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1.
本文阐述了利用X射线脉冲星实现航天器姿态确定的成像仪定姿、探测器扫描定姿和垂直双矢量相对定位姿态的3种方法,介绍了其基本原理;分析了3类方法与现有姿态确定方法相比存在的优势;并利用仿真数据分析了垂直双矢量相对定位姿态确定方法;研究了时延测定误差、可观测脉冲星数、脉冲星历表误差等对姿态确定精度的影响,得出了有益的结论.  相似文献   

2.
X射线脉冲星单星动力学定轨   总被引:1,自引:0,他引:1  
基于单脉冲星的动力学定轨,在X射线脉冲星导航技术尚不成熟时具有较强的实用价值.将X射线脉冲星观测方程与航天器动力学模型相结合,系统研究了利用X射线脉冲星观测量进行单星动力学定轨的方法原理.利用仿真数据量化分析了各项因素对定轨精度的影响,指出X射线脉冲星方向单位向量越靠近航天器轨道面单星定轨位置精度越差.因此提出了单探测器轮流观测多颗脉冲星的准多星定轨方法,从而使定轨精度由km量级提高到了20 m.  相似文献   

3.
针对移动测量系统对载体姿态的需求,对车载三天线全球卫星导航系统(global navigation satellite system,GNSS)的直接法定姿进行了研究。分析了定姿的原理,给出了姿态解算公式,并提出一种简便的方法确定航向角的象限,解决了航向角的多值性问题。为了评估该方法的精度,利用车载的三天线GNSS进行了动态实验,采集了动态观测数据,利用直接法对观测数据进行了姿态解算,并用同车搭载的一套高精度惯性导航系统(inertial navigation system,INS)给出的姿态参考值对三天线GNSS定姿的精度和可靠性进行了评估。结果表明,三天线GNSS直接法定姿精度高、可靠性好,并具有计算简便,可避免奇异性问题等优点。  相似文献   

4.
现行X射线脉冲星导航方法中存在两种固有误差,源于推算太阳系质心在当前时刻接收脉冲的相位以及将航天器固有时转换成太阳系质心坐标时。针对这一情况,文章根据相对论定位系统的基本思想和后牛顿引力理论,导出了X射线脉冲星导航的4维观测方程。相对于现行的3维观测方程,新方法只需根据航天器测量脉冲轮廓的相位即可完成航天器定位,不必考虑太阳系质心处的光子到达时间因而不必推算该处观测者在当前时刻的脉冲轮廓相位;也不必进行航天器固有时与质心坐标时的转换因而不必预先估计航天器的运动状态。新方法简单易行,能够有效地减小测量误差,建议在X射线脉冲星导航中取代现行观测方程。  相似文献   

5.
针对车载移动测量系统对运动载体姿态的确定,研究车载全球卫星导航系统(GNSS)天线阵列定姿方法,分析直接法和最小二乘法定姿的姿态解算公式,并进行GNSS天线阵列车载实验. 为得到两种定姿方法的精度,在不同软件定位模式解算的基础上,利用直接法和最小二乘法进行了姿态解算. 实验和分析结果表明:四天线阵列最小二乘法定姿精度优于三天线阵列直接法,可靠性更高;在所有组合中,基于Moving-base定位模式的四天线阵列最小二乘法定姿精度最高,其航向角、俯仰角和横滚角精度分别可达0.066 0°、0.168 4°和0.267 8°.   相似文献   

6.
首先介绍定姿的关键问题、常用定姿方法的分类及其特点。然后详细分析了常用的两种最优化定姿算法以及它们存在的问题,并提出一种新的最优化定姿方法。文中详细叙述了推导过程以及解算的步骤,为了对新方法进行验证,使用仿真数据对所提方法的罚函数和解算精度进行了详细分析。结果表明本文所提方法和其它两种最优化方法的定姿结果一致,都具有很高的定姿精度。本文所提方法由于不需要对矩阵进行奇异值分解或计算出所有特征值和特征向量,因此对计算机要求比较低,易于编程实现。  相似文献   

