CC BY
7УДК 528.01/.06
Rakhmatullayev A.A.
Master's student in scientific and pedagogical direction S. Seifullin Kazakh Agro Technical Research University (Astana, Kazakhstan)
AN ANALYSIS OF THE ACCURACY GPS TO IMPROVE THEIR PERFORMANCE
Аннотация: this article investigates the factors affecting the accuracy of Global Positioning System (GPS) technology, particularly in high-precision applications such as geodesy, surveying, and autonomous systems. GPS accuracy is influenced by satellite geometry, atmospheric interference, multipath effects, and the quality of the receiver. This analysis highlights methods to enhance GPS precision, including Differential GPS (DGPS), Real-Time Kinematic (RTK) positioning, and satellite-based augmentation systems (SBAS). The study compares GPS performance in urban and rural environments, demonstrating significant accuracy challenges in urban areas due to signal obstructions and reflections. Advanced correction techniques and the integration of multiple GNSS constellations (e.g., GPS, GLONASS, Galileo) are recommended to mitigate these issues, ensuring reliable performance in precision-dependent fields. As technology advances, innovations such as machine learning and multi-constellation systems will further enhance GPS accuracy, expanding its applications across various industries.
Ключевые слова: geodesy, GPS, remote sensing, Data Collection Methods, surveying
methods.
INTRODUCTION.
Global Positioning System (GPS) technology is a cornerstone of modern navigation, positioning, and timing applications across a broad range of industries. From everyday personal navigation to highly specialized fields like surveying, cartography, and scientific research, GPS plays a crucial role in determining accurate location data. However, GPS is not infallible. While it offers reliable positioning, the precision of GPS can be influenced by a variety of factors, leading to discrepancies in
location accuracy. These discrepancies are critical in applications where precision is essential, such as geodesy, autonomous systems, and land surveying.
Understanding the variables that affect GPS accuracy is crucial for improving the reliability of this technology. As industries increasingly rely on highly accurate GPS data, the need to assess and enhance its precision becomes more pressing. This analysis explores the factors that impact GPS accuracy, including satellite geometry, atmospheric interference, and receiver quality. We also examine methods designed to improve GPS accuracy, such as Differential GPS (DGPS) and Real-Time Kinematic (RTK) positioning, and discuss the implications for advanced applications in mapping, navigation, and autonomous technologies.
GPS is a satellite-based navigation system that provides location and time information in all weather conditions, anywhere on Earth, where there is an unobstructed line of sight to four or more GPS satellites. GPS receivers on the ground capture signals from these satellites and use the time delay of the received signals to calculate the user's position. This system has become vital to numerous fields and industries.
For instance, in agriculture, GPS technology supports precision farming by enabling tractors to follow pre-determined paths, optimizing land use and resource distribution. In cartography, GPS data is crucial for creating accurate maps of terrain, cityscapes, and infrastructure. Similarly, in logistics and transportation, GPS ensures the real-time tracking of goods, vehicles, and shipments, leading to more efficient supply chains. Additionally, it plays a key role in emergency services, military operations, and autonomous vehicle systems, which require precise location data for safety and functionality. Yet, the varying accuracy of GPS, due to multiple external factors, means that its application in high-stakes contexts necessitates deeper understanding and improvement.
The accuracy of GPS is impacted by several critical factors, one of the most significant being the geometry of the satellites used to calculate a receiver's position. The geometric dilution of precision (GDOP) quantifies the effect that satellite positions have on the precision of location estimates. When satellites are widely spaced, the
positioning accuracy is higher, as the triangulation of signals is more precise. However, if the satellites are clustered together or located at low angles relative to the receiver, the GDOP increases, leading to greater uncertainty in the calculated position. This issue is particularly pronounced in urban environments where tall buildings or natural features obstruct satellite signals, a phenomenon commonly referred to as the "urban canyon" effect. In such cases, only a limited number of satellites may be visible, which reduces the accuracy of the GPS position.
Multipath interference is another factor that can significantly degrade GPS accuracy. This occurs when GPS signals bounce off surfaces such as buildings, bodies of water, or other reflective structures before reaching the receiver. When these reflected signals combine with direct signals from the satellite, they can distort the time delay measurement, causing errors in the calculated position. Multipath interference is especially problematic in built-up areas or near large natural features like mountains, where multiple reflective surfaces are present. This issue can be partially mitigated by using advanced receivers that are capable of distinguishing between direct and reflected signals or by employing ground-based augmentation systems.
The atmosphere also plays a vital role in GPS accuracy. GPS signals pass through the Earth's ionosphere and troposphere, layers of the atmosphere that can cause delays and signal distortions. In the ionosphere, charged particles can slow down the GPS signals, introducing delays that result in inaccurate distance measurements. These delays vary depending on solar activity and the time of day. Similarly, the troposphere, which contains the Earth's weather systems, can also affect GPS signals, as variations in temperature, pressure, and humidity can alter the speed at which the signals travel. Techniques such as ionospheric and tropospheric modeling are often employed to correct for these atmospheric effects, though some residual errors can persist.
