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This paper deals with the relative navigation of a formation of two spacecrafts separated by hundreds of kilometers based on processing dual-frequency differential carrier-phase GPS measurements. Specific requirements of the considered application are high relative positioning accuracy and real-time on board implementation. These can be conflicting requirements. Indeed, if on one hand high accuracy can be achieved by exploiting the integer nature of double-difference carrier-phase ambiguities, on the other hand the presence of large ephemeris errors and differential ionospheric delays makes the integer ambiguities determination challenging. Closed-loop schemes, which update the relative position estimates of a dynamic filter with feedback from integer ambiguities fixing algorithms, are customarily employed in these cases. This paper further elaborates such approaches, proposing novel closed loop techniques aimed at overcoming some of the limitations of traditional algorithms. They extend techniques developed for spaceborne long baseline relative positioning by making use of an on-the-fly ambiguity resolution technique especially developed for the applications of interest. Such techniques blend together ionospheric delay compensation techniques, nonlinear models of relative spacecraft dynamics, and partial integer validation techniques. The approaches are validated using flight data from the Gravity Recovery and Climate Experiment (GRACE) mission. Performance is compared to that of the traditional closed-loop scheme analyzing the capability of each scheme to maximize the percentage of correctly fixed integer ambiguities as well as the relative positioning accuracy. Results show that the proposed approach substantially improves performance of the traditional approaches. More specifically, centimeter-level root-mean square relative positioning is feasible for spacecraft separations of more than 260 km, and an integer ambiguity fixing performance as high as 98% is achieved in a 1-day long dataset. Results also show that approaches exploiting ionospheric delay models are more robust and precise of approaches relying on ionospheric-delay removal techniques. 相似文献
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Global navigation satellites of the European Galileo system transmit code signals on four carriers in the L1, E5a, E5b and E6 band.New geometry-free linear combinations are presented that eliminate the geometry terms (user to satellite ranges and orbital errors), the clock errors of the user and satellites and the tropospheric delay. The remaining parameters of these carrier phase combinations include integer ambiguities, ionospheric delays, carrier phase multipath and phase noise. The weighting coefficients are designed such that the integer nature of ambiguities is maintained. The use of four frequency combinations is highly recommended due to a noise reduction of up to 14.4 dB and an ionospheric reduction of up to 25.6 dB compared to two frequency geometry-free combinations.Moreover, a modified Least-squares Ambiguity Decorrelation Adjustment (LAMBDA) algorithm is suggested, which differs in two points from the traditional approach: the baseline is replaced by the ionospheric delay and the correlation is caused by linear combinations instead of double differences. For correct ambiguity resolution, the ionospheric delay can be determined with millimeter accuracy. This is quite beneficial as the ionosphere represents the largest source of error for absolute positioning. 相似文献
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提出了一种利用广义卡尔曼滤波进行GPS/INS组合导航的技术 ,同时给出了一种最优选星算法。采用间接的反馈校正设置 ,直接利用伪距数据和不受噪声污染的星历数据。利用该方法 ,组合导航精度高 ,在导航过程中若丢失GPS信息 ,短时间内单纯INS的导航精度仍能保持。恢复GPS信号后组合系统继续正常工作。 相似文献