7.
针对滤波和优化融合算法在不同场景下定位性能不明确的问题,该文构建了一种融合先验点云地图、激光雷达(LiDAR)、惯性测量单元(IMU)的位姿估计框架。对比分析了基于图优化和误差状态卡尔曼滤波(ESKF)两种算法的位姿估计精度,并采用3组KITTI数据进行实验分析。结果表明:图优化算法的绝对位姿误差的均方根小于ESKF算法,3组数据的精度分别提升了28.9%、12.5%和21%;在复杂场景下,基于图优化算法的性能高于滤波算法;在简单场景下,滤波和图优化算法的精度接近,而滤波算法更加稳定。  相似文献   

8.
X射线脉冲星导航中脉冲轮廓的频偏和时延算法   总被引:1,自引:1,他引:0  
观测轮廓与标准轮廓的频率偏差和时间延迟是X射线脉冲星导航的两个观测量,讨论其计算方法并提出如下改进意见:①对探测器的最小分辨时间作进一步的时间细分,在每一个小的时间间隔内接收的光子数可以假设满足二项分布,再对观测轮廓叠加可以求得更高精度的频偏;②将实际观测轮廓分为理想轮廓及其偏差两部分,而TOA是指理想轮廓与标准轮廓的时延,Sala等人提出的用相关函数求TOA方法仅对理想轮廓成立;③如果实际轮廓在测量过程中形状不变,则偏差产生的TOA估计误差为一常数。在此基础上提出实际观测轮廓的TOA估计方法,其计算精度小于探测器的最小分辨率。  相似文献   

9.
惯性测量单元(IMU)受自身温度、零偏、振动等因素干扰,积分时位姿容易发散,并且机器人快速移动时,单目视觉定位精度较差,为此研究了一种基于紧耦合的视觉惯性即时定位与地图构建(SLAM)方法. 首先研究了视觉里程计(VO)定位问题,为减少特征点的误匹配,采用基于快速特征点提取和描述的算法(ORB)特征点的提取方法. 然后构建IMU的数学模型,使用中值法得到运动模型的离散积分. 最后将单目视觉姿态与IMU轨迹对齐,采用基于滑动窗口的非线性优化得到机器人运动的最优状态估计. 通过构建仿真场景以及与单目ORB-SLAM算法对比两个实验进行验证,结果表明,该方法优于单独使用VO,定位精度控制在0.4 m左右,相比于传统跟踪模型提高30%.   相似文献   

10.
FAST对馈源舱精调机构的位姿测量提出了极高的精度要求。本文介绍了由全站仪组成的精调机构测量系统,计算了全站仪跟踪观测棱镜时的主要观测条件,包括棱镜入射角、观测距离和观测高度角,并进行了棱镜初始指向的优化配置。结果表明,棱镜入射角的最大值约为35°,平均值约为13°~18°,由此产生的测量误差可以忽略;观测距离约为140~350 m,估算全站仪动态测距精度约为2.1~2.4 mm;观测高度角约为0~40°,分布合理,且有利于全站仪的防护。仿真测量结果表明,9个测站的定位精度优于2.5 mm,定姿精度优于360";6个测站的定位精度优于3 mm,定姿精度优于430",均达到精调机构的位姿测量精度要求。  相似文献   

11.
针对单目视觉定位方法定位精度高但数据源不稳定,而惯性测量组件可稳定获取定位数据却存在累计误差的问题,提出了一种融合惯导信息的单目视觉室内定位方法.该方法利用四参数拟合模型将图像数据转换成定位定姿数据,并在惯导数据解算过程中引入互补滤波修正陀螺仪读数,最后将处理后的数据作为观测值输入到扩展卡尔曼滤波器中,得到最优位置信息.实验结果表明,该方法能够有效地提高室内定位的精度和稳定性.   相似文献   