Another factor influencing GPS accuracy is the quality of the receiver. GPS receivers come in a wide range of designs, with varying levels of sophistication. Highend receivers, such as those used in geodesy and surveying, have advanced processing capabilities that allow them to mitigate many of the errors caused by satellite geometry,
multipath interference, and atmospheric conditions. These receivers can employ techniques like signal averaging and the use of multiple frequency bands to improve accuracy. By contrast, consumer-grade receivers, such as those found in smartphones, tend to have lower accuracy due to their limited processing power and sensitivity. However, even consumer devices have seen significant improvements in accuracy due to technological advancements in recent years.
To achieve greater accuracy, particularly in applications where even small deviations can have significant consequences, various techniques have been developed. Differential GPS (DGPS) is one such method. DGPS involves the use of ground-based reference stations, which broadcast correction signals to GPS receivers. These corrections account for errors caused by satellite orbit inaccuracies, clock errors, and atmospheric conditions. By comparing the known position of the reference station with the position calculated by GPS, the system can determine and correct errors, leading to much more accurate location data. DGPS is commonly used in surveying, aviation, and marine navigation, where higher precision is required.
Another highly effective technique for improving GPS accuracy is Real-Time Kinematic (RTK) positioning. RTK uses the phase of the carrier wave, rather than just the timing information of the GPS signal, to calculate a much more precise position. By using a base station with a known location and a moving receiver, RTK can achieve centimeter-level accuracy in real time. This method is widely used in applications such as precision agriculture, autonomous vehicles, and construction site surveying, where precise positioning is critical.
In addition to these techniques, satellite-based augmentation systems (SBAS) such as the European Geostationary Navigation Overlay Service (EGNOS) and the Wide Area Augmentation System (WS) provide additional correction data to improve GPS accuracy. These systems use a network of ground stations to monitor GPS signals and calculate corrections, which are then transmitted to users via geostationary satellites. These augmentation systems are especially useful for aviation, where safety-critical operations require highly accurate and reliable positioning data.
GPS accuracy is influenced by a complex interplay of factors, including satellite geometry, signal interference, atmospheric effects, and receiver quality. Understanding these influences is critical for improving the reliability of GPS in various industries, from everyday navigation to precision-dependent fields like surveying, autonomous vehicle operation, and geodesy. Techniques such as Differential GPS, Real-Time Kinematic positioning, and satellite-based augmentation systems have significantly enhanced the precision of GPS, enabling its use in more demanding applications. As technology continues to advance, further improvements in GPS accuracy are expected, opening up new possibilities for its application across multiple domains.
ANNOTATED BIBLIOGRAPHY.
Research on GPS and GNSS positioning accuracy covers a variety of approaches, from traditional correction methods to modern solutions using machine learning. The 2021 article examines the use of dual-frequency Android smartphones to evaluate GNSS accuracy, focusing on the limitations of pseudo-dimensional measurements and real-time calls. In contrast, the 2023 review on Precise Point Positioning (PPP) focuses on sophisticated technologies and demonstrates how PPP can achieve centimeter accuracy, which is especially important for professional applications such as geodesy and agriculture.
The latest research also brings innovative approaches such as machine learning to improve GPS accuracy. The 2023 paper examines various machine learning algorithms that offer improved accuracy of vehicle tracking data, which could be an alternative to more expensive GNSS devices. A similar article on machine learning for IoT applications shows that this method can be applied to a wide range of networks and devices, expanding the scope of GPS correction.
Earlier work focused on traditional correction methods such as differential GPS (DGPS) and real-time correction systems (RTK). A 2016 study on long-term accuracy tests of marine DGPS reveals how system performance changes over time depending on conditions. Meanwhile, the 2021 work on PPP and GNSS correction models in the
context of RTK demonstrates how high accuracy can be achieved in real-time in real-world settings such as agriculture.
Other sources address narrower topics, such as underwater navigation systems, where traditional GPS technologies face major challenges. A 2016 study highlights the specific difficulties of GPS operation in underwater environments and suggests methods to improve accuracy in such environments. While articles focused on the statistical distribution of navigation errors and data filtering techniques (such as the Kalman filter) offer a deeper understanding of how errors can be analyzed and corrected in real time.
METHODS AND MATERIALS.
The GPS accuracy analysis was conducted to evaluate how different environments affect the precision of GPS readings. Two types of environments were selected for this study: urban and rural. These two settings were chosen due to their varying levels of potential obstructions to GPS signals, such as buildings, trees, and open spaces. The urban area included locations with tall buildings, narrow streets, and other structures that could block or reflect satellite signals, creating multipath errors. In contrast, the rural area was characterized by large, open fields with minimal obstructions, providing an ideal setting for GPS signal reception.
To measure GPS accuracy, data was collected using two devices: a handheld GPS receiver and a smartphone with built-in GPS functionality. Both devices supported multiple Global Navigation Satellite System (GNSS) constellations, including GPS, GLONASS, and Galileo. Using multiple GNSS constellations is known to enhance accuracy by increasing the number of visible satellites and improving signal redundancy.
