Open AccessGNSS velocimeter by adaptively combining carrier phase and Doppler measurements
Author(s) -
Zhang Laihong,
Chang Guobin,
Chen Chao,
Zhang Siyu,
Zhu Ting
Publication year - 2020
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2018.5674
Subject(s) - gnss applications , doppler effect , kalman filter , computer science , control theory (sociology) , kinematics , global positioning system , velocimetry , noise (video) , algorithm , physics , artificial intelligence , telecommunications , optics , classical mechanics , astronomy , image (mathematics) , control (management)
In order to use a stand‐alone global navigation satellite system (GNSS) receiver to determine the stable instantaneous velocity, a new hybrid GNSS velocimetry approach combining carrier phase and Doppler measurements is proposed. This is a data fusion problem. The problem is expressed as a state‐space model, in which the deviation between the average velocity determined by the time difference carrier phase approach and the instantaneous velocity is represented by the uncertainty of the state model. In kinematic applications, this uncertainty is often variant and hard to be known in advance, a predefined process noise level of the state model is often not sufficiently accurate in the whole working time. Here, an adaptive Kalman filtering approach is employed to fix this problem. To verify the proposed approach, one static experiment and two dynamic experiments with different sampling intervals are performed, separately. All results demonstrate the validity and stability of the proposed approach.