基于视线矢量测量的火星接近段自主导航算法

为了实现中国首次火星探测接近段的自主导航,设计一种基于视线矢量测量的自主导航算法,以测量火星视线单位矢量为唯一观测量,在轨道动力学及星-火间几何关系的基础上,详细推导出了探测器位置矢量模的表达式,并进一步推导出探测器位置及速度矢量的表达式,建立自主导航算法.通过仿真验证,分别对闭合轨道和双曲线轨道下基于三视线测量自主导航算法的表现进行比较分析.     

火星探测接近段的光学自主导航研究

目前光学自主导航技术已成为深空探测计划中的重点研究对象. 已有研究, 多侧重于光学自主导航技术在深空探测巡航段或是对小行星探测接近段中的应用, 而关于大行星探测接近段光学自主导航技术的研究比较少. 结合中国即将开展的火星探测计划, 研究了探测器在火星探测接近段中利用火星进行光学自主导航的整个过程, 提出了适用于接近段的动力学模型、光学观测模型及自主导航滤波算法. 通过对自主导航系统的可观测性分析, 证明了仅利用火星光学信息进行自主导航的可行性. 仿真计算结果表明, 在接近段, 整个光学自主导航的持续时间约为40h. 在自主导航的最后5h内, 滤波结果稳定, 探测器的总体位置误差在40km以内, 速度误差在0.25m·s^-1以内. 计算结果的精度满足实际任务需求, 对中国火星探测计划具有直接的参考价值.     

火星探测巡航段天文自主导航方法研究

对于火星探测巡航段的自主导航问题,提出了一种基于太阳及行星观测的自主导航方法。在巡航段初期及后期,根据探测器在太阳系中的位置关系,分别选择太阳、地球及太阳、火星作为观测目标,采用星载太阳敏感器和光学相机测量导航天体实现矢量,建立观测方程。利用非线性扩展卡尔曼滤波,分别建立两种观测方案对应的导航算法。仿真结果表明巡航段导航定位精度优于100 km,定速精度1 m/s。该方法实现简单,系统资源要求不高,对未来火星探测具有一定的工程参考价值。     

基于视线矢量的深空自主导航算法研究

针对深空探测器在行星际飞行的轨道确定问题, 研究了一种基于视线矢量的自主导航算法. 结合深空探测任务的特点, 以太阳视线矢量和地球视线矢量作为导航系统的观测量, 在详细分析太阳敏感器测量原理的基础上, 给出了太阳视线矢量的观测模型及其观测误差表达式. 通过分析导航相机观测原理, 给出像元像线观测模型, 并推导了地球视线矢量的观测误差. 根据惯性空间内视线矢量间的几何关系, 详细推导了探测器的位置矢量及其误差表达式, 结合非线性扩展卡尔曼滤波建立自主导航算法. 利用深度撞击任务的实际飞行数据对本文提出的深空自主导航算法进行了仿真验证.     

火星着陆自主导航方案研究进展

火星着陆导航技术是火星着陆过程的核心技术之一。围绕火星着陆环境特点与导航技术遇到的挑战,分析了目前火星着陆过程的导航能力和自主导航的发展趋势,并针对火星着陆过程的特殊性和导航需求,概述了火星着陆过程各阶段自主导航方案的研究现状与进展。进而从导航方案设计与配置、导航模型建立与仿真、导航方案性能分析等方面,对自主导航方案的最新研究进展进行了分析,并在火星着陆全过程自主导航方案综合仿真的基础上,获得了满足火星定点着陆要求的各阶段交接点应满足的导航精度。最后,基于目前技术现状和发展趋势,提出了构建"递进式三阶段"火星着陆自主导航方案的设想,可为未来火星着陆自主导航方案的设计与论证提供参考。     

火星探测器自主导航方法综述

火星是人类深空探测的重要目标之一,火星探测器的自主导航是探测任务的重要支撑技术。针对火星探测器自主导航方法的国内外研究现状进行综述与总结,讨论和分析了火星探测器自主导航可行的导航信标和测量手段,对自主导航算法需要研究的关键技术进行了梳理和探讨,提出了火星探测器在巡航段、捕获段和环绕段等不同阶段场景下的测量手段、自主导航方法的建议和设想。     

基于ASUKF的火星探测器脉冲星自主导航方法

脉冲星导航可靠、稳定、精度高, 是实现火星探测器自主导航的有效手段之一.针对脉冲星导航中脉冲到达时间的微小误差会引起巨大的位置估计误差这一问题,提出了一种基于扩维Unsented卡尔曼滤波(ASUKF,Augmented State Unscented Kalman Filter)的火星探测器脉冲星自主导航方法,建立了以位置、速度和脉冲到达时间的常值测量误差作为状态量的导航系统数学模型,可在对探测器位置、速度进行估计的同时有效估计并修正脉冲到达时间的常值测量误差,并降低随机测量误差的影响.仿真结果表明该方法的导航定位精度可达350m以内,可以满足火星探测自主导航的需要.     

火卫二地形地貌探测综述

火卫二(Deimos)是火星自然卫星之一,研究人员利用火星探测器对其地形地貌开展了大量研究.首先对火卫二的基本参数及起源假说进行了介绍,进而全面梳理了与火卫二相关的航天探测活动,重点对地形地貌探测活动进行了详细介绍,并对围绕火卫二地形地貌的研究成果进行了归纳分析,结果表明火卫二表面分布有撞击坑、风化层、明亮的反射物质及...     

