5 Key Points to Improve the Accuracy of RTK Point Cloud Measurements｜Practical Steps to Minimize Errors

Table of Contents

• Introduction

• Point 1: Installation and Management of Reference Stations

• Point 2: Optimization of the Satellite Reception Environment

• Point 3: Acquisition and Verification of Fixed Solutions

• Point 4: Quality Monitoring During Measurement Operations

• Point 5: Post-Verification and Accuracy Evaluation

• Integrated Approach to Improving Accuracy

• Common Causes of Accuracy Degradation and Countermeasures

• Accuracy Improvement Strategies for Different Measurement Environments

• Practical Case Studies of Accuracy Improvement

• Technological Advances and Prospects for Future Accuracy Improvements

• Site-specific Accuracy Improvement Strategies

Introduction

In RTK point cloud surveying, obtaining high-precision data greatly influences the quality of subsequent analysis and decision-making. Although RTK positioning technology can theoretically achieve accuracy on the order of several centimeters, in actual field measurements accuracy can degrade due to various factors. To minimize variability in measurement results and consistently obtain high-precision data, appropriate measures are required at each phase—from pre-survey preparation and monitoring during surveying to post-survey verification.

In this article, we explain in detail five points you should put into practice to improve the accuracy of RTK point cloud measurements. From a practical standpoint, we describe what to pay attention to and what measures to take at each stage—establishing and managing reference stations, optimizing the satellite reception environment, obtaining and verifying fixed solutions, monitoring quality during measurement operations, and post-measurement verification and accuracy assessment. By following these points, you can reliably utilize high-accuracy RTK point cloud data at construction sites and in infrastructure management.

In the surveying industry, the use of high-precision measurement technologies is standardized, and technical understanding of these technologies leads to optimal decision-making in the field. The content explained in this article provides the basic knowledge needed to prevent failures in practice and to ensure reliable success. It aims to serve as a reference for all practitioners involved in RTK point cloud measurement, from surveyors to construction engineers.

Point 1: Installation and Management of Reference Stations

The most important factor affecting RTK positioning accuracy is the quality of the reference station. A reference station is a fixed receiver with known, precise coordinates that measures errors in satellite radio signals and transmits that information to the rover, thereby greatly improving the rover’s positioning accuracy. Therefore, if the reference station itself has inaccurate coordinates or unstable signal reception, the overall accuracy will degrade. Because reference station errors propagate across the entire survey area, ensuring the accuracy of the reference point is such a critical factor that it can determine the success or failure of the entire project.

There are several methods for determining the coordinates of a reference station. If a known survey control point exists within the measurement area, using it as the reference station is the most reliable option. If such known control points are not available, you can use a wide-area RTK correction service. This service integrates correction information transmitted from multiple reference stations and delivers high-precision corrections in real time; depending on the service area, it can achieve accuracy on the order of several centimeters (cm-level accuracy, half-inch accuracy). Furthermore, this method can greatly reduce the effort required to install and manage reference stations, making it easier for small and medium-sized enterprises to adopt.

If you establish a reference station independently, selecting the installation site is the first important step. A good satellite reception environment is essential; the sky should be open and free from signal obstructions caused by trees or buildings. Also, installing it in a location that overlooks the entire measurement area minimizes the transmission distance of correction information from the reference station to the rover, which leads to improved accuracy. Once the coordinates of the reference station are determined, it is important to record those coordinate values accurately and to confirm that all personnel performing measurements are using the same coordinates. If coordinate values are entered incorrectly or misunderstood, the entire system can be thrown off. It is also recommended to save the coordinate values on multiple recording media to ensure redundancy.

The receiver at the reference station must operate stably at all times during the measurement period. Place the receiver’s power supply in a location where a stable power source is available, and regularly check that the communication cables are not disconnected. Especially when conducting long-term measurements, it is important to frequently check the receiver’s remaining battery level and the status of the communication connection. If the reference station’s receiver temporarily stops, the positioning of the rover during that time will lack correction information and become a float solution, reducing accuracy. For long-term measurements, providing an uninterruptible power supply or backup power for the receiver is also an important measure to improve reliability.

