Abstract
The global navigation satellite system (GNSS) has been applied to many areas, e.g.,the autonomous ground vehicle, unmanned aerial vehicle (UAV), precision agriculture, smart city,and the GNSS-reflectometry (GNSS-R), being of considerable significance over the past few decades.Unfortunately, the GNSS signal performance has the high risk of being reduced by the environmentalinterference. The vector tracking (VT) technique is promising to enhance the robustness in highdynamics as well as improve the sensitivity against the weak environment of the GNSS receiver.However, the time-correlated error coupled in the receiver clock estimations in terms of the VT loopcan decrease the accuracy of the navigation solution. There are few works present dealing with thisissue. In this work, the Allan variance is accordingly exploited to specify a model which is expectedto account for this type of error based on the 1st-order Gauss-Markov (GM) process. Then, it is usedfor proposing an enhanced Kalman filter (KF) by which this error can be suppressed. Furthermore,the proposed system model makes use of the innovation sequence so that the process covariancematrix can be adaptively adjusted and updated. The field tests demonstrate the performance of theproposed adaptive vector-tracking time-correlated error suppressed Kalman filter (A-VTTCES-KF).When compared with the results produced by the ordinary adaptive KF algorithm in terms of the VTloop, the real-time kinematic (RTK) positioning and code-based differential global positioning system(DGPS) positioning accuracies have been improved by 14.17% and 9.73%, respectively. On the otherhand, the RTK positioning performance has been increased by maximum 21.40% when comparedwith the results obtained from the commercial low-cost U-Blox receiver.
Highlights
The architecture of the vector tracking (VT)-based software-defined receiver (SDR) is illustrated in Figure 1, where red lines denote the VT feedbacks, blue blocks represent the satellite vehicle (SV) ephemeris and the implementations which rely on ephemeris, DCM stands for the direction cosine matrix which includes unit vectors between the user and the line-of-sight (LOS) satellites, LR stands for the loop rate of the update
Since the VT architecture based on the weighted non-linear least square (WNLS) navigator is not our contribution, the system model associated with this algorithm can be referred to the conference paper [70], and it will not be investigated and stated in this work
An introduction related to the process of presenting the A-VTTCES-Kalman filter (KF) in this work is summarized in Figure 8, where the blocks associated with the dashed lines correspond to the preliminary work to build the system model of the A-VTTCES-KF; the solid lines correspond to the real-time field test process with the proposed global navigation satellite system (GNSS) SDR using the A-VTTCES-KF
Summary
The application of the global navigation satellite system (GNSS) has had considerable significance during the past two decades for positioning and navigation in terms of the autonomous ground vehicle [1,2,3,4], unmanned aerial vehicle (UAV) [5,6,7], precision farming [8,9,10,11], smart city relied on information and communication technology (ICT) [12,13,14] and internet of things (IoT) [15,16,17], as well as for the GNSS-reflectometry (GNSS-R) towards agriculture [18,19], forest monitoring [20], wind geophysical modeling [21], sea ice remote sensing [22], and its other improved algorithms [23,24]. The multipath interference forms another large challenge faced by the GNSS signal, since it randomly occurs It is a type of biased error source that is hard to be modelled as well [38,39,40,41]. The vector tracking (VT) technique is capable of remarkably improving the performance on the GNSS signal processing in weak and dynamic environments with the assistance of the position and velocity solutions. An introduction related to the process of presenting the A-VTTCES-KF in this work is summarized, where the blocks associated with the dashed lines correspond to the preliminary work to build the system model of the A-VTTCES-KF; the solid lines correspond to the real-time field test process with the proposed GNSS SDR using the A-VTTCES-KF. Both the PLL and delay lock loop (DLL) are working under the assistance of the VT algorithm
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