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...     

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.     

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.     

New low cost avionics with INS/GPS for a variety of vehicles

Development of a new vehicle avionics suite is described, including integration of a low-cost, tightly-coupled integrated Inertial Navigation System/Global Positioning System (INS/GPS) to support vehicle guidance, navigation, and control (GN&C). A wide variety of next-generation low-cost launch vehicles could potentially benefit from integrated INS/GPS technology for GN&C and/or range safety applications. Coleman Aerospace Company (CAC) has developed a new low-cost avionics suite, the generic Integrated Mission Guidance & Tracking System (IMGTS), an open architecture, modular system that supports the requirements for various guidance applications and range safety tracking. As part of this development, Boeing North American, Inc. is supplying its Modular Miniature Integrated GPS/INS Tactical System (M-MIGITS^TM) Military-Off-The-Shelf (MOTS) INS/GPS product to support CAC's IMGTS GN&C     

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 strong tracking cubature Kalman filter and its application in maneuvering target tracking

The fading factor exerts a significant role in the strong tracking idea. However, traditional fading factor introduction method hinders the accuracy and robustness advantages of current strong-tracking-based nonlinear filtering algorithms such as Cubature Kalman Filter (CKF) since traditional fading factor introduction method only considers the first-order Taylor expansion. To this end, a new fading factor idea is suggested and introduced into the strong tracking CKF method. The new fading factor introduction method expanded the number of fading factors from one to two with reselected introduction positions. The relationship between the two fading factors as well as the general calculation method can be derived based on Taylor expansion. Obvious superiority of the newly suggested fading factor introduction method is demonstrated according to different nonlinearity of the measurement function. Equivalent calculation method can also be established while applied to CKF. Theoretical analysis shows that the strong tracking CKF can extract the third-order term information from the residual and thus realize second-order accuracy. After optimizing the strong tracking algorithm process, a Fast Strong Tracking CKF (FSTCKF) is finally established. Two simulation examples show that the novel FSTCKF improves the robustness of traditional CKF while minimizing the algorithm time complexity under various conditions.     

基于神经网络的航天器GPS/INS组合定姿系统

基于GPS和惯性技术的组合导航系统是近年来导航系统的研究热点和主要发展方向.目前基于卡尔曼滤波方法的算法在稳定性、计算量、算法鲁棒性以及系统可观测性等方面仍然存在问题.基于神经网络技术研究了一种新的GPS/INS组合定姿自适应卡尔曼滤波方法,理论分析表明,该方法不但对姿态信息具有较好的估计性能,而且对系统模型的精确性、噪声特性具备良好的鲁棒性.最后,利用模拟数据对所研究算法进行了分析计算,与传统的卡尔曼滤波方法进行了比较、分析,结果表明所设计组合算法在精度、稳定性以及鲁棒性等方面较传统卡尔曼方法具有良好的特性.     

Novel attitude determination method by integration of electronic level meter,INS, and low-cost turntable for level attitude evaluation and calibration of INS

Attitude references are greatly needed for the evaluation and calibration of Inertial Navigation Systems (INSs), which are widely used in gravimeter, marine, and aeronautical navigation. High-accuracy turntable, INS, and Global Navigation Satellite System have been utilized to verify the performance of relatively low-accuracy INS. The accuracy requirement of the attitude reference continuously increases with the rapid improvement of inertial sensors and navigation algorithms. However, the cost of attitude determination system increases rapidly with the increase of attitude accuracy requirement. To solve this limitation, the integration of level meter, INS, and low-cost turntable is proposed to provide level attitude, such as roll and pitch. The turntable is utilized to rotate the INS. An integration model of the level meter and INS is built to estimate the level attitude and reduce the cost of the turntable. The proposed method successfully avoids the dependence on high-accuracy turntables. An observability degree analysis is conducted to improve the level attitude accuracy further. The simulation and turntable test results indicate that the proposed method can provide high-accuracy level attitude without high-accuracy INS or turntable and is applicable to error calibration and attitude evaluation of INS.     

