Rapid Static Positioning Using a Four System GNSS Receivers in the Forest Environment

Abstract

Global Navigation Satellite Systems (GNSS) are crucial elements used in forest inventories. Forest metrics modeling efficacy depends on the accuracy of determining sample plot locations by GNSS. As of 2021, the GNSS consists of 120 active satellites, ostensibly improving position acquisition in forest conditions. The main idea of this article was to evaluate GIS-class and geodetic class GNSS receivers on 33 control points located in the forest. The main assumptions were operating on four GNSS systems (GPS, GLONASS, Galileo, and BeiDou), keeping a continuous online connection to the network of reference stations, maintaining occupation time-limited to 60 epochs, and repeating all the measurements three times. Rapid static positioning was tested, as it compares the true performance of the four GNSS systems receivers. Statistical differences between the receivers were confirmed. The GIS-class receiver achieved an accuracy of 1.38 m and a precision of 1.29 m, while the geodetic class receiver reached 0.74 m and 0.91 m respectively. Even though the research was conducted under the same data capture conditions, the large variability of positioning results were found to be caused by cycle slips and the multipath effect.

Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet

“…The u-blox ZED-F9P obtains signals in multiband from four global GNSS. Multi-GNSS contributes to increasing the continuity and integrity of positioning by the receivers, particularly in environments with obstacles [62,63]. The effect of receiver types on the accuracy of positioning was reported in earlier studies.…”

“…Tree's characteristics, such as height, volume, tree density and canopy may block or weaken the signals [70]. A closed canopy can cause cycle slips [63], which clogs the signals to reach the receivers. Our analyses demonstrated that the low-cost GNSS receiver continuously recorded the signals throughout the logging trails, and it was resistant against cycle slips effects.…”

A Study of Outliers in GNSS Clock Products

“…[1] raw clock data (phase data) [2] clock correction rate (frequency data) [3] outliers removal [4] jump detection and removal [5] polynomial trend removal [6] outliers removal (MAD method) The number of existing outliers in final clock products for each satellite and for each year was found. Outliers were removed using the MAD (median absolute deviation) method, and a criterion of 3 × MAD was adopted [27,28].…”

“…The first fully operable GNSS system was the American GPS (Global Positioning System) in operation since the 1990s, and the second was the Russian GLONASS, operational since 2011 [3]. The Chinese BeiDou system has also reached full operational capability (FOC) [4]. Currently, only Galileo does not have the planned number of operational satellites in orbit and is entering the FOC phase.…”

Evaluation of Static Autonomous GNSS Positioning Accuracy Using Single-, Dual-, and Tri-Frequency Smartphones in Forest Canopy Environments

“…However, measurements of smartphone positioning detected rapid Multipath variations over time [ 48 , 49 ]. Even when positioning was conducted using geodetic class receivers, considerable variability in positioning accuracies occurred due to the Multipath effect [ 50 ]. Additionally, the satellite constellations also do not behave in the same way.…”