面向失锁在线补偿的高超声速飞行器组合导航方法研究

根据高超声速飞行器导航的主要需求，针对高动态飞行条件下可能出现的卫星导航信号跟踪丢失等问题，本文设计了基于卫星观测值在线补偿的组合导航方法，该方法可在GPS导航接收机失锁的情况下，基于预存卫星星历外推模型和卫星信号误差模型，在线重构虚拟卫星导航观测值并补偿由信号失锁导致的组合滤波器发散情况，从而确保飞行器组合导航的精度。结合助推—滑翔高超声速飞行器航迹对该方案进行了仿真验证，结果表明，该方案能够在助推—滑翔高超声速飞行器强动态条件下确保卫星导航数据输出的连续性，在一定程度上克服了卫星导航信号丢失带来的不利影响，确保高超声速飞行器GPS/捷联惯导组合导航的基本导航定位性能。     

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。     

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。     

SINS/GNSS组合导航测试系统用惯导模拟源技术研究

针对光纤陀螺SINS(捷联惯性导航系统)与GNSS(全球卫星导航系统)组合导航产品高动态性能测试难的问题,本文研究了一种组合导航测试系统,并对捷联惯导模拟源进行了重点研究.首先以捷联惯导解算算法为基础逆推出了捷联惯导模拟源算法,然后对捷联惯导模拟源进行了功能实现,可以与导航卫星信号模拟源同步向组合导航计算机发送数据用于组合导航解算.最后对捷联惯导模拟源的功能与性能进行了验证.结果表明,捷联惯导模拟源功能正常,模拟数据的精度达到设计要求.利用此惯导模拟源与导航卫星信号模拟源配套使用,将可满足后续SINS/GNSS组合导航系统的相关性能测试或验证要求.     

基于导航卫星反射信号的空间飞行器探测定位方法

导航卫星信号经由空间飞行器后将发生反射与散射,此信号对于飞行器自身的定位通常作为多径信号被消除。利用双基无源雷达的概念,提出利用该信号实现空间飞行器的远程定位方法。该方法充分利用空间飞行器对于导航卫星信号的反射与散射,在地面/空中设置可以接收此反射信号的接收机,从而实现飞行器的探测。接收机利用码延迟锁定环路实现直射信号与反射信号的锁定,并通过求解直射信号与反射信号的相关功率获得其路径差,进而计算出空间飞行器的位置。介绍了利用延迟映射接收机(DMR)探测空间飞行器的系统组成,并给出了远程定位的数学模型、关键技术分析、DMR的设计原理及验证实验,实验结果表明所设计的DMR可以有效地接收到导航卫星反射信号。为空间飞行器的探测提供了一种新型的手段。     

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。     

车载捷联惯导双里程计组合导航方法研究

针对当前车载捷联惯导与里程计组合导航时，将里程计安装在车底盘左侧或右侧位置而造成的导航误差，以及里程计信息未能真实反映车体中心的实际运行状态，研究了一种车载捷联惯导/双里程计组合导航方法。该方法分别在车底盘左侧和右侧位置各安装了一个里程计，将双里程计信息作为量测量，设计了组合导航融合算法进行Kalman滤波组合导航。在导航过程中对双里程计信息进行χ２检测，以避免车体作大转弯运行或有外部干扰时引起的里程计信息异常。跑车试验结果表明，该融合算法能使定位结果得到最优融合，定位误差整体减小到20m以内，最大处减小6m，离线分析进一步证明了该融合算法的有效性。     

复杂环境下微小飞行器惯性/激光雷达Robust-SLAM方法

针对微小型飞行器在巡检、探测和地图构建等应用中关键的自主导航技术,提出了一种基于惯性辅助的激光雷达Robust-SLAM方法用于微小型飞行器自主导航。相对于传统的激光雷达SLAM方法,该方法在SLAM框架中引入了感知环境突变检测方法,并且加强了惯性与SLAM的组合程度,有效地解决了高程方向感知环境发生突变时激光雷达SLAM定位误差大的问题。室内车库实际飞行实验结果表明,该方法能够实现微小型飞行器在三维空间中实时可靠的自主导航,具有较好的工程应用价值。     