Point 2: Optimizing the Satellite Reception Environment

The accuracy of RTK positioning depends heavily on the number of satellites that can be received and their geometric configuration. In ideal environments, signals can be received simultaneously from multiple satellites, and because those satellites are dispersed in various directions across the sky, high-precision positioning is possible. Conversely, in areas with many trees or buildings, the satellites that can be received are limited, and accuracy tends to decrease.

It is extremely important to investigate the satellite reception environment of the area to be measured in advance. The way to do this is to bring a simple GNSS receiver to the planned measurement site and confirm beforehand which satellites can be received and how strong the received signals are. Many GNSS testing applications are available, and by using them you can easily assess the satellite reception conditions.

If reception conditions are expected to be problematic, multiple countermeasures should be considered. First, adjust the measurement time window. Because satellite visibility changes over time, reception conditions may improve during certain periods. By conducting preliminary surveys and identifying the optimal measurement time window, an improvement in accuracy can be expected.

Secondly, consider the position and orientation of the receiving antenna. Installing the antenna as high as possible can reduce the impact of surrounding obstacles. It is also effective to clear the space around the antenna and remove any unnecessary objects.

Third, making use of multiple satellite systems. By simultaneously receiving signals from multiple satellite systems such as GPS, GLONASS, Galileo, and BeiDou, the total number of satellites that can be received increases, satellite geometry is improved, and accuracy is enhanced while initialization time is reduced. Many modern high-performance receivers support these multiple systems, so it is important to check the settings and enable them.

Point 3: Acquiring and Verifying a Fixed Solution

In RTK positioning, achieving high accuracy requires a fixed solution. A fixed solution refers to a state in which the carrier-phase ambiguities are completely resolved and the relative position between the rover and the base station is fully determined in integer-cycle units. In this state, accuracy improves to a few centimeters (a few in) or less, but if a fixed solution is not reached, positioning is performed in a float solution and accuracy remains on the order of tens of centimeters (tens of in).

The time required to reach a fixed solution is called the "initialization time," and it is influenced by factors such as the number of satellites that can be received, the satellites' geometric configuration, receiver performance, and the quality of correction information. In ideal conditions, the initialization time ranges from a few seconds to tens of seconds, but if satellite reception conditions are poor, the initialization time can extend to several minutes or more.

Before starting measurements, confirming that the rover has reliably obtained a fixed solution is one of the most important checks. It is common for the receiver’s screen or software to display the current positioning status (float solution or fixed solution), and it is necessary to monitor this status. If a fixed solution cannot be obtained, you should not forcibly continue the measurements; instead, investigate the cause, take corrective measures, and then resume the measurements.

Even if a fixed solution is obtained once, it can be lost during measurement. This can happen when signal reception is temporarily interrupted or when the mobile station's movement speed changes abruptly. Particular caution is needed in locations where signal reception tends to be unstable, such as when passing by the base of trees or entering the shadow of buildings. During measurements, it is important to check reception regularly and monitor whether the fixed solution is being maintained.

Point 4: Quality monitoring during measurement work

During measurement work, continuously monitoring the quality of measurements rather than merely collecting data mechanically is indispensable for maintaining accuracy. Evaluating the quality of measurement data in real time and responding immediately when problems occur reduces the need for rework during post-processing and improves overall work efficiency.

Items that should be monitored during measurements include maintaining a fixed solution, the number of satellites received, signal strength, and DOP values (geometric strength factor). The DOP value is an indicator of the quality of the satellites' geometric configuration; the smaller the value, the better the geometry and the higher the positioning accuracy. An ideal DOP value is 5 or less, and values above this tend to be associated with reduced accuracy.

Especially in automated measurements using drones, it can be difficult to monitor measurement quality in real time during flight. In such cases, it is important to immediately inspect the collected data after the flight and check for any areas with insufficient quality. If there are areas with quality issues, conducting additional flights to supplement those parts can ensure the overall accuracy.