12.
Georeferencing is one of the most important tasks in photogrammetry. Traditionally it has been achieved indirectly using the well-known method of aerial triangulation. With the availability of integrated GPS and inertial measurement units (IMU), this situation changed. Direct determination of exterior orientation is now possible. Today, direct and integrated sensor orientation is used for a wide range of sensors including lidar and SAR, as well as for digital line scanner systems and aerial cameras. This paper investigates the performance of direct and integrated sensor orientation for large scale mapping using the data-set of the 'Integrated Sensor Orientation' test of the European Organisation for Experimental Photogrammetric Research (OEEPE—now known as EuroSDR). The concept, potential, problems and solutions of direct and integrated sensor orientation are discussed.  相似文献   

13.
Enhanced MEMS-IMU/odometer/GPS integration using mixture particle filter   总被引:2,自引:2,他引:0  
Dead reckoning techniques such as inertial navigation and odometry are integrated with GPS to avoid interruption of navigation solutions due to lack of visible satellites. A common method to achieve a low-cost navigation solution for land vehicles is to use a MEMS-based inertial measurement unit (IMU) for integration with GPS. This integration is traditionally accomplished by means of a Kalman filter (KF). Due to the significant inherent errors of MEMS inertial sensors and their time-varying changes, which are difficult to model, severe position error growth happens during GPS outages. The positional accuracy provided by the KF is limited by its linearized models. A Particle filter (PF), being a nonlinear technique, can accommodate for arbitrary inertial sensor characteristics and motion dynamics. An enhanced version of the PF, called Mixture PF, is employed in this paper. It samples from both the prior importance density and the observation likelihood, leading to an improved performance. Furthermore, in order to enhance the performance of MEMS-based IMU/GPS integration during GPS outages, the use of pitch and roll calculated from the longitudinal and transversal accelerometers together with the odometer data as a measurement update is proposed in this paper. These updates aid the IMU and limit the positional error growth caused by two horizontal gyroscopes, which are a major source of error during GPS outages. The performance of the proposed method is examined on road trajectories, and results are compared to the three different KF-based solutions. The proposed Mixture PF with velocity, pitch, and roll updates outperformed all the other solutions and exhibited an average improvement of approximately 64% over KF with the same updates, about 85% over KF with velocity updates only, and around 95% over KF without any updates during GPS outages.  相似文献   

14.
Differential carrier phase observations from GPS (Global Positioning System) integrated with high-rate sensor measurements, such as those from an inertial navigation system (INS) or an inertial measurement unit (IMU), in a tightly coupled approach can guarantee continuous and precise geo-location information by bridging short outages in GPS and providing a solution even when less than four satellites are visible. However, to be efficient, the integration requires precise knowledge of the lever arm, i.e. the position vector of the GPS antenna relative to the IMU. A previously determined lever arm by direct measurement is not always available in real applications; therefore, an efficient automatic estimation method can be very useful. We propose a new hybrid derivative-free extended Kalman filter for the estimation of the unknown lever arm in tightly coupled GPS/INS integration. The new approach takes advantage of both the linear time propagation of the Kalman filter and the nonlinear measurement propagation of the derivative-free extended Kalman filter. Compared to the unscented Kalman filter, which in recent years is typically used as a superior alternative to the extended Kalman filter for nonlinear estimation, the virtue of the new Kalman filter is equal estimation accuracy at a significantly reduced computational burden. The performance of the new lever arm estimation method is assessed with simulated and real data. Simulations show that the proposed technique can estimate the unknown lever arm correctly provided that maneuvers with attitude changes are performed during initialization. Field test results confirm the effectiveness of the new method.  相似文献   

