SINS/GPS/地磁组合导航系统的研究

为了应对航天、航海和车辆导航对导航系统的精度,提出了基于DSP的捷联惯性导航系统(SINS)/全球定位系统(GPS)/地磁组合导航系统。介绍了该组合导航的系统结构与基本原理,采用无迹卡尔曼滤波(UKF)算法完成对组合导航信息的融合,并对组合导航样机进行车载实验。试验结果表明,该组合导航系统提高了精度、计算速度和稳定性。     

垂直导向钻井工具安装误差的单象限校正

井下钻具姿态惯性测量单元(IMU)的安装误差降低了近垂直姿态的测量与解算精度。基于近垂直姿态下测量值与理论值之间的关系矩阵,推导其关系矩阵各项的相对误差,分析表达式各项相对误差特征,提出一种单象限校正方法。近垂直姿态下,采用单一象限内相对均匀的三组测量值得到一个校正矩阵,并对该象限内全部测量数据进行校正。姿态解算结果表明,与传统方法相比,单象限校正方法能有效提高姿态参数解算精度3.3倍以上。     

捷联惯导系统姿态解算的实现

提出了捷联惯性导航系统姿态解算模块的一种实现方法。基于DSP的硬件平台和四元数的数学平台,设计了捷联惯性导航系统的姿态解算模块。介绍了捷联惯性导航系统的工作原理和姿态解算的基本算法,并给出了四元数法的四阶龙格—库塔数值解法。设计了姿态解算模块的硬件电路和软件实现程序。实验测试结果表明,在增量角小于5°的情况下,四阶龙格—库塔法进行姿态解算,误差小于0.0053％,能够满足捷联惯性导航系统的精度要求;应用TMS320C6713B进行硬件电路设计,每次解算时间小于36µs,能够满足捷联惯性导航的实时性的要求。     

引入滑模观测器的GPS/INS组合导航滤波方法

由低成本器件组成的卫星/惯性(GPS/INS)组合导航系统中,存在较大的非线性与不确定性,为改善这一问题,本文提出一种引入滑模观测器(SMO)的滤波方法。首先,该方法建立了组合导航系统模型,介绍了扩展卡尔曼滤波(EKF)计算过程并分析存在的不足。然后,介绍了滑模观测器的基本原理,根据系统构建观测器。最后,说明了引入滑模观测器的EKF组合导航算法实现流程,滑模观测器将模型误差、状态估计以及均值方差融入EKF算法,修正系统输出。通过轨迹仿真实验与车载实验验证了所提方法优于传统EKF算法,具有更高的滤波精度。在车载实验中,卫星信号失锁15 s情况下,与EKF方法相比,所提方法的东向位置误差降低了53%,北向位置误差降低了37%,证明该方法能够有效抑制GPS/INS组合导航误差发散,为以后工程实践提供一定的参考价值。     

捷联惯导系统姿态解算模块的实现

提出了一种实现捷联惯性导航系统姿态解算模块的方法。基于DSP的硬件平台和四元数的数学平台,设计了捷联惯性导航系统的姿态解算模块。介绍了捷联惯性导航系统的工作原理和姿态解算的基本算法,并给出了四元数法的四阶龙格一库塔数值解法。设计了姿态解算模块的硬件电路和软件实现程序。实验测试结果表明,在增量角〈5°的情况下,用四阶龙格一库塔法进行姿态解算,误差〈0．0053％;应用TMS320C6713B进行硬件电路设计,每次解算时间〈36μs,能够满足捷联惯性导航系统对精度和速度的要求。     

嵌入式GPS/MIMU/磁罗盘组合导航系统

研制出基于FPGA和DSP的嵌入式GPS/MIMU/磁罗盘组合导航系统。该系统硬件由石英微机械陀螺仪、石英挠性加速度计、GPS接收机、数字磁罗盘和基于FPGA和DSP的高速导航计算机模块等组成。在该系统软件方面,采用圆锥误差补偿与划船误差补偿的现代捷联导航算法和含传感器噪声模型的18维扩展Kalman滤波器,并利用惯性传感器和MIMU导航信息对GPS和磁罗盘信号进行质量控制。经车载试验结果表明,该组合导航系统水平姿态误差小于0.2°,航向角误差小于0.3°,定位精度小于3m。     

IMU/GPS数据同步电路的研究与实现

数据同步是INS/GPS组合导航中数据融合的重要前提.对IMU/GPS组合系统中的数据同步技术进行研究,在IMU没有同步脉冲的情况下,提出了一种以GPS的1PPS(秒同步脉冲信号)为参考时标,由CPLD和8253实现的数据同步方法.实验证明了方案的设计是成功的.     

基于双DSP的POS数据采集与处理系统的设计与实现

详细阐述了一种基于双DSP的POS数据采集与处理系统的设计与实现.该系统采用FPGA实现了IMU输出多路脉冲的并行采集和GPS数据的接收.通过专门的DSP1实现IMU的误筹补偿和GPS数据解包,以及IMU和GPS数据的时间同步.采用高性能DSP2进行导航解算处理,两DSP之间通过并行主机接口(HPI)进行高速数据传输.所采集的IMU和GPS数据以及解算结果通过以太网接口输出.最后进行了跑车实验,实验结果表明:所研制的POS数据采集与处理系统在功能、精度及实时性方面均达到了预期的设计同标.     