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针对时变拓扑卫星集群的相对导航需求,提出了基于图论的时变拓扑分布式一致性无迹卡尔曼滤波算法。首先给出了固定拓扑卫星集群的相对运动方程、测角测距测量模型和无迹卡尔曼滤波算法,然后考虑测角失效时相对导航系统不可观或弱可观的问题,结合矢量环一致性约束,构造了一致性无迹卡尔曼滤波算法,以提高系统的可观度;在此基础上,针对时变拓扑卫星集群,以滤波精度为优化指标,在图论的基础上利用Dijkstra算法对卫星集群的时变拓扑结构进行重构,并将重构后的拓扑结构应用于卫星集群相对导航。仿真结果表明所提算法能有效改善不完备测量带来的模糊轨道问题,并且能够实现实时的拓扑重构,以满足时变拓扑星群的相对导航精度要求。 相似文献
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适于惯导系统初始对准的神经网络实时算法研究 总被引:3,自引:0,他引:3
通常卡尔曼滤波器被用于解决惯导系统的初始对准问题。由于卡尔曼滤波的运算时间与系统阶次的立方成正比 ,所以当系统阶次较高时 ,滤波器会失去实时性。而神经网络具有函数逼近性能 ,实时性又好。为此 ,本文研究了一种基于扩展卡尔曼滤波原理的权值更新多层神经网络学习算法 ,对此算法进行了详细的推证 ,并将该算法运用到惯导系统的初始对准过程。仿真结果表明了这种神经网络结构用于惯导系统初始对准问题的有效性 ,既真正获得了与扩展卡尔曼滤波器相同的对准精度 ,又大大提高了系统的实时性 相似文献
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针对传统的利用单一视觉传感器难以实现复杂非合作空间操控导航的问题,提出一种基于单目相机与无扫描三维激光雷达融合的非合作目标相对位姿估计方法。首先,设计了基于成像几何关系的单目纹理-非扫描距离图像的快速配准与融合方法;之后,在构建目标同步定位与建图(SLAM)贝叶斯滤波模型基础上,提出一种扩展卡尔曼滤波-无损卡尔曼滤波-粒子滤波联合的滤波估计算法,可实现尺度模糊下相对位姿的快速鲁棒估计;其次,针对估计中的尺度模糊问题,提出基于融合图像的全局尺度系数确定方法,将尺度系数估计问题转化为简单线性滤波问题。基于OpenGL生成的2D/3D图像实验表明:所提出的方法具有较优的精度和鲁棒性;相对位置估计误差与尺度估计误差相关,二者近似成线性正比关系。 相似文献
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This paper studies the autonomous navigation method for a group of satellites based on relative position measurements, which can be obtained by using inter-satellite links for measuring relative range and navigation star sensors for measuring relative bearing. For the satellites that are far from each other, it may be difficult to obtain relative bearing measurement due to poor visibility. To address this difficulty, this paper proposes a novel scheme, where three satellites, whose relative ranges are rather small such that the relative bearings can be observed, are used as beacons for the navigation of the other satellites that are invisible. The feasibility of the proposed navigation scheme is analyzed by using the Cramer-Rao lower bound (CRLB), with the consideration of the availability of relative bearing measurements. In addition, the multiple model adaptive estimation (MMAE) algorithm is adopted to improve the convergence speed of the estimator in the presence of large initial errors. Simulation results illustrate the high performance of the proposed scheme. 相似文献
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一种提高导航卫星星座自主定轨精度的方法研究 总被引:1,自引:0,他引:1
针对近地导航卫星仅利用星间测距进行自主定轨时,因无法消除星座整体旋转误差而导致长期自主定轨精度不高的问题,提出了利用拉格朗日导航卫星星座与近地导航卫星星座联合仅利用星间测距进行自主定轨的方法。建立了拉格朗日轨道导航卫星星座和近地导航卫星星座联合仅利用星间测距进行自主定轨的动力学模型和观测模型。利用扩展Kalman滤波(EKF)算法和星间测距信息实现了拉格朗日轨道导航星座与近地导航星座的长期自主定轨。以4颗拉格朗日卫星组成的导航星座与12颗GPS卫星组成的近地导航星座作为仿真对象进行了仿真分析,仿真结果表明本文仅利用星间测距的联合自主定轨方法可以有效提高导航卫星星座的长期自主定轨精度。 相似文献
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以惯性导航系统输出的数据作为辅助信息 ,对 GPS完善性监测算法进行了研究。该法以卡尔曼滤波新息序列为依据 ,对 GPS卫星的伪距测量值是否出现故障进行的检测 ,并给出了计算机仿真算例。仿真结果表明 :该方法能够及时准确地检测出 GPS故障星 相似文献
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基于模糊自适应卡尔曼滤波的INS/GPS 组合导航系统算法研究 总被引:15,自引:2,他引:15
针对车载组合导航系统量测噪声统计特性随实际工作条件的不同而变化的特点,提出了一种基于模糊自适应卡尔曼滤波的车载INS/GPS组合导航算法。该方法通过监视理论残差与实际残差的比值是否在一附近,应用模糊推理系统不断的调整量测噪声协方差阵的加权,对卡尔曼滤波的量测噪声协方差阵进行递推在线修正,使其逐渐逼近真实噪声水平,从而使滤波器执行最优估计,提高导航系统的精度。对车载组合导航系统的仿真结果表明,这种算法对时变的量测噪声具有较强的自适应性,进而精度比常规卡尔曼滤波也大为提高,是一种可行的车载组合导航算法。 相似文献
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为实现主从式卫星编队飞行中心星与环绕星的自主定轨,采用微波雷达测量卫星间相对距离、距离速率、方位角和仰角。根据动力学方程给出了导航算法,并利用扩展卡尔曼滤波(EKF)提高微波雷达相对速度的测量精度。仿真结果表明,该导航算法对主从式卫星编队较有效,且能获得较佳的导航精度。 相似文献
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GPS/INS组合导航系统的平滑滤波应用研究 总被引:3,自引:0,他引:3
在一些特殊应用场合,采用平滑滤波的处理方法,可以大大改善GPS/INS组合导航系统的定位精度。有关飞行器精密定位参照系统的事后处理算法,平滑滤波的算法,与卡尔曼滤波器的关系,以及在GPS/INS组合导航系统中平滑滤波的实现技术,在本文中作了讨论并给出了系统的原理结构和仿真方法。仿真结果表明平滑滤波精度比卡尔曼滤波器的精度提高一倍左右,是一种有效的事后处理技术。 相似文献