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.     

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.     

Observability analysis of piece-wise constant systems. I. Theory

For pt.II see ibid., vol.28, no.4, p.1068-75, Oct. 1992. A method for analyzing the observability of time-varying linear systems which can be modeled as piece-wise constant systems (PWCS) is presented. An observability matrix for such systems is developed for continuous and discrete time representations. A stripped observability matrix (SOM) is introduced which simplifies the analysis in cases where the use of this matrix is legitimate. The observability analysis is presented as a step-by-step procedure     

Observability in passive target motion analysis

The nature of observability of nonlinear systems encountered in passive target motion analysis (TMA) is carefully examined. The approach proposed here is based upon a well-chosen criterion which allows us to answer the major observability questions     

传统组合导航中的实用Kalman滤波技术评述

在随机线性系统建模准确的情况下,Kalman滤波是线性最小方差无偏估计。针对传统惯导/卫导组合导航的实际应用,难以精确建模,给出了常用的建模方法、状态量选取原则、离散化方法及滤波快速计算方法。讨论了平方根滤波、自适应滤波、联邦滤波和非线性滤波等技术的适用场合,并给出了使用建议。针对前人研究可观测度中未考虑随机系统噪声的缺陷,提出了更加合理的以初始状态均方误差阵为参考的可观测度定义和分析方法。提出了均方误差阵边界限制方法,可有效抑制滤波器的过度收敛和滤波发散。该讨论可为工程技术人员提供一些有实用价值的参考。     

车载捷联惯导与里程计组合导航技术研究

惯导的误差随着时间增长是积累的,可采用里程计辅助捷联惯导构成纯自主的车载组合导航系统.利用捷联惯导的速度和里程计测量的速度之差作为观测量,通过卡尔曼滤波技术校正惯导的导航参数,可以有效地抑制惯导误差的积累,提高导航参数的精度.本文推导了组合导航系统的模型,从理论上用特征值方法分析了系统的可观测度,进而设计轨迹进行了仿真...     

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.     

基于可观测度分析和增量因子图的多源融合导航方法

复杂动态场景下高精度导航定位是自主无人系统决策规划与控制执行的基础。在城市峡谷、隧道、地下或室内停车场等场景下，卫星信号弱甚至丢失，严重影响了惯性/卫星/视觉等多源融合导航的精度和可靠性。为主动适应动态场景变化，迫切需要设计一种适用于跨场景的多源融合导航系统。基于动态时变系统的可观测度分析，在线度量惯性/卫星、惯性/视觉等组合导航因子的可信程度，进而采用因子图融合导航框架，根据各组合导航因子的可信程度，主动优化因子构建和增量平滑过程，以实现多传感器自适应融合导航与可靠定位。实验仿真表明：基于可观测度分析方法，能够在线优化因子图计算过程，提升了多源融合导航系统的环境适应性和跨场景能力，保证了复杂动态场景下自主无人系统跨场景导航模式切换和连续可靠的导航定位。     

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.     

A maintenance-free lead acid battery for inertial navigationsystems aircraft

Historically, aircraft inertial navigation system (INS) batteries have utilized vented nickel-cadmium batteries for emergency DC power. The United States Navy and Air Force developed separate systems during their respective INS developments. The Navy contracted with Litton industries to produce the LTN-72 and Air Force contracted with Delco to produce the Carousel IV INS for the large cargo and specialty aircraft applications, over the years, a total of eight different battery national stock numbers (NSNs) have entered the stock system along with 75 battery spare part NSNs. The standard hardware acquisition and reliability program is working with the Aircraft Battery Group at Naval Surface Warfare Center Crane Division, Naval Air Systems Command (AIR 536), Wright Laboratory, Battelle Memorial Institute, and Concorde Battery Corporation to produce a standard INS battery. This paper discusses the approach taken to determine whether the battery should be replaced and to select the replacement chemistry. The paper also discusses the battery requirements, aircraft that the battery is compatible with, and status of Navy flight evaluation. Projected savings in avoided maintenance in Navy and Air Force INS systems is projected to be $14.7 million per year with a manpower reduction of 153 maintenance personnel. The new INS battery is compatible with commercially sold INS systems which represents 66% of the systems sold     

改进的GPS/INS组合导航选星算法

在已有的 GPS定位的选星算法的基础上,从组合系统量测矩阵出发提出了一种适用于 GPS/INS组合导航的选星算法。此算法在原有算法的基础上,考虑了卫星仰角、方位角对卡尔曼滤波器可观性的影响,避免因观测量与系统状态间关联项的减少而导致的滤波器可观性下降,从而保证滤波器性能的稳定。     