惯导/北斗/里程计一体化紧组合导航方法研究

当前,主要通过采用惯导/卫星导航组合或者惯导/里程计组合的方式来实现 车辆的定位定向;卫星信号良好时,惯导系统与卫星导航组合实现车辆定位定向,当卫 星导航信号不好甚至没有信号无法正常工作时,惯导系统与里程计组合实现车辆定位定 向。提出一种惯导/卫星导航/里程计三者的一体化组合方案,针对惯导、北斗、里程计 这三项测量设备构成的组合系统建立了统一的误差状态模型、组合量测模型以及反馈修 正模型,并通过卡尔曼滤波器来实现三者的一体化紧组合,这种惯导/北斗/里程计一体 化的紧组合方式,能更好地实现三者信号之间的充分交流与融合。将这种一体化紧组合 方法与传统的惯导/北斗组合、惯导/里程计组合方法进行了仿真比较,结果表明：惯导/ 北斗/里程计一体化的紧组合方法能更加快速、准确得到传感器误差（ 包含惯组误差、 北斗误差、里程计误差）的在线估计,更能有效提高各传感器的测量精度。     

Quadratic extended Kalman filter approach for GPS/INS integration

GPS/INS integration system has been widely applied for navigation due to their complementary characteristics. And the tightly coupled integration approach has the advantage over the loosely coupled approach by using the raw GPS measurements, but hence introduces the nonlinearity into the measurement equation of the Kalman filter. So the typical method for navigation using measurements of range or pseudorange is by linearizing the measurements in an extended Kalman filter (EKF). However, the modeling errors of the EKF will cause the bias and divergence problems especially under the situation that the low quality inertial devices are included. To solve this problem, a quadratic EKF approach by adding the second-order derivative information to retain some nonlinearities is proposed in this paper. Simulation results indicate that the nonlinear terms included in the filtering process have the great influence on the performance of integration, especially in the case that the low quality INS is used in the integrated system. Furthermore, a two-stage cascaded estimation method is used, which circumvents the difficulty of solving nonlinear equations and greatly decreases the computational complexity of the proposed approach, so the quadratic EKF approach proposed in this paper is of great value in practice.     

高动态下惯性加速度辅助三阶锁相环性能分析

针对高阶跟踪环路稳定性比低阶环路差,大带宽带来测量误差大的问题。研究在高动态环境下,惯导加速度信息辅助卫星接收机三阶载波锁相环跟踪算法,以及不同环路参数下跟踪环路的性能。对载体高动态场景、加速度信息延迟进行建模,并对算法进行了数学仿真。仿真分析结果表明,在加速度信息辅助下,即使压缩载波跟踪环路等效噪声带宽到3Hz,在高达1200g/s的加速度动态下,环路跟踪同样稳定可靠。     

Enhancing filter robustness in cascaded GPS-INS integrations

Filter robustness is defined herein as the ability of the Global Positioning System/Inertial Navigation System (GPS-INS) Kalman filter to cope with adverse environments and input conditions, to successfully identify such conditions and to take evasive action. The formulation of two such techniques for a cascaded GPS-INS Kalman filter integration is discussed This is an integration in which the navigation solution from a GPS receiver is used as a measurement in the filter to estimate inertial errors and instrument biases. The first technique presented discusses the handling of GPS position biases. These are due to errors in the GPS satellite segment, and are known to be unobservable. They change levels when a satellite constellation change occurs, at which point they introduce undesirable filter response transients. A method of suppressing these transients is presented. The second technique presented deals with the proper identification of the filter measurement noise. Successful formulation of the noise statistics is a factor vital to the healthy estimation of the filter gains and operation. Furthermore, confidence in the formulation of these statistics can lead to the proper screening and rejection of bad data in the filter. A method of formulating the filter noise statistics dynamically based on inputs from the GPS and the INS is discussed     

A relative navigation system for formation flight

A relative navigation system based on both the Inertial Navigation System (INS) and the Global Positioning System (GPS) is developed to support situational awareness during formation flight. The architecture of the system requires an INS/GPS integration across two aircraft via a data link. A fault-tolerant federated filter is used to estimate the relative INS errors based on relative GPS measurements and a range measurement obtained from the data link. The filter is constructed based on a reduced-order model of the relative INS error process. A method for analyzing the filter performance is presented. A case involving two helicopters in formation flight is studied under three different night trajectories to account for the effect of vehicle motion on the INS state transition matrix. The results of the covariance analysis are compared with actual night results over an instrumented test range.     

