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SXblue GPS GNSS

1-800-463-4363

CASE STUDY ON ACCURACY OF SXBLUE MODULAR GPS / GLONASS RECEIVER

Duluth Laboratories & Administration 5013 Miller Trunk Highway Duluth, Minnesota 55811 Coleraine Laboratories One Gayley Avenue P.O. Box 188 Coleraine, Minnesota 55722

By Michael Joyce, Ph.D. Ron Moen, Ph.D. Report Number: NRRI/TR -2018/28, Release 1.0





SUMMARY


One of the main factors that affect GPS location accuracy is the type of GPS receiver being used. In general, more expensive receivers (e.g., mapping-grade or survey-grade receivers) provide better accuracy, and GPS users must balance GPS receiver cost with location accuracy when determining which receiver to use. Applications of GPS often require use of GPS receivers in less than ideal conditions while GPS manufacturers often report accuracy specifications that can be expected under ideal conditions. Forest canopies reduce GPS accuracy by interfering with signal transmission between GPS satellites and the GPS receiver and causing multipath errors. When GPS receivers are to be used in forest conditions and accuracy thresholds must be met, it is important to conduct accuracy testing in forest conditions rather than relying on accuracy specifications provided by the manufacturer.


We tested the accuracy of the SXBlue II + GNSS, a modular, mapping-grade GPS receiver, under forest canopies in northeastern Minnesota. We estimated cumulative accuracy to evaluate the relationship between collection period and accuracy. GPS test sites covered a range of canopy conditions. We compared accuracy among sites to determine how canopy closure influenced location accuracy. Finally, we compared post-hoc methods to evaluate accuracy based on characteristics of the sites and acquired GPS fixes. The SXBlue II + GNSS receiver typically provided meter or sub-meter accuracy, even under forest canopy. Maximum accuracy was achieved after 10- 30 minutes. Accuracy was lower at sites with higher canopy closure values. In sites with canopy closure >65%, maximum accuracy was reduced to 1.5 m. Post-hoc filtering to remove outliers did not improve accuracy. There was a strong, positive relationship between 50% CEP, a measure of location precision, and accuracy, suggesting that 50% CEP can be used for post-hoc accuracy assessment. Our results suggest that the SXBlue II + GNSS provides sufficient accuracy for a wide range of applications, including those that require GPS location measurement in forest conditions


This report and any future updates can be downloaded from the University of Minnesota Digital Conservancy (https://conservancy.umn.edu). For questions related to NRRI reports, contact us @ nrrireports@umn.edu. Web site: http://www.nrri.umn.edu ©2018 by the Regents of the University of Minnesota


INTRODUCTION


With the increasing availability of LiDAR data for forestry and wildlife applications, precise geographic positioning is critical to ensure features of interest (e.g., field plot locations, animal locations, etc.) can be compared directly with the corresponding LiDAR data or derived products. Spatial overlap is affected by both global positioning system (GPS) accuracy and horizontal accuracy of LiDAR data. GPS accuracy is usually a bigger source of positional error (White et al. 2013). LiDAR data often have horizontal accuracy within 1 meter. Relatively inexpensive recreation-grade (also known as consumer-grade) GPS receivers typically have THE accuracy of about 9 meters when used under closed forest canopy (Wing and Eklund 2007, Wing 2008).

Survey-grade GPS receivers can achieve centimeter-level accuracy, but tend to be cost-prohibitive for many applications (Laes et al. 2011, White et al. 2013). Guidelines for forest inventory modeling using LiDAR typically recommend using mapping-grade GPS receivers capable of obtaining locations with sub-meter accuracy under forest canopy (Laes et al. 2011). Mapping-grade receivers cost less than survey-grade receivers, and they can typically achieve sub-meter to 2 m accuracy (White et al. 2013). Modular mapping-grade GPS receivers now available are less expensive but still as accurate.


