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Keywords = INS-assisted navigation

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Article
Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume
by Shuai Jing, Xingqun Zhan, Baoyu Liu and Maolin Chen
Sensors 2016, 16(9), 1412; https://doi.org/10.3390/s16091412 - 2 Sep 2016
Cited by 13 | Viewed by 5779
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
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Figure 1
<p>The selection of CIT over different LOS jerks.</p> Full article ">Figure 2
<p>The maximum bearable LOS jerk under different C/N<sub>0</sub> for SSV RRAM.</p> Full article ">Figure 3
<p>Block diagrams of adaptive four-state KF-based tracking strategy.</p> Full article ">Figure 4
<p>Suggested architecture of INS-assisted open loop tracking.</p> Full article ">Figure 5
<p>Schematic diagram of the simulation scenario.</p> Full article ">Figure 6
<p>The variation of C/N<sub>0</sub> and LOS jerk for the established scenario. (<b>a</b>) Global view; and (<b>b</b>) close-up view of the second phase.</p> Full article ">Figure 7
<p>The distribution and connection of the instruments in the experiment. (<b>a</b>) Physical connection; and (<b>b</b>) schematic connection.</p> Full article ">Figure 8
<p>PLL lock status of two CL form tracking strategies, SSV RRAM and the adaptive KF-based method.</p> Full article ">Figure 9
<p>Comparison of the estimated Doppler frequency using different tracking schemes in the experiments. (<b>a</b>) Global view; (<b>b</b>) viewport of the second phase (non-maneuvering); (<b>c</b>) viewport of the third and fourth phase (maneuvering); and (<b>d</b>) close-up view around the 300th s.</p> Full article ">Figure 10
<p>Comparison of Doppler estimation errors using different tracking schemes in the experiments. (<b>a</b>) Global view; and (<b>b</b>) close-up view.</p> Full article ">
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