小型无人机的导航与制导仿真系统研究

研究了基于飞行器动力学模型的小型无人机的惯性组合导航与制导系统仿真技术,组合导航系统嵌入了飞行器的轨迹和姿态控制回路,建立了基于MATLAB/AEROSIM的组合导航计算机仿真系统,仿真系统包括惯性组合导航仿真模块、传感器仿真支持模块、飞行器6自由度动力学模型模块、飞行器轨迹生成、轨迹控制与姿态控制模块、导航仿真评估模块。基于该仿真系统,目前已开展惯性/卫星深组合、惯性/大气数据融合等理论算法和技术研究。     

基于分层置信规则库的惯导系统性能评估方法

为解决惯导系统（INS）性能评估所面临的高价值样本缺失、评估指标多、系统复杂等问题,提出一种基于分层置信规则库（Hierarchical BRB）的惯导系统性能评估方法。将专家知识与监测数据进行有效融合,提高了惯导系统的性能评估精度。首先,针对惯导系统结构构建分层BRB模型,同时将系统内部器件产生组合误差考虑在模型中。其次,为降低专家知识不确定性对初始模型评估精度的影响,采用基于投影算子的协方差矩阵自适应优化策略（P-CMA-ES）构建优化模型,通过监测数据对模型参数进行微调。最后,以某型捷联惯导系统的性能评估为例,验证了所提方法的有效性。     

INS/GPS/TAN系统中的联邦卡尔曼滤波信息融合方法

在分析联邦卡尔曼滤波原理和结构的基础上,提出了一个适合惯性导航系统／全球定位系统／地形辅助导航（ＩＮＳ／ＧＰＳ／ＴＡＮ）子系统状态向量维数不同这一特点的联邦卡尔曼滤波方法,并构造了一种具有较强容错性能和适应性的联邦卡尔曼子系统滤波器结构。由于采用了局部状态扩展、局部状态压缩、智能的不等间隔滤波、多级故障检测、阈值控制等信息融合技术,在保证精度的前提下,联邦卡尔曼滤波器的可靠性、适应性得到了明显提高。     

捷联式惯导系统动态误差特性研究

根据载体运动状态下捷联惯性导航系统(SINS)的误差方程时变的特点,推导出捷联惯性导航系统动态误差模型,并对其在几种动态环境下的误差特性进行了仿真研究。     

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...     

GPS/惯性组合方式讨论与导航精度分析

 本文讨论GPS/惯性组合两种方式的优缺点。并以GPS伪距和伪距率与惯导组合为例,按GPS测量误差的不同,以及使用差分机等情况,仿真计算了机载使用的组合导航性能,进行了详细的精度分析。结果表明,这种组合的导航精度比GPS和惯导各自的导航精度高。在采用差分GPS机与惯导组合后,位置误差将进一步减少,使组合导航具有开辟例如飞机进场着陆等新的使用领域的可能性。     

An Algorithm Providing All-Attitude Capability for Three-Gimballed Inertial Systems

This paper describes an algorithm which protects a three-gimballed inertial system against gimbal lock while preserving the inertial reference. One sample of the gimbal angles and gimbal angle rates for a torque-free dynamic vehicle provides the information needed to determine whether or not gimbal lock will occur at some later time. When gimbal lock is imminent, the inertial platform is commanded to a new "safe" orientation, and knowledge of the inertial reference is updated accordingly. By iterating this process gimbal lock protection is extended to a vehicle subjected to torques. The results of digital simulations using the Apollo Primary Guidance, Navigation and Control System as a model are presented for various dynamic situations.