基于可观测性分析的旋转式惯导系统在线自标定方法的设计

本文建立了速度误差外观测量的静基座双轴旋转式惯导系统在线标定卡尔曼滤波模型,其状态向量包括地速误差、姿态失准角和惯性器件零偏、标度因数误差、安装误差,可估计旋转式惯导系统失准角与惯性器件误差参数。通过分段线性定常系统(PWCS)可观测性分析方法分析不同旋转方式下系统可观测性变化情况,得出双轴连续旋转的角运动方案可以改善卡尔曼滤波滤波的可观测性。根据基于奇异值分解的可观测度分析结果进行模型降阶,同时结合旋转式惯导系统的工程应用特性,得到12阶卡尔曼滤波参数模型。降阶系统阶数降低约55%,可以显著降低运算量,有效提高了导航计算机运算效率和实时性。仿真实验表明：降阶模型的估计精度不低于原模型,而且部分状态量的滤波收敛速度有提高。     

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     

基于卫星信息的惯导系统可观测性分析

可观测性分析是组合导航系统进行滤波器设计的重要内容,直接影响状态估计时的收敛速度和收敛精度,因而需要对状态变量的可观测程度进行定量分析。文章针对基于卫星的惯导系统在机动方式时的可观测性分析进行研究,改进了组合导航系统的可观测度,省略了外观测量的求取,有效减少了计算量,简化了分析步骤。仿真结果证明了该方法的有效性。     

Spatial Gauss-Markov Models of Ocean Currents

Ocean currents are an important error source in marine inertial navigation systems (INS). Satellite radar altimeter data are used to construct self- consistent Gauss- Markov models of ocean currents. These models are useful for INS error analysis and optimal (Kalman) filtering of INS outputs.     

无人机下滑着陆DGPS/INS导航及引导系统的仿真与试验研究

介绍了一种采用输出校正方式DGPS/INS组合导航系统引导无人机下滑着陆的方案。给出了该方案的数学模型,对组合导航系统进行了数字仿真,并在数字仿真的基础上进行了动态跑车试验,验证了所设计的输出校正方式DGPS/INS组合导航系统能够满足引导无人机自动下滑着陆的精度要求。     

Discrete-time observability and estimability analysis for bearings-only target motion analysis

Observability in the context of bearings-only tracking (BOT) is still the subject of important literature. Different from previous approaches, where continuous-time analysis was considered, our approach relies on discrete-time analysis. It is then shown that this allows us to use directly and efficiently the simple formalisms of linear algebra. Using the direct approach, observability analysis is essentially reduced to basic considerations about subspace dimensions. Even if this approach is conceptually quite direct, it becomes more and more complex as the source-encounter scenario complexity increases. For complex scenarios, the dual approach may present some advantages essentially due to the direct use of multilinear algebra. New results about BOT observability for maneuvering sources are thus obtained. Observability analysis is then extended to unknown instants of source velocity changes. Even if observability analysis provides thorough insights about the algebraic structure of the BOT problem, the optimization of the observer maneuvers is essentially a control problem. Basic algebraic considerations prove that a relevant cost functional for this control problem is the determinant of the Fisher information matrix (FIM). So, a large part of this work is devoted to the analysis of this cost functional. Using multilinear algebra, general approximations of this functional are given. In order to involve only directly estimable parameters, the source bearing-rates are examined. Using these approximations, a general framework for optimizing the observer trajectory is derived which allow us to approximate the optimal sequence of controls. It is worth stressing that our approach does not require the knowledge of the source trajectory parameters and is still valid for a maneuvering source.     

Multi-sensor optimal data fusion for INS/GPS/SAR integrated navigation system

INS/GPS/SAR integrated navigation system represents the trend of next generation navigation systems with the high performance of independence, high precision and reliability. This paper presents a new multi-sensor data fusion methodology for INS/GPS/SAR integrated navigation systems. This methodology combines local decentralized fusion with global optimal fusion to enhance the accuracy and reliability of integrated navigation systems. A decentralized estimation fusion method is established for individual integrations of GPS and SAR into INS to obtain the local optimal state estimations in a parallel manner. A global optimal estimation fusion theory is studied to fuse the local optimal estimations for generating the global optimal state estimation of INS/GPS/SAR integrated navigation systems. The global data fusion features a method of variance upper finiteness and a method of variance upper bound to ensure that the global optimal state estimation can be achieved under a general condition. Experimental results demonstrate that INS/GPS/SAR integrated navigation systems achieved by using the proposed methodology have a better performance than INS/GPS integrated systems.     

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     

基于奇异值分解的组合导航可观测度计算

以捷联惯组为主惯导的组合导航系统具有短时定位精度高、可靠性强等优点,但其依然存在长时间导航精度不高、运算量大、组合效率不高等问题。为更好地完善组合导航系统的误差补偿和抑制技术,对SINS/DVL组合导航系统的可观测性能进行了研究。在分段定常系统(Piece-wise Constant System,PWCS)的可观测性分析方法及基于奇异值分解的系统状态可观测度分析方法基础上,结合可观测性矩阵的遗传特性,提出了一种简化的状态量可观测性分析方法,并对该方法进行了理论仿真。为方便比较状态量的可观测程度,对各状态的可观测度进行了归一化处理。最后,通过湖面跑船实验设计了不同的航迹机动方式,计算了关键导航参数的可观测性能。实验证明,该方法可以实时计算组合导航参数的可观测度,根据可观测度设计的航迹可以有效提高导航精度,定位精度可提高1个量级,收敛速度也获得了明显提高。