基于FPGA的GNSS/INS组合系统时间同步设计

为解决组合导航系统中的GNSS和INS数据的时间同步问题,研制开发了一种基于FPGA的低成本时间同步系统,实现INS或其他辅助导航传感器测量数据与GNSS接收机数据之间的时间同步.通过实验结果证实,所设计的时间同步系统的精度可达600μs,满足大多数中高精度INS/GNSS组合系统的同步测量要求,并对姿态误差进行研究,可以看出,设计的时间同步系统可以将姿态误差控制在一个较小的范围内,从而验证了时间同步系统的可行性.     

基于激光三角测量原理的轨距检测系统研究

轨距是轨道几何尺寸中的一个重要参数,及时掌握轨距信息对保证行车安全具有重要意义.基于激光三角测量原理研发了一种安装于路轨两栖综合检测车上的轨距检测系统.该系统使用2组共6台二维激光扫描传感器获得左右钢轨断面轮廓,利用基于CPLD的同步信号触发模块保证各传感器数据同步.通过对采集的钢轨断面轮廓数据采用基于不连续度的自适应滤波和钢轨弧形区特征提取算法,实时提取轨距特征点并计算显示当前断面轨距值.实验结果表明,该轨距检测系统可实现轨距参数的非接触式动态实时测量,检测车运行速度为40 km/h时钢轨断面采样间隔3.7 mm,轨距检测精度±0.8 mm.     

Attitude determination GPS/INS integrated navigation system with FDI algorithm for a UAV

Recently an unmanned aerial vehicle (UAV) has been widely used for military and civil applications. The role of a navigation system in the UAV is to provide navigation data to the flight control computer (FCC) for guidance and control. Since performance of the FCC is highly reliant on the navigation data, a fault in the navigation system may lead to a disastrous failure of the whole UAV. Therefore, the navigation system should possess a fault detection and isolation (FDI) algorithm. This paper proposes an attitude determination GPS/INS integrated navigation system with an FDI algorithm for a UAV. Hardware for the proposed navigation system has been developed. The developed hardware comprises a commercial inertial measurement unit (IMU) and the integrated navigation package (INP) which includes an attitude determination GPS (ADGPS) receiver and a navigation computer unit (NCU). The navigation algorithm was implemented in a real-time operating system with a multi-tasking structure. To evaluate performance of the proposed navigation system, a flight test has been performed using a small aircraft. The test results show that the proposed navigation system can give accurate navigation results even in a high dynamic environment.     

Application of unscented R–T–S smoothing based on novel mathematical model in SINS/GPS integrated system post processing

The integrated system of Strapdown Inertial Navigation System (SINS) and Global Positioning System (GPS) has become widely-applied equipment in airborne remote sensing for getting the motion information. For the SINS/GPS integration used estimation theory, the mathematical model plays an important role in the optimal estimation of state. In this paper, the main factors that affect the precision of SINS/GPS integrated estimation in IMU calibration errors are considered and a novel nonlinear mathematical model is proposed. An unscented Rauch–Tung–Striebel smoother (URTSS) is implemented based on this model, and Monto Carlo simulation and flight test with a loaded SINS/GPS integrated system are conducted to verify the performance of this model. The comparison results indicate that the proposed nonlinear model can effectively improve the attitude estimate precision.     

Novel hybrid of strong tracking Kalman filter and wavelet neural network for GPS/INS during GPS outages

Aiming to improve positioning precision of the GPS/INS integrated navigation system during GPS outages, a novel model combined with strong tracking Kalman filter (STKF) and wavelet neural network (WNN) algorithms for INS errors compensation is proposed and tested. STKF is used to estimate INS errors as a replacement of Kalman filter (KF), and WNN is applied to establish a highly accurate model based on STKF when GPS works well and to predict INS errors during GPS outages. Performance of the proposed model has been experimentally verified using GPS and INS data collected in a land vehicle navigation test. The comparison results indicate that the proposed model combined with STKF/WNN algorithms can effectively provide high accurate corrections to the standalone INS during GPS outages.     

Observability analysis of ins with a GPS multi-antenna system

This paper investigates observability properties of strapdown INS aided by a GPS antenna array. The motivation to consider a GPS antenna array is that the lever-arms between the GPS antennas and IMU play an important role in the estimation of vehicle attitude and biases of IMU. It is shown that time-invariant INS error models are observable with measurements from at least three GPS antennas. It is also shown that time-varying error models are instantaneously observable with measurements from three antennas. Numerical simulation results are given to show the effectiveness of multiple GPS antennas on estimating vehicle attitude and biases of IMU when IMU has considerable magnitude of biases.     