At each study site, GPS readings were collected at predetermined points, such as survey benchmarks with known coordinates, to allow for an accurate comparison. Data collection occurred at various times of the day, including early morning, midday, and late afternoon, to account for fluctuations in satellite visibility and geometry, which can affect GPS accuracy. Additionally, environmental factors, such as cloud cover,
temperature, and wind speed, were recorded to assess the influence of weather on signal reception.
Two types of accuracy were measured: horizontal and vertical. Horizontal accuracy refers to the difference in the horizontal (X-Y plane) position between the measured GPS coordinates and the known coordinates. Vertical accuracy refers to the difference in elevation (Z-axis) between the measured and known values. Both types of errors were calculated for each data point, and multiple readings were taken at each location to determine the consistency of the measurements.
The Root Mean Square Error (RMSE) was used as the primary metric for evaluating GPS accuracy. RMSE quantifies the differences between predicted and observed values and provides a measure of the overall accuracy of the system. This metric is especially useful for identifying the magnitude of errors across multiple data points.
The results showed a clear difference in GPS accuracy between rural and urban environments.
In rural areas, where open spaces allowed for unobstructed GPS signal reception, the average horizontal error was found to be between 2 and 3 meters. The variation between measurements was relatively small, indicating consistent accuracy across multiple readings. Vertical accuracy in rural areas was also high, with an average error of 3 meters. These results suggest that GPS performs well in open environments with minimal interference from structures or natural obstacles.
In urban areas, the GPS accuracy was significantly lower due to the presence of tall buildings and other obstructions that reflected or blocked satellite signals. The average horizontal error in urban areas was found to be between 5 and 7 meters. Additionally, the vertical error in these areas increased, with some readings showing errors as high as 7 meters. The accuracy was especially poor in locations surrounded by tall buildings, where multipath effects caused by signal reflection off building surfaces contributed to the inaccuracy.
The time of day also played a role in GPS accuracy. Readings taken during early morning and late afternoon, when satellite visibility was optimal, were generally
more accurate than those taken during midday. This is due to the geometry of the satellites, as the relative positions of satellites affect the dilution of precision (DOP). A low DOP value, indicating a wider spread of satellites in the sky, generally leads to better accuracy, which was more common during the early morning and late afternoon hours.
This analysis demonstrate the significant impact that environmental factors have on GPS accuracy. In rural areas with minimal obstructions, GPS devices were able to achieve relatively high levels of accuracy. This was due to the clear line of sight between the GPS receiver and the satellites, allowing for uninterrupted signal reception and minimal multipath errors. However, in urban environments, GPS accuracy suffered considerably due to signal obstruction and reflection caused by buildings, narrow streets, and other urban structures. Multipath errors, which occur when signals reflect off surfaces before reaching the receiver, were particularly problematic in densely built-up areas, resulting in higher horizontal and vertical errors.
The findings also suggest that using multiple GNSS constellations (such as GPS, GLONASS, and Galileo) improves overall accuracy, especially in rural areas where signals from different constellations can enhance satellite availability and reduce errors. However, in urban areas, even multiple GNSS constellations were not sufficient to completely mitigate the issues caused by signal reflection and obstruction. This indicates that while GNSS technology continues to improve, additional methods such as differential GPS (DGPS) or Real-Time Kinematic (RTK) systems may be necessary for achieving high accuracy in urban environments.
The influence of time of day on GPS accuracy was another notable finding. Satellite geometry and visibility vary throughout the day, affecting the overall precision of the system. The results showed that GPS readings were generally more accurate during early morning and late afternoon, when satellite visibility was more favorable, as indicated by lower DOP values.
If GPS accuracy is generally reliable in open, rural areas, urban environments pose significant challenges due to obstructions and multipath effects. Future improvements in GPS technology, such as the integration of additional satellite
constellations, better algorithms to correct for multipath errors, or complementary technologies like DGPS, will be essential for enhancing accuracy in complex urban settings.
CONCLUSION.
GPS technology has evolved into a critical tool for various industries, providing essential location and time data in diverse applications, from everyday navigation to high-precision fields like surveying and autonomous systems. However, as demonstrated in this analysis, the accuracy of GPS is subject to significant environmental influences such as satellite geometry, atmospheric conditions, and signal interference. Urban environments, in particular, present unique challenges due to signal obstruction and reflection, leading to greater inaccuracies.
The research findings underline the importance of employing advanced techniques like Differential GPS (DGPS), Real-Time Kinematic (RTK) positioning, and multi-constellation GNSS systems to enhance GPS accuracy, especially in environments where precision is critical. While rural areas with minimal obstructions show higher accuracy levels, urban settings continue to necessitate more sophisticated correction methods to mitigate signal degradation caused by multipath errors and obstructions.
Future research and technological advancements should focus on improving GPS performance in complex environments, exploring machine learning models, and integrating more satellite constellations. Such innovations will further enhance GPS accuracy, allowing for broader and more reliable use in fields that demand precise geolocation data. This work lays the foundation for ongoing efforts to refine GPS systems, providing a roadmap for future exploration and technological improvement.
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