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51.
针对超低轨道地球卫星导航自主需求,提出了一种脉冲星/星光折射/光谱测速组合天文导航方法。首先根据地球超低轨道卫星运行轨道动力学方程建立导航系统状态模型;分别根据脉冲到达时间差和星光折射角与天体光谱频率建立导航系统量测模型;使用Unscented卡尔曼滤波方法,降低随机误差对导航精度的影响,使用基于UKF的信息融合方法,有效融合了三种天文导航方法结果数据。经计算机仿真分析,该组合导航方法位置导航误差均值为85.62m,速度误差均值0.190m/s,能够满足超低轨道地球卫星在轨运行导航需求。 相似文献
52.
为了解决探测器在月面工作时惯性导航系统的误差累积问题,克服现有研究对环境敏感或是需要定期停止才能进行误差修复的短板,结合探测器的行驶行为,将探测器使用零速更新(ZUPT)原理修正误差的过程分解成了无ZUPT、完全ZUPT、水平动态ZUPT和垂向动态ZUPT 4种子模型的叠加,并分别推导了它们的系统矩阵和测量矩阵。针对月面导航系统提出了一种新型多模型零速更新(MMZUPT)算法。该算法应用多模型交互原理,允许多种更新模型同时工作,可以通过计算每个模型的权重在每个定位历元输出最优导航结果并约束误差。在精心挑选的受限环境中对月面导航进行了模拟实验,结果表明,所提MMZUPT方法无需频繁地主动停车以满足传统ZUPT使用边界就可以取得良好的效果,并且通过对包含错误的校准信号加以识别和利用可以获得更好的性能。 相似文献
53.
惯性推算误差抑制是提升复杂场景下组合导航定位性能的关键,现有采用运动约束或系统误差高阶建模的方法从运动学模型及传感器误差模型出发,通过经验确定参数及模型的最优解。深度学习隐式模型能够挖掘数据之间的隐含关系,进行自主化参数寻优,并在提升惯导误差建模精度方面具有一定优势。总结了现有主流网络模型设计的优缺点,通过对比不同的输入输出方案进行优选,最终利用卷积神经网络构建了一套惯性误差抑制的轻量化神经网络自学习模型,并利用实测车载数据验证了该模型的有效性。实验结果表明,在GNSS信号失锁300 s的路段I和失锁285 s的路段II,网络模型速度约束的算法相较于纯惯性推算和传统NHC算法均有一定提升,融合NHC及网络模型速度约束的算法在水平定位精度上分别改善了41.7%~47.4%和26.7%~36.6%,一定程度上抑制了惯性推算误差。 相似文献
54.
G. Gaias J.-S. Ardaens C. Colombo 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2021,67(11):3515-3526
This work presents a precise analytical model to reconstruct the line-of-sight vector to a target satellite over time, as required by angles-only relative navigation systems for application to rendezvous missions. The model includes the effects of the geopotential, featuring: the analytical propagation in the mean relative orbital elements (up to second-order expansion), the analytical two-way osculating/mean orbital elements’ conversion (second-order in and up to a given degree and order of the geopotential), and a second-order mapping from the perturbed osculating elements’ set to the local orbital frame. Performances are assessed against the line-of-sight reconstructed out of the precise GPS-based positioning products of the PRISMA mission. The line-of-sight modelled over a far-range one day long scenario can be fitted against the true one presenting residuals of the order of ten arc-seconds, which is below the typical sensor noise at far-range. 相似文献
55.
《中国航空学报》2016,(3):746-753
X-ray pulsar-based navigation (XPNAV) is an attractive method for autonomous deep-space navigation in the future. The pulse phase estimation is a key task in XPNAV and its accuracy directly determines the navigation accuracy. State-of-the-art pulse phase estimation techniques either suffer from poor estimation accuracy, or involve the maximization of generally non-convex object function, thus resulting in a large computational cost. In this paper, a fast pulse phase estimation method based on epoch folding is presented. The statistical properties of the observed profile obtained through epoch folding are developed. Based on this, we recognize the joint prob-ability distribution of the observed profile as the likelihood function and utilize a fast Fourier transform-based procedure to estimate the pulse phase. Computational complexity of the proposed estimator is analyzed as well. Experimental results show that the proposed estimator significantly outperforms the currently used cross-correlation (CC) and nonlinear least squares (NLS) estima-tors, while significantly reduces the computational complexity compared with NLS and maximum likelihood (ML) estimators. 相似文献
56.