GPS position error is typically caused by interference with the signal being broadcast from the satellite and received by the GPS unit. Given that the GPS satellites are about 20,000 km above the earth, it is not surprising that interference occurs. Forest canopies obstruct the signal, especially when moisture is present (Johnson and Barton 2004, Edson and Wing 2012), and can also reflect the signal and cause multipath interference in which the receiver has difficulty identifying the signal amongst the noise (Wing 2008). For these reasons, using GPS in forested environments is often associated with reduced accuracy. One solution to improve accuracy is to use differential correction with a base station. If a base station is located at a known location the error in the position can be calculated, although base stations are not typically located under a forest canopy. If the same satellites are used, the error should be the same at the unknown location where a GPS unit is, and the result of this differential correction is higher precision. Differential GPS approaches include both real-time differential correction, for which the GPS unit receives corrections in real time from a base station, and post-processing when corrections are applied after the GPS data have been acquired.


Another solution to reduce GPS error is the use of Space-Based Augmentation Systems (SBAS), such as the Wide Area Augmentation System (WAAS) that covers Central and North America. SBAS utilizes a network of ground reference stations with known locations which provide information to a master station that calculates corrections that can be applied over a wide area. SBAS calculates separate correction factors for different error sources (e.g., ionospheric errors, GPS satellite timing errors, GPS satellite orbit errors) rather than calculating the total effect of these factors. Corrections are broadcast using a constellation of geostationary satellites, allowing use of SBAS for real-time correction without the need for communicating with a differential GPS base station.


Our objectives were to test the accuracy of a modular, mapping-grade GPS receiver under forest canopies in northeastern Minnesota. The GPS receiver we tested is capable of sub-meter GPS accuracy under ideal conditions but has not been tested in conditions under a forest canopy. We (1) evaluated the relationship between the length of the data collection period and accuracy, (2) identified the effect of tree canopy closure on the accuracy, and (3) tested potential post-hoc methods to evaluate accuracy based on site characteristics or GPS data. Our results are specific to the receiver and software that we used, but could logically be extended to other GPS units in similar conditions.


METHODS

Field Testing


We tested the horizontal accuracy of the SXBlue II + GNSS receiver (Geneq Inc., Montreal, Quebec, Canada), a compact Global Navigation Satellite System (GNSS) receiver. In ideal conditions with an unobstructed view of the sky, the SXBlue II + GNSS should provide sub-meter horizontal accuracy 95% of the time (Geneq Inc., 2014). In many locations the view of the sky is obstructed by trees, hillsides, or other structures. We determined expected accuracies when using the SXBlue II receiver under forest canopy.


The SXBlue II + GNSS receiver uses conventional real-time differential corrections obtained from a Space Based Augmentation System (SBAS) to improve position accuracy. The SXBlue II + GNSS unit receives location information from both GPS and GLONASS satellite constellations. Use of both satellite systems improves accuracy and reduces the chance that poor satellite geometry will reduce position accuracy by increasing the number of satellites that are available to determine the position.


The SXBlue II + GNSS receiver is one component of a modular system to collect location information at a field site (Fig. 1). The two other required components of the system are data acquisition hardware and data collection software. Many types of computers can be used as the acquisition hardware, including smart phones, laptops, PDA, and tablets. There are also options for data collection software, including free mobile applications, ArcGIS Collector, and Microsoft Windows-compatible software. Data collection software acquires data from one of 3 available communication options: (1) Bluetooth port (Class 1), (2) USB Port (Type B, female port), and (3) RS-232 Serial Port.


Figure 1. Components of the system we used:




We used a tablet (Samsung Galaxy Tab A) and mobile applications to collect location data at test sites using the SXBlue II + GNSS receiver. We used the ‘Bluetooth GPS’ application (Version 1.3.7, GG MobLab) to establish a Bluetooth connection between the receiver and the tablet, and the ‘GPSlogger’ application (Version 91, Mendhak) to collect location information. Both mobile applications are available free of char