An elastic deformation measurement method for helicopter based on double-IMUs/DGPS TRAMS

Because of the severe vibration during flight process, the elastic deformation caused by the weight of avionic devices which are placed in the head nacelle of the helicopter such as millimeter wave radar cannot be measured through the optical-imaging and accelerometer-induction method. In order to survey this elastic deformation in real-time, this paper proposes the double-IMUs/DPGS tightly-coupled relative attitude measurement system (TRAMS): double IMUs are comprised by the same accuracy grade inertial sensors; one IMU is assembled in the head nacelle, while the other is in the airframe; the double-IMUs tightly-coupled with the DPGS respectively can measure the attitudes (pitch, roll and heading) of the nacelle and helicopter airframe in high accuracy; the relative attitudes between the two single IMU/DPGS TRAMSs reflect the elastic deformation between the nacelle and airframe. The double-IMUs/DPGS TRAMS have been effectively verified through the ground experiment in a vehicle and two flight tests in a military helicopter. The results present satisfactory stability and repeatability. This system can be popularized to other dynamic deformation measurement backgrounds.     

基于 EM 估计的多模型车载组合导航算法

针对行车过程中车载全球卫星导航系统受遮挡产生多径效应、可见星数量少等影响,造成的定位精度差的问题,提出了 一种基于期望最大化(EM)的交互式多模型车载组合导航算法。 本文采用了混合高斯分布模型描述 GNSS 多径效应误差分布, 提出了基于 EM 的 SINS / GNSS 子系统组合导航信息融合方法,实现多径效应偏置误差的估计。 建立了基于零速约束的 SINS / OD 组合导航模型,同时利用交互式多模型算法实现了在 GNSS 信号丢失情况下的导航模型交互融合,提高了车载组合导航系 统精度。 车载实验结果表明在 GNSS 多径效应及信息丢失条件下,本文所提出算法能有效提高导航精度,多径效应的混合高斯 模型偏置为 10 m 条件下,偏置估计误差小于 0. 5 m,水平最大定位误差为 2 m,比传统交互式多模型算法定位误差降低 84. 62% 。     

大型散货堆体积的快速测量

针对现有散货测量系统对堆场环境适应性差、盘点时间长、效率低、操作复杂等不足,提出了一种散货堆体积快速测量方法。同时,利用二维激光扫描仪、差分GPS和姿态测量系统设计了一种体积测量系统。该系统用激光扫描仪动态测量堆体表面的几何信息,用姿态测量系统实时测量扫描仪的空间姿态数据,用GPS测出扫描仪在测量过程中的三维位置;最后通过数据融合计算形成堆体的三维点云,利用点云获得散货堆体积。文中基于单条堆体轮廓点云特征,提出快速堆体下边缘查找算法来去除扫描过程中地面点云的误差影响;采用投影剖分法完成完整堆体点云计算体积。实验显示,利用本文设计的测试系统可在30s内完成体积为69m3的标准堆体测量,平均相对误差为0.42%,重复测量误差为0.41%。在实际散货堆实验中,可在10min内完成大小约为31 500m3的散货堆测量,4个不同料堆体积测量的平均重复测量误差为0.74%。结果表明,本方法可在保证测量精度的同时,简单、高效地测量散货堆体积。     

激光雷达 / MEMS IMU/ 里程计紧组合导航算法

为提高机器人在未知复杂环境中导航系统的鲁棒性与稳定性,提出了一种激光雷达/ MEMS IMU/ 里程计紧组合导航 算法。 首先通过 MEMS IMU/ 里程计的预积分,对激光雷达运动产生的畸变点云进行矫正,提高两帧点云之间的特征匹配效 率;然后根据时间戳对预积分的机器人位姿进行线性插值,得到两帧点云之间粗略的位姿变化量,以此粗略的位姿变化量作 为优化算法迭代初值,减少优化算法的迭代次数;其次在后端优化中加入 MEMS IMU/ 里程计的运动约束,利用多传感器联合 优化来提高机器人的定位精度;最后利用数据集进行仿真实验、利用四轮小车开展了室内与室外开闭环实验,实验表明,本 算法室外开环定位误差均值比传统算法 ALOAM、LEGO-LOAM 分别减小 51. 01% 和 24. 75% ,并且其在拐弯等运动剧烈时能 够保持较高精度。     

Observability analysis of alignment errors in GPS/INS

Misalignment can be an important problem in the integration of GPS/INS. Observability analysis of the alignment errors in the integration of low-grade inertial sensors and multiantenna GPS is presented in this paper. A control-theoretic approach is adopted to study the observability of time-varying error dynamics models. The relationship between vehicle motions and the observability of the errors in the lever arm and relative attitude between GPS antenna array and IMU is given. It is shown that alignment errors can be made observable through maneuvering. The change of acceleration makes the components of the relative attitude error that are orthogonal to the direction of the acceleration change observable. The change of angular velocity makes the components of the lever arm error that are orthogonal to the direction of the angular velocity observable. The motion of constant angular velocity has no influence on the estimation of the lever arm.