Chi-Ming Lee Chung-Yen Kuo Jian Sun Tzu-Pang Tseng Kwo-Hwa Chen Wen-Hau Lan C.K. Shum Tarig Ali Kuo-En Ching Philip Chu Yuanyuan Jia 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2019,63(3):1280-1288
Global sea level rise due to an increasingly warmer climate has begun to induce hazards, adversely affecting the lives and properties of people residing in low-lying coastal regions and islands. Therefore, it is important to monitor and understand variations in coastal sea level covering offshore regions. Signal-to-noise ratio (SNR) data of Global Navigation Satellite System (GNSS) have been successfully used to robustly derive sea level heights (SLHs). In Taiwan, there are a number of continuously operating GNSS stations, not originally installed for sea level monitoring. They were established in harbors or near coastal regions for monitoring land motion. This study utilizes existing SNR data from three GNSS stations (Kaohsiung, Suao, and TaiCOAST) in Taiwan to compute SLHs with two methods, namely, Lomb–Scargle Periodogram (LSP)-only, and LSP aided with tidal harmonic analysis developed in this study. The results of both methods are compared with co-located or nearby tide gauge records. Due to the poor quality of SNR data, the worst accuracy of SLHs derived from traditional LSP-only method exceeds 1?m at the TaiCOAST station. With our procedure, the standard deviations (STDs) of difference between GNSS-derived SLHs and tide gauge records in Kaohsiung and Suao stations decreased to 10?cm and the results show excellent agreement with tide gauge derived relative sea level records, with STD of differences of 7?cm and correlation coefficient of 0.96. In addition, the absolute GNSS-R sea level trend in Kaohsiung during 2006–2011 agrees well with that derived from satellite altimetry. We conclude that the coastal GNSS stations in Taiwan have the potential of monitoring absolute coastal sea level change accurately when our proposed methodology is used. 相似文献
57.
针对复合壳阻尼结构的拓扑减振优化问题,以约束阻尼层的有限单元为设计变量,采用体积比、模态频率和振型为优化约束条件,构建以多模态权重系数的结构模态损耗因子数值关系为优化目标函数的拓扑减振优化模型。为了拓展优化目标灵敏度具有不局限于某一变密度法插值模型的形式,推导了数值表达式的一般函数式。动力学优化中优化目标灵敏度正、负数集共存,使得非凸性的目标函数设计变量出现负值或优化函数寻优于局部极值点。为此,推导出复合壳阻尼结构的全域灵敏度改进优化准则法迭代格,以确保每次迭代域均为全域设计变量集。结合有限单元法编程实现了复合壳阻尼结构改进准则法,并对复合壳结构进行拓扑减振优化分析。结果表明:在敷设体积减为全覆盖的50%时,复合壳结构的模态损耗因子增减偏差为10%,具有提升减振的轻量化设计目的;各阶目标函数和拓扑构型所需的迭代次数少,中间密度区域较小,多阶优于单阶模态优化函数,易于获得全域寻优的有效减振。 相似文献
58.
59.
采用高精度卫星导航速度、位置信息以及星敏感器提供的姿态信息设计十表冗余捷联惯组的标定模型,包含陀螺和加速度计的零次项和标度因数,对卫星和星敏感器辅助的冗余激光陀螺捷联惯组进行实时在轨标定.利用标准Kalman滤波和Sage-Husa自适应滤波作为估计算法,对十表冗余捷联惯组参数进行在线估计.数值仿真结果表明:参数标定精度均在7%以内,是一种实时的在轨标定方法,满足误差补偿要求.冗余惯组在轨标定方法为航天器高精度定姿和定轨提供了一种理论参考. 相似文献
60.