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Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume

机译:空间服务量中飞行任务的微弱和动态GNSS信号跟踪策略

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Weak-signal and high-dynamics are of two primary concerns of space navigation using GNSS (Global Navigation Satellite System) in the space service volume (SSV). The paper firstly defines a reference assumption third-order phase-locked loop (PLL) as the baseline of an onboard GNSS receiver, and proves the incompetence of this conventional architecture. Then an adaptive four-state Kalman filter (KF)-based algorithm is introduced to realize the optimization of loop noise bandwidth, which can adaptively regulate its filter gain according to the received signal power and line-of-sight (LOS) dynamics. To overcome the matter of losing lock in weak-signal and high-dynamic environments, an open loop tracking strategy aided by an inertial navigation system (INS) is recommended, and the traditional maximum likelihood estimation (MLE) method is modified in a non-coherent way by reconstructing the likelihood cost function. Furthermore, a typical mission with combined orbital maneuvering and non-maneuvering arcs is taken as a destination object to test the two proposed strategies. Finally, the experiment based on computer simulation identifies the effectiveness of an adaptive four-state KF-based strategy under non-maneuvering conditions and the virtue of INS-assisted methods under maneuvering conditions.
机译:弱信号和高动力是空间服务量(SSV)中使用GNSS(全球导航卫星系统)进行空间导航的两个主要问题。本文首先将参考假设三阶锁相环(PLL)定义为机载GNSS接收器的基线,并证明了这种传统架构的不足。然后,引入一种基于自适应四态卡尔曼滤波器(KF)的算法来实现环路噪声带宽的优化,该算法可以根据接收信号功率和视线动力学来自适应地调节其滤波器增益。为了克服在弱信号和高动态环境下失去锁定的问题,建议采用惯性导航系统(INS)辅助的开环跟踪策略,并在非惯性导航系统中修改传统的最大似然估计(MLE)方法重建似然代价函数的方法此外,结合轨道机动和非机动弧的典型任务被作为目标对象来测试这两种拟议的策略。最后,基于计算机仿真的实验确定了在非机动条件下基于自适应四态KF的策略的有效性以及在机动条件下INS辅助方法的优势。

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