深空探测航天器巡航段自主导航方法研究

对深空探测航天器自主导航方法进行了研究。为了应对深空探测中航天器轨道动力学模型的误差,在分光计测量航天器相对于太阳径向速度基础上,引入了小行星的视线矢量测量。通过最小二乘法计算出由小行星视线矢量所得到的位置信息,采用改进的信息融合方法修正扩展卡尔曼滤波中不精确的动力学模型造成的状态估计误差。同时计算了模型的能观度,对模型的可观性进行了分析。最后对算法进行了仿真分析,仿真结果表明,该算法对动力学模型的依赖性明显低于其他算法,在相同模型精度下,可获得更好的滤波精度。     

火星车自主导航与路径规划技术研究

针对火星车工作任务环境,借鉴国外成功研究经验,给出了火星车自主导航敏感器配置,研究可在实际工程中应用的火星车自主导航与路径规划技术,包括DEM图构建与障碍物检测、全局路径规划、基于立体视觉相机的视觉里程计、多传感器融合位姿确定以及局部路径规划技术,并搭建了实验系统,在实验室内进行了仿真验证。相关研究结果可为我国后续开展火星车自主导航系统研究提供一定的基础。     

Autonomous navigation of Mars probe using X-ray pulsars: Modeling and results

Autonomous navigation of Mars probe is a main challenge due to the lack of dense ground tracking network measurements. In this paper, autonomous navigation of the Mars probe Orbits is investigated using the X-ray pulsars. A group of X-ray pulsars with high ranging accuracy are selected based on their properties and an adaptive extended Kalman filter is developed to incorporate the Mars probe dynamics and pulsar-based ranging measurements. Results of numerical experiment show that the three-dimensional positioning accuracy can achieve 750m in X-axis, 220m in Y-axis and 230m in Z-axis, which is much better than the positioning results by current Very Long Baseline Interferometry (VLBI) or Doppler observations with the accuracy of 150 km or several kilometers, respectively.     

MCAV/IMU integrated navigation for the powered descent phase of Mars EDL

Pin-point landing is considered as a key technology for future manned Mars landing and Mars base missions. The traditional inertial navigation system (INS) based guidance, navigation and control (GNC) mode used in the Mars entry, descent and landing (EDL) phase has no ability to achieve the precise and safe Mars landing, so novel EDL GNC methodologies should be investigated to meet this goal. This paper proposes the MCAV/IMU integrated navigation scheme for the powered descent phase of Mars EDL. The Miniature Coherent Altimeter and Velocimeter (MCAV) is adopted to correct the inertial bias and drift and improve the performance of integrated navigation. Altitude and velocity information derived from MCAV and the lander’s state information sensed by inertial measurement unit (IMU) are integrated in extended Kalman filter algorithm. The validity of the proposed navigation scheme is confirmed by computer simulation.     

An innovative navigation scheme of powered descent phase for Mars pinpoint landing

Pinpoint landing (within 100 m from the target) is essential for future Mars exploration missions. This paper deals with one aspect of the pinpoint landing architecture—the navigation performance improvement during the powered descent phase, and proposes an innovative navigation scheme to obtain the vehicle complete and accurate states. On the basis of dead reckoning relying on the Inertial Measurement Unit, measurements of the Integrated Doppler Radar are adopted to correct the vehicle velocity and altitude. Distance between the vehicle and one Mars Orbiter as well as their line-of-sight relative velocity is measured by a radio sensor, and integrated in the filter to correct the vehicle horizontal position. The innovative navigation system is based on an Extend Kalman Filter. Two observation schemes are developed. One considers measurements of the Integrated Doppler Radar and radio range measurement. Another further considers radio velocity measurement. The performance of the innovative navigation scheme is greatly influenced by the position of the Mars Orbiter with respect to the target. Stochastic analyses are performed to obtain optimal locations of Mars Orbiter. Finally, the innovative navigation scheme performances are assessed through stochastic simulations. Its performance improvements are demonstrated by comparison with the Integrated Doppler Radar only navigation scheme.     

Radio beacons/IMU integrated navigation for Mars entry

High precision entry navigation capability is essential for future Mars pinpoint landing missions, together with the entry guidance and aerodynamic lift control. This paper addresses the issue of Mars entry navigation using inertial measurement unit (IMU) and orbiting or surface radiometric beacons. The range and Doppler information sensed from orbiting or surface radio beacons and the entry vehicle state information derived from IMU are integrated in Unscented Kalman filter to correct the inertial constant bias and suppress the navigation measurement noise. Computer simulations show that the integrated navigation algorithm proposed in this paper can achieve 50 m position error and 2 m/s velocity error, which satisfies the need of future pinpoint Mars landing missions.     

月球探测器天文导航的遗传粒子滤波方法

天文导航系统是典型的非线性和噪声非高斯分布的系统.针对传统的扩展卡尔曼滤波不适于非线性和噪声非高斯分布的系统,和一般粒子滤波存在的粒子退化和采样枯竭问题,提出了一种基于遗传算法进行再采样的月球探测器自主天文导航粒子滤波新方法.计算机仿真结果显示了该方法可以有效的克服传统粒子滤波方法的缺点,提高天文导航系统的定位精度.