Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service VolumeReport as inadecuate


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


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School of Aeronautics and Astronautics, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Shanghai 200240, China





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Academic Editor: Vittorio M. N. Passaro

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 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. View Full-Text

Keywords: GNSS; adaptive Kalman filter; INS-assisted navigation; maximum likelihood estimation; space service volume; Doppler frequency estimation GNSS; adaptive Kalman filter; INS-assisted navigation; maximum likelihood estimation; space service volume; Doppler frequency estimation





Author: Shuai Jing, Xingqun Zhan * , Baoyu Liu and Maolin Chen

Source: http://mdpi.com/



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