方案,基于实际系统的试验验证是技术研究和产品检验交付的重要环节,为了有效评估惯导系统动基座对准的精...     

惯性导航系统各种传递对准方法讨论

 本文按对准基本原理将惯性导航系统各种传递对准方法分为两大类,一类可称为计算参数匹配法,它包括速度匹配和位置匹配;另一类可称为测量参数匹配法,它包括加速度匹配、姿态匹配和角速度匹配。文中详细讨论了这两类方法的性质,指出:计算参数匹配法类似静基座自对准和空间率对准,在载体无机动动作时对准时间较长。测量参数匹配法对准时间短,但受载体挠性变形的影响大。     

基于速度积分匹配的旋转调制惯导系统动基座对准方法

卫星导航信息辅助动基座对准过程中,速度噪声会影响对准精度和快速性,制约了旋转调制惯导角秒级高精度快速对准的实现.针对这一问题,提出了一种基于旋转调制惯导速度积分匹配的快速动基座对准方法,通过建立旋转调制惯导动基座对准误差方程和卡尔曼滤波观测模型,以消除动基座对准对载机特殊运动的要求.最后,在实验室静态环境和车载环境下,分别开展了速度积分匹配和速度十位置组合导航动基座对准仿真实验.仿真结果表明,提出的速度积分匹配方法具有误差估计量收敛速度快的特点,在对准精度不降低的情况下相对组合导航匹配方式能有效缩短动基座对准时间,并能基于旋转调制惯导取消动基座对准对载机的机动需求.     

基于强跟踪滤波的GPS/INS组合导航系统对准技术研究

针对卡尔曼滤波鲁棒性较差的问题,研究了基于强跟踪滤波方法的GPS/INS对准。建立了GPS/INS组合导航系统对准的误差模型,对机载装备系统进行GPS/INS组合导航系统的对准仿真分析,验证该方案的可行性及强跟踪滤波器的性能。仿真结果表明,采用强跟踪滤波能够根据残差的变化求出渐消因子,能够在机动过程中有效跟踪系统状态量,从而提高对准精度和速度。采用强跟踪滤波的GPS/INS组合导航系统对准技术可以保证对准的快速性及对准精度,对工程应用具有重要的参考价值。     

MSSS-UKF滤波在大方位失准角初始对准中的应用

针对大方位失准角初始对准中非线性滤波的实时性问题,在分析UKF滤波中的Sigma点采样策略基础上,将最小偏度单形采样策略应用于UKF滤波算法的Sigma点采样过程,并将基于最小偏度单形采样的UKF应用于大方位失准角的非线性初始对准过程。仿真结果显示,基于最小偏度单形采样策略(Minimal Skew Simplex Sampling)的UKF对姿态失准角估计的快速性要明显优于基于对称采样策略的UKF滤波算法,且可以满足惯导系统对对准精度和时间的要求。     

Online INS/GPS integration with a radial basis function neural network

Most of the present navigation systems rely on Kalman filtering to fuse data from global positioning system (GPS) and the inertial navigation system (INS). In general, INS/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings, including signal blockage for GPS and growth of position errors with time for INS. Present Kalman filtering INS/GPS integration techniques have some inadequacies related to the stochastic error models of inertial sensors, immunity to noise, and observability. This paper aims to introduce a multi-sensor system integration approach for fusing data from INS and GPS utilizing artificial neural networks (ANN). A multi-layer perceptron ANN has been recently suggested to fuse data from INS and differential GPS (DGPS). Although being able to improve the positioning accuracy, the complexity associated with both the architecture of multi-layer perceptron networks and its online training algorithms limit the real-time capabilities of this technique. This article, therefore, suggests the use of an alternative ANN architecture. This architecture is based on radial basis function (RBF) neural networks, which generally have simpler architecture and faster training procedures than multi-layer perceptron networks. The INS and GPS data are first processed using wavelet multi-resolution analysis (WRMA) before being applied to the RBF network. The WMRA is used to compare the INS and GPS position outputs at different resolution levels. The RBF-ANN module is then trained to predict the INS position errors and provide accurate positioning of the moving platform. Field-test results have demonstrated that substantial improvement in INS/GPS positioning accuracy could be obtained by applying the combined WRMA and RBF-ANN modules.     

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.     

Observability of an integrated GPS/INS during maneuvers

An observability analysis of a GPS/INS system during manoeuvers is presented based upon a perturbation model with respect to the Earth-centered-Earth-fixed (ECEF) coordinate system. Analysis is performed on two types of manoeuvers, linear acceleration and steady turn. These manoeuvers could be used for in-flight INS alignment using GPS. During the constant linear acceleration without rotation relative to the Earth, the linear system model is shown to be time-invariant. The observability analysis for the time invariant linear system model shows that linear acceleration does not change the number of observable modes but rather the structure of the observable space. For a nonconstant linear acceleration or a steady turn, the perturbation linear system becomes time varying. For this time-varying system, three types of observability are considered, complete, differential, and instantaneous observability. Instantaneous observability is the strongest properties and means that the state of the system at any time may be determined instantaneously from observation of the output and its derivatives. Instantaneous observability is important for fast in-flight INS alignment. It is shown that the number of instantaneously observable moded is increased by at least 2 during a maneuver. Hence, some linear combinations of the attitude angles become instantaneously observable.     

光纤陀螺惯导在航海领域的发展与应用

针对航海导航领域对惯性技术发展的新需求,从系统精度、旋转调制技术、陀螺性能等方面出发,梳理了国外航海惯导技术的发展脉络。由此总结出了航海惯导三点新的发展需求,包括定位精度、研制成本、使用维护性,同时给出了满足当前发展需求的一个研究方向,那就是采用超高精度的光纤陀螺研制航海惯导。最后从陀螺精度极限、温控、全阻尼等几个方面进行简要的可行性论证,并给出了部分验证试验结果,试验结果表明光纤陀螺惯导在航海领域具有广阔的发展前景。