Observability analysis of piece-wise constant systems. II.Application to inertial navigation in-flight alignment [militaryapplications]

For pt.I see ibid., vol.28, no.4, p.1056-67, Oct. 1992. The method of analyzing the observability of time-varying linear systems as piecewise constant systems (PWCS) is applied to the analysis of in-flight alignment (IFA) of inertial navigation systems (INS) whose estimability is known to be enhanced by maneuvers. The validity of this approach to the analysis of IFA is proven. The analysis lays the theoretical background to, and clearly demonstrates the observability enhancement of, IFA. The analytic conclusions are confirmed by covariance simulations. Although INS IFA was handled to various degrees in the past, a comprehensive control theoretic approach to the problem is introduced. The analysis yields practical conclusions and a procedure previously unknown     

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。     

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...     

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.     

一种基于可观测度分析的SINS/GPS自适应反馈校正滤波新方法

 针对机载捷联惯导系统(SINS)/全球定位系统（GPS）组合导航系统不完全可观测导致滤波器精度下降甚至发散的问题,提出了一种基于系统状态可观测度分析的自适应反馈校正滤波新方法。该滤波方法改进了系统可观测度的归一化处理方法,将归一化处理后的系统状态可观测度作为反馈因子,对SINS系统进行自适应反馈校正。最后,将该方法应用于机载合成孔径雷达(SAR)运动补偿用SINS/GPS组合导航系统中,飞行试验结果表明该方法在系统不完全可观测的情况下有效地提高了导航精度。     

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.     

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     

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。     

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。     

一种改造的SINS误差模型在精对准中的应用

针对捷联惯导系统原始的静态误差模型航向角误差不可观测的情况,本文提出了一种改造的静态误差模型.该模型在原始模型的基础之上,通过能观测性结构分解以及状态变换转化而来.理论分析表明经改造后的误差模型可从一定程度上解决航向角误差不可观测的问题.利用该模型对某型号车载激光捷联惯组作卡尔曼滤波精对准实验,并对比参数辨识精对准的结...     

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     

GPS/SINS超紧组合导航的性能分析

GPS接收机在高动态环境下很容易失锁,特别是载体的高动态造成的应力对接收机载波跟踪环影响很大。为了解决高动态环境下的组合导航,分析了GPS接收机载波跟踪环的测量误差和跟踪门限,采用惯导速度辅助GPS接收机跟踪环路的超紧组合结构。超紧组合需要涉及到GPS接收机跟踪环内部编排及高动态环境下的实验数据,难度较大。针对超紧组合仿真专门开发了GPS实时软件接收机、高动态GPS中频信号仿真器和惯导模拟器并构建了一个完整的GPS/SINS超紧组合仿真系统。仿真结果表明,该超紧组合导航系统可以跟踪50g的加速度和10倍音速。     

GPS Aided Inertial Navigation

The Global Positioning System is an extremely accurate satellite-based navigation system which, after its completion in 1989, will provide users worldwide, 24 hour. all weather coverage. A joint research project among Boeing, Rockwell-Collins, and Northrop has been completed in which a GPS receiver was integrated with a low-cost strap-down inertial navigation system and a flight computer. A Kalman filter in the latter allows in-fight alignment and calibration of the INS. In addition, feedback from the INS to the GPS receiver improves the system's ability to reacquire satellite signals after outages. The resulting system combines the accuracy of GPS with the jamming immunity and autonomy of inertial navigation. System tests were conducted in which a Boeing owned T-33 jet aircraft was flown through known test pattern to align and calibrate the INS. Earlier tests, including tests against an airborne jammer, were conducted in a modified passenger bus.     

基于“速度+姿态”快速传递对准的可观测性分析

惯导系统初始对准一般采用卡尔曼滤波器对初始姿态误差角进行估计,而在设计卡尔曼滤波器之前通常要对系统进行可观测性分析,确定卡尔曼滤波器的效果。捷联惯导系统的卡尔曼滤波模型在传递对准时,为线性时变系统,而线性时变系统的可观测性分析比较困难。文中采用一种依据系统矩阵的奇异值确定状态可观测度的方法对基于“速度＋姿态”快速传递对准的卡尔曼滤波模型进行可观测性分析,结果表明该方法可直接简单地实现系统状态的可观测度分析。     

Multiposition alignment of strapdown inertial navigation system

The authors demonstrate that the stationary alignment of strapdown inertial navigation system (SDINS) can be improved by employing the multiposition/technique. Using an observability analysis, it is shown that an optimal two-position alignment not only satisfies complete observability conditions but also minimizes alignment errors. This is done by analytic rank testing of the stripped observability matrix and numerical calculation of the error covariance. It is also shown that an optimal three-position alignment accelerates the convergence of the alignment error compared with two-position alignment     

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。     

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。     

惯导系统传递对准技术研究及海试验证

设计了抖动偏频激光陀螺捷联惯导系统的动基座传递对准方案,并进行了仿真计算及海上试验验证。激光陀螺捷联惯导系统采用该传递对准方案在试验船上完成了数十次海上传递对准试验,结果表明,该传递对准方案具有如下优点:在传递对准过程中,不专门要求载体作加速或S型机动运动;抗载体扰动运动的能力强;对准精度高。     

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。