15.
卫星导航系统和惯性导航系统(INS)具有极强的互补性,两者组合能有效提高导航定位结果的可用性、连续性和可靠性. 随着北斗卫星导航系统(BDS)的快速发展和低成本惯导元件(IMU)性能的不断提高,进行基于BDS和低成本IMU的组合导航系统相关理论和技术研究具有很强的研究意义和实用价值. 本文首先对BDS RTK/M-EMS INS组合理论模型进行推导,并利用实测车载数据对组合系统的性能进行分析. 实验结果表明,在BDS中引入低成本IMU,可以在不损失定位精度的同时有效改善测速精度. 组合后在车载动态中定位精度影响为mm级,而速度误差改善在北、东、地方向达到了75.8%、79.5%、66.7%. 此外,在BDS+INS紧组合中使用双频数据可以改善测速定姿精度,速度误差改善为18.2%、33.3%、33.3%,姿态误差改善为41.1%、26.7%、59.0%.   相似文献   

16.
针对低动态高抖动环境下,影响GPS/INS紧组合精度的重要因素——惯性测量单元(IMU)数据中的噪声,该文提出利用小波降噪方法分离IMU数据中的噪声和有用信号以提高GPS/INS紧组合的精度。首先对IMU数据进行小波分解后得到的高频系数进行阈值量化处理,然后将GPS观测数据与降噪后的IMU数据进行GPS/INS紧组合解算,最终得到载体的导航信息。实例结果表明,该方法可以大幅提升GPS/INS紧组合的精度和稳定可靠性。  相似文献   

17.
Due to their complementary features of GPS and INS, the GPS/INS integrated navigation system is increasingly being used for a variety of commercial and military applications. An attitude determination GPS (ADGPS) receiver, with multiple antennas, can be more effectively integrated with a low-cost IMU since the receiver gives not only position and velocity data but also attitude data. This paper proposes a low-cost attitude determination GPS/INS integrated navigation system. The proposed navigation system comprises an ADGPS receiver, a navigation computer unit (NCU), and a low-cost commercial MEMS IMU. The navigation software includes a fault detection and isolation (FDI) algorithm for integrity. In order to evaluate the performance of the proposed navigation system, two flight tests have been performed using a small aircraft. The first flight test confirmed the fundamental operation of the proposed navigation system and the effectiveness of the FDI algorithm. The second flight test evaluated the performance of the proposed navigation system and demonstrated the benefit of GPS attitude information in a high dynamic environment. The flight test results show that the proposed ADGPS/INS integrated navigation unit gives reliable navigation performance even when anomalous GPS data is provided and gives better navigation performance than a conventional GPS/INS unit.  相似文献   

18.
CNS+GNSS+INS船载高精度实时定位定姿算法改进研究   总被引:2,自引:1,他引:1  
天文导航(CNS)、卫星导航(GNSS)和惯性导航(INS)3种系统组合可提供高精度的定位定姿结果。实际工程中因INS长时间误差累积,以及系统硬件传输存在不可忽略的时间延迟,导致INS提供给CNS的预报粗姿态误差较大,恶劣海况下难以保障快速搜星,造成天文导航可靠性下降、姿态测量精度较低的问题。为此,本文提出了一种CNS+GNSS+INS高精度信息融合实时定位定姿框架,引入了等角速度外推措施,有效地解决了惯导信息延迟问题。通过高精度转台模拟恶劣海况下载体大角速度摇摆,验证了本文提出的改进算法的有效性。试验结果表明,该算法架构简单,性能可靠,显著提高了恶劣环境下星敏感器的快速、准确搜星能力,保障了三组合姿态测量的精度和可用性。  相似文献   

19.
激光SLAM移动机器人室内定位研究   总被引:3,自引:1,他引:2  
针对目前室内移动导航定位精度低和累积误差大的问题,提出了一种激光雷达(LiDAR)和惯性测量单元(IMU)相融合的导航定位系统。首先,该方法是从LiDAR扫描测量中提取环境特征和构建地图,然后,由IMU采集的姿态信息通过卡尔曼滤波,补偿由于LiDAR扫描引起的位置和姿态输出的误差,以提高机器人移动的定位精度。试验结果表明,该方法可以提高室内移动机器人定位和构建地图的精度和稳健性。  相似文献   

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