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。     

红外成像导引头跟踪丢失状态下的控制策略研究

针对红外成像导引头跟踪丢失后无导引信号输出的情况,提出了一种飞行控制策略:即在导引头稳定跟踪过程中通过目标被动定位算法实时估算其相对位置信息,当导引头跟踪丢失后,根据估算得到的相对位置信息和惯导输出的飞行器实时位置、速度信息解算理论导引信号,以及该信号生成控制指令控制飞行器朝目标飞行。对导引头跟踪丢失后的控制效果进行了数学仿真验证。结果表明,目标被动定位结果收敛,跟踪丢失情况下飞行器飞行控制稳定,命中精度较高,具有一定的工程应用价值。     

Systematic methods for knowledge acquisition and expert systemdevelopment [for combat aircraft]

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy inertial navigation system (INS) was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm     

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     

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.     

无人机动态目标高精度定位方法研究

针对未来无人机对目标高精度定位的迫切需求,开展了无人机动态目标高精度定位方法研究,提出了动态目标高精度定位总体方案。方案将惯性/卫星组合导航系统和机载光电平台系统获取的载机信息和目标相对信息作为目标定位算法的输入量,合理分配目标定位过程中各项误差参数,实现无人机对目标的高精度定位。经仿真验证,目标定位精度和载机导航精度都达到了期望指标,表明了方案和算法的有效性。     

机载双轴旋转调制激光惯导系统误差特性及关键技术分析

在未来作战环境下,长航时远程作战飞机对全自主长航时高精度导航系统提出了迫切的需求,对提高作战能力起着重要作用.对比各种导航手段,其中双轴旋转调制激光惯导系统是目前唯一一种可行的全天候全自主高精度导航手段,从双轴旋转调制惯导系统的原理出发,对双轴旋转调制激光惯导系统机载应用的误差特性及关键技术进行深入分析,结果表明:对于1n mile/12h的导航精度,双轴旋转调制惯导系统较捷联惯导系统对陀螺漂移精度要求降低一个数量级,关键技术实现方案合理可行.     

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.     

Periodic Error Compensation for Quartz MEMS Gyroscope Drift of INS

In order to improve the navigation accuracy of an inertial navigation system （INS）, composed of quartz gyroscopes, the existing real-time compensation methods for periodic errors in quartz gyroscope drift and the periodic error term relationship between sampled original data and smoothed data are reviewed. On the base of the results, a new compensation method called using former period characteristics to compensate latter smoothness data （UFCL for short） method is proposed considering the INS working characteristics. This new method uses the original data without smoothing to work out an error conversion formula at the INS initial alignment time and then compensate the smoothed data errors by way of the formula at the navigation time. Both theoretical analysis and experimental results demonstrate that this method is able to cut down on computational time and raise the accuracy which makes it a better real-time compensation approach for periodic error terms of quartz micro electronic mechanical system （MEMS） gyroscope＇s zero drift.     

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。     

Integration of GPS and low cost INS for pedestrian navigation aided by building layout

In outdoor environments, GPS is often used for pedestrian navigation by utilizing its signals for position computation, but in indoor or semi-obstructed environments, GPS signals are often unavailable. Therefore, pedestrian navigation for these environments should be realized by the integration of GPS and inertial navigation system （INS）. However, the lowcost INS could induce errors that may result in a large position drift. The problem can be minimized by mounting the sensors on the pedestrian＇s foot, using zero velocity update （ZUPT） method with the standard navigation algorithm to restrict the error growth. However, heading drift still remains despite using ZUPT measurements since the heading error is unobservable. Also, tbot mounted INS suffers from the initialization ambiguity of position and heading from GPS. In this paper, a novel algorithm is developed to mitigate the heading drift problem when using ZUPT. The method uses building lay- out to aid the heading measurement in Kalman filter, and it could also be combined for the initial- ization. The algorithm has been investigated with real field trials using the low cost Microstrain 3DM-GX3-25 inertial sensor, a Leica GS10 GPS receiver and a uBlox EVK-6T GPS receiver. It could be concluded that the proposed method offers a significant improvement in position accuracy for the long period, allowing pedestrian navigation for nearly40 min with mean position error less than 2.8 m. This method also has a considerable effect on the accuracy of the initialization.     

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。