It is also important to monitor environmental changes at the measurement site. During measurements, unexpected environmental changes can occur—for example, surrounding trees may start to sway and obstruct signals, or other construction may begin and generate electrical noise. Detecting and responding to such changes early helps maintain the quality of the measurements.

Point 5: Post-validation and Accuracy Evaluation

After measurements are completed, it is important to comprehensively verify whether the collected data meet the required accuracy specifications. Verification at this stage ensures the reliability of the data and enables appropriate subsequent analysis and decision-making.

The main items of the post-validation include accuracy checks at multiple locations, verification of consistency of measurement data across multiple sessions, and comparison with known points. Immediately after completing the measurements, several known points within the survey area (such as existing survey control points) are re-measured to determine how closely the results match the known coordinate values. This check allows assessment of whether there are systematic errors in the overall data, outliers, and so on.

When measurements are taken across multiple sessions, it is also important to check for discontinuities or inconsistencies in the data between sessions. Errors in coordinate system transformations or incorrect entry of reference point coordinates can cause poor continuity of data between sessions. If such problems are discovered during post-validation, they can be addressed promptly.

If the results of the accuracy evaluation do not meet the required specifications, remeasurement or additional measurements may be necessary. However, if post-verification can detect problems early, additional measures can be taken while the measurement site is still available, preventing delays to the overall project.

An Integrated Approach to Improving Accuracy

The five points discussed so far should not be considered independently; only by integrating them together can their maximum effect be achieved. Even if the reference station’s quality is high, accuracy will decline if the satellite reception environment is poor, and even if a fixed solution has been obtained, re-measurement will be required if quality issues are discovered during post-verification.

As an integrated approach, it is important during the pre-measurement planning phase to fully understand the characteristics of the measurement area and to consider countermeasures for anticipated issues in advance. During on-site measurements, it is necessary to proceed carefully while remaining mindful of each point. After measurements are completed, rigorously conducting post-measurement verification and adopting an attitude that prioritizes quality assurance will lead to improved overall accuracy.

By adopting such an integrated, phased approach, you can maximize the reliability and accuracy of RTK point cloud measurements and ultimately greatly enhance the value of the measurement data. By implementing the five points discussed in this article, you can significantly reduce the occurrence of problems at measurement sites and ensure the delivery of high-quality results.

Common causes of accuracy degradation and countermeasures

In practice, the primary causes of accuracy degradation in RTK point cloud measurements are often a combination of multiple factors. When accuracy first deteriorates, identifying the cause requires systematically inspecting each element.

Multipath (the phenomenon in which signals are reflected by buildings or terrain and received via multiple paths) is particularly pronounced when temporary structures are present around construction sites. Potential countermeasures include slightly shifting the antenna's position, changing the reception time window, or placing absorptive materials around the antenna.

If a fixed solution cannot be obtained, this may be due to an insufficient number of satellites or deterioration of DOP values. In such cases, moving to a more open location, changing the measurement time, or utilizing multiple satellite systems can be effective.

Excessive distance between the reference station and the rover can also cause a decrease in accuracy. Typically, RTK positioning accuracy decreases in proportion to distance, and when the distance exceeds 10 km (32808.4 ft), accuracy tends to deteriorate markedly. In such cases, it is necessary to install an auxiliary reference station at a closer location or consider using a wide-area RTK broadcast service.

Accuracy Improvement Measures by Measurement Environment

Measurement environments vary, and each has its own specific challenges and countermeasures. On construction sites, existing structures and temporary buildings often block satellite signals, so careful selection of measurement positions and adjustment of antenna height are effective. In open areas such as farmland, satellite reception conditions are generally favorable, so by attending to the basic points, high accuracy can be expected.

In mountainous areas, satellite reception conditions tend to be complex, and signals from certain directions may be blocked. In such cases, using multiple satellite systems is particularly effective. In heavily wooded areas, signal fluctuations when passing between trees can affect accuracy, so measurements at a slow speed or averaging multiple measurements should be considered.

