Evaluating the Repeatability of RTK GPS

Pirti, Atınç

doi:10.1179/003962611x12894696204984

Cited by 10 publications

(8 citation statements)

References 2 publications

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“…In a ground-based augmentation system (GBAS), correction messages are transmitted to the end user via radio or mobile data network [ 63 ]. Real-time kinematic (RTK) positioning is a GBAS differential correction method in which one or more base (reference) stations at fixed, precisely-surveyed locations are used to improve the accuracy of mobile rover units [ 63 , 66 , 67 ]. Specifically, both the reference and rover units receive pseudorange and carrier phase measurements from similar satellites, which allows common errors between the units to be estimated and used to correct the rover’s accuracy in real time [ 66 , 67 ].…”

Section: Types Of Positioning Technologiesmentioning

confidence: 99%

“…Real-time kinematic (RTK) positioning is a GBAS differential correction method in which one or more base (reference) stations at fixed, precisely-surveyed locations are used to improve the accuracy of mobile rover units [ 63 , 66 , 67 ]. Specifically, both the reference and rover units receive pseudorange and carrier phase measurements from similar satellites, which allows common errors between the units to be estimated and used to correct the rover’s accuracy in real time [ 66 , 67 ]. Real-time kinematic is typically built into survey-grade devices, enabling them to achieve centimeter-level accuracy in unobstructed conditions (see Table 1 ) [ 29 ] and is integrated into heavy equipment for road construction ( Figure 3 , right panel) [ 68 , 69 ].…”

Section: Types Of Positioning Technologiesmentioning

confidence: 99%

“…Real-time kinematic is typically built into survey-grade devices, enabling them to achieve centimeter-level accuracy in unobstructed conditions (see Table 1 ) [ 29 ] and is integrated into heavy equipment for road construction ( Figure 3 , right panel) [ 68 , 69 ]. Real-time kinematic methods improve accuracy under the canopy as well, but are not immune to multipath error inherent in forests; therefore, positioning accuracies are lower (about 1 m) in these highly reflective environments [ 29 , 63 , 66 ].…”

Section: Types Of Positioning Technologiesmentioning

confidence: 99%

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Positioning Methods and the Use of Location and Activity Data in Forests

Keefe

Wempe

Becker

et al. 2019

Forests

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In this paper, we provide an overview of positioning systems for moving resources in forest and fire management and review the related literature. Emphasis is placed on the accuracy and range of different localization and location-sharing methods, particularly in forested environments and in the absence of conventional cellular or internet connectivity. We then conduct a second review of literature and concepts related to several emerging, broad themes in data science, including the terms location-based services (LBS), geofences, wearable technology, activity recognition, mesh networking, the Internet of Things (IoT), and big data. Our objective in this second review is to inform how these broader concepts, with implications for networking and analytics, may help to advance natural resource management and science in the future. Based on methods, themes, and concepts that arose in our systematic reviews, we then augmented the paper with additional literature from wildlife and fisheries management, as well as concepts from video object detection, relative positioning, and inventory-tracking that are also used as forms of localization. Based on our reviews of positioning technologies and emerging data science themes, we present a hierarchical model for collecting and sharing data in forest and fire management, and more broadly in the field of natural resources. The model reflects tradeoffs in range and bandwidth when recording, processing, and communicating large quantities of data in time and space to support resource management, science, and public safety in remote areas. In the hierarchical approach, wearable devices and other sensors typically transmit data at short distances using Bluetooth, Bluetooth Low Energy (BLE), or ANT wireless, and smartphones and tablets serve as intermediate data collection and processing hubs for information that can be subsequently transmitted using radio networking systems or satellite communication. Data with greater spatial and temporal complexity is typically processed incrementally at lower tiers, then fused and summarized at higher levels of incident command or resource management. Lastly, we outline several priority areas for future research to advance big data analytics in natural resources.

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Section: Types Of Positioning Technologiesmentioning

confidence: 99%

Section: Types Of Positioning Technologiesmentioning

confidence: 99%

Section: Types Of Positioning Technologiesmentioning

confidence: 99%

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Positioning Methods and the Use of Location and Activity Data in Forests

Keefe

Wempe

Becker

et al. 2019

Forests

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“…A well‐known limitation of the global navigation satellite system (GNSS) is that it is often impossible to obtain accurate coordinates within forests (Pirti et al., 2010). Thus, obtaining accurate positioning data in forests remains a challenge.…”

Section: The Nature 40 Projectmentioning

confidence: 99%

Nature 4.0: A networked sensor system for integrated biodiversity monitoring

Zeuss,

Bald,

Gottwald

et al. 2023

Global Change Biology

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Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade‐off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real‐world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low‐cost, and open‐source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area‐wide ecosystem mapping tasks, thereby providing an exemplary cost‐efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystems and the provision of ecosystem services.

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“…To avoid this, CORS FKP surveys have been done on the open area side of the border with the goal of giving precise observations to improve the GNSS receiver's communications with satellites. The points whose coordinates are being calculated was established at the forested area side, and CORS FKP surveys and static GNSS surveys were also conducted (Pirti 2010). The data collection and processing speed for CORS-FKP surveys was set to 1 second and 5 epochs with a 10 degree elevation mask angle.…”

Section: Study Areamentioning

confidence: 99%

Network Real Time Kinematic (Cors-FKP Method) Accuracy in/Under Forest Area

Pirti¹,

Kurtulgu²

2023

AgricultForest

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The use of Global navigation satellite system (GNSS), (geolocation and navigation system) in/under forestry is increasingly being established, especially in the areas of logistics, inventory and measurements. However, the uninitialized forest user assumes that GNSS will always work with the same accuracy everywhere, while the more critical foresters assume that GNSS will probably not work properly in/under the forest. A criterion is often used to evaluate the performance of a GNSS receiver in an obstructed environment. Due to tree canopy in a forest, GNSS performance can be limited, disturbed or completely prevented. The Real Time Kinematics (RTK) approach can provide centimetrelevel accuracy in a suitable environment. A more accurate and stable positioning technique was first proposed in the mid-1990s by meticulously modelling all fault components based on a known reference network called the Network Based RTK (NRTK) technique. Since then, several methods have been developed and implemented in practice, such as the Virtual Reference Station (VRS), the Flächen Korrektur Parameter (FKP) and the Master-Auxiliary Concept (MAC), which are fundamentally similar approaches. The purpose of all studies for this paper was to evaluate the achievable accuracy of the Continuously Operating Reference Stations (CORS)-FKP in the project area and check the results. The CORS-FKP results show that the solution for the forest area was reached at cm level (±10-15 cm) for horizontal accuracy.

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Evaluating the Repeatability of RTK GPS

Cited by 10 publications

References 2 publications

Positioning Methods and the Use of Location and Activity Data in Forests

Positioning Methods and the Use of Location and Activity Data in Forests

Nature 4.0: A networked sensor system for integrated biodiversity monitoring

Network Real Time Kinematic (Cors-FKP Method) Accuracy in/Under Forest Area

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