In urban areas, multipath caused by reflections from high-rise buildings becomes a significant problem. By selecting measurement routes and choosing appropriate measurement times, this impact can be minimized.

Examples of Accuracy Improvement in Practical Work

There is much to learn from real-world cases on construction sites. In a large-scale land development project, the initial measurements showed variability in accuracy because the reference station was not adequately secured and had shifted. After discovering the problem, the reference station was securely fixed with anchor bolts and a process to periodically check its position was put in place. As a result, accuracy improved dramatically and the efficiency of construction management was greatly enhanced.

In another case, on an urban construction site, multipath was the primary cause of degraded accuracy. Reflections of signals from building facades reduced measurement accuracy to the level of several tens of centimeters (several tens of in). As countermeasures, restricting measurement times to the morning and installing the receiving antenna at a higher position minimized the impact of multipath. Furthermore, advancing support for multiple satellite systems increased the number of receivable satellites and improved the geometry.

What can be commonly learned from these cases is that improving accuracy requires not merely mechanical settings but a deep understanding of the measurement environment and flexible response strategies. Not only textbook countermeasures, but also practical measures tailored to site-specific conditions ultimately lead to improved accuracy.

Technological Evolution and Outlook for Future Accuracy Improvements

With advances in receiver technology, the accuracy of RTK point cloud measurements is expected to improve further. The adoption of multi-frequency reception technology has increased resistance to multipath interference, making high accuracy achievable even in poor satellite reception environments. By receiving multiple frequency bands simultaneously, the effects of signal delay caused by the atmosphere can be corrected more accurately, resulting in improved accuracy.

By leveraging AI technologies, real-time quality assessment of measurement data and anomaly detection are also expected to be automated. This will make measurement tasks more efficient and reduce human errors. By learning patterns in measurement data, machine learning algorithms may detect early signs of quality degradation and may also enable automatic adjustment of measurement parameters.

If RTK positioning functionality becomes available on common devices such as smartphones, more people will be able to take advantage of this technology. In particular, iPhone-mounted GNSS high-precision positioning devices enable flexible and efficient measurements that conventional professional surveying instruments cannot achieve. With such devices, not only surveyors but also construction technicians, drone operators, and other specialists across various fields will be able to perform high-precision measurements easily.

By utilizing such devices, on-site measurements become simpler, and as a result, it will be possible to leverage high-precision point cloud data in even more projects. In terms of both accuracy improvements and efficiency gains, the evolution of RTK point cloud measurement technology is expected to have a significant impact on the surveying and construction industries. It will also serve as an important foundation for accelerating industry-wide productivity improvements and the promotion of DX.

Accuracy Improvement Strategies by Site Environment

To maximize the accuracy of RTK point cloud measurements, a strategic approach tailored to the environmental characteristics of the survey site is required. Because the factors that affect accuracy differ by environment—urban areas, mountainous regions, coastal areas, and so on—a one-size-fits-all approach will not produce the best results.

In urban measurements, the biggest challenge is multipath caused by high-rise buildings. Radio signals from satellites reflect off buildings and reach the receiver, causing the apparent distance to be calculated longer than the actual distance and resulting in positioning errors. As a countermeasure, it is effective to set a higher satellite elevation mask angle to exclude low-elevation satellites. Also, selecting measurement time windows and aiming for periods when satellite geometry is favorable contributes to improved accuracy.

In measurements in mountainous areas, satellite blockage caused by steep terrain becomes a problem. Surrounding mountains and cliffs can block radio signals, limiting the number of visible satellites and making it difficult to obtain fixed solutions. In such environments, using a multi-constellation receiver that can simultaneously utilize multiple GNSS satellite systems (GPS, GLONASS, Galileo, Michibiki, etc.) can increase the number of visible satellites and improve positioning stability.

State-of-the-art high-precision positioning devices, such as the LRTK (iPhone-mounted GNSS high-precision positioning device), are equipped with functions to support measurements in a variety of field environments. By applying optimal settings tailored to each field environment and delivering stable, high-precision measurements, they can reliably meet the accuracy targets of RTK point cloud measurements.