Asynchronous RTK precise DGNSS positioning method for deriving a low-latency high-rate output

Zhang, Liang; Lv, Hanfeng; Wang, Dingjie; Hou, Yanqing; Wu, Jie

doi:10.1007/s00190-015-0803-7

Cited by 23 publications

(17 citation statements)

References 20 publications

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“…GCPs could also be implemented for longer periods depending on the durability of permanent ground markings, particularly during thinning procedures. Furthermore, such sites could be implemented for the testing and calibration of remote sensing technologies for the purpose of assessment [62][63][64][65][66], as well as sensor fusion and upscaling [67][68][69].…”

Section: Discussionmentioning

confidence: 99%

UAV-Based Photogrammetric Tree Height Measurement for Intensive Forest Monitoring

Sanders²,

et al. 2019

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The measurement of tree height has long been an important tree attribute for the purpose of calculating tree growth, volume, and biomass, which in turn deliver important ecological and economical information to decision makers. Tree height has traditionally been measured by indirect field-based techniques, however these methods are rarely contested. With recent advances in Unmanned Aerial Vehicle (UAV) remote sensing technologies, the possibility to acquire accurate tree heights semi-automatically has become a reality. In this study, photogrammetric and field-based tree height measurements of a Scots Pine stand were validated using destructive methods. The intensive forest monitoring site implemented for the study was configured with permanent ground control points (GCPs) measured with a Total Station (TS). Field-based tree height measurements resulted in a similar level of error to that of the photogrammetric measurements, with root mean square error (RMSE) values of 0.304 m (1.82%) and 0.34 m (2.07%), respectively (n = 34). A conflicting bias was, however, discovered where field measurements tended to overestimate tree heights and photogrammetric measurements were underestimated. The photogrammetric tree height measurements of all trees (n = 285) were validated against the field-based measurements and resulted in a RMSE of 0.479 m (2.78%). Additionally, two separate photogrammetric tree height datasets were compared (n = 251), and a very low amount of error was observed with a RMSE of 0.138 m (0.79%), suggesting a high potential for repeatability. This study shows that UAV photogrammetric tree height measurements are a viable option for intensive forest monitoring plots and that the possibility to acquire within-season tree growth measurements merits further study. Additionally, it was shown that negative and positive biases evident in field-based and UAV-based photogrammetric tree height measurements could potentially lead to misinterpretation of results when field-based measurements are used as validation.

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Section: Discussionmentioning

confidence: 99%

UAV-Based Photogrammetric Tree Height Measurement for Intensive Forest Monitoring

Sanders²,

et al. 2019

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“…The undifferenced observations for the code and carrier phase equations relating to satellite i and receiver B are as follows [21,22]:…”

Section: Methodsmentioning

confidence: 99%

“…However, it was still within a stable range. The most accurate results were obtained in the E direction, which benefitted from the geometry of the five geosynchronous Earth orbit satellites of the BeiDou system, stationed over the Asia-Pacific region from the west to the east [22]. Figure 11 shows that when the SRTK and ARTK methods were applied to the imminent sliding stage of the landslide, the displacement sequences of the two To clearly compare the sequence of values obtained from the SRTK and ARTK methods, the shaded parts of the three plots in Figure 11 are shown as enlarged.…”

Section: Landslide Monitoringmentioning

confidence: 99%

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Asynchronous RTK Method for Detecting the Stability of the Reference Station in GNSS Deformation Monitoring

Huang

Zhang

et al. 2020

Sensors

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The real-time kinematic (RTK) positioning technique of global navigation satellite systems (GNSS) has been widely used for deformation monitoring in the past several decades. The RTK technique can provide relative displacements in a local reference frame defined by a highly stable reference station. However, the traditional RTK solution does not account for reference stations that experience displacement. This presents a challenge for establishing a near real-time GNSS monitoring system, as since the displacement of a reference station can be easily misinterpreted as a sign of rapid movement at the monitoring station. In this study, based on the reference observations in different time domains, asynchronous and synchronous RTK are proposed and applied together to address this issue, providing more reliable displacement information. Using the asynchronously generated time difference of a reference frame, the proposed approach can detect whether a measured displacement has occurred in the reference or the monitoring station in the current epoch. This allows for the separation of reference station movements from monitoring station movements. The results based on both simulated and landslide monitoring data demonstrate that the proposed method can provide reliable displacement determinations, which are critical in deformation monitoring applications, such as the early warning of landslides.

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“…Various methods have been proposed to mitigate gaps in the base station observations so that continuous RTK solutions can be provided during outage periods [11,12,13,14,15,16]. For example, an algorithm was proposed to estimate the rover position based on time-differenced carrier observations [12].…”

Section: Introductionmentioning

confidence: 99%

A New Asynchronous RTK Method to Mitigate Base Station Observation Outages

Huang

Zhang

et al. 2019

Sensors

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Real-time kinematic (RTK) positioning is a satellite navigation technique that is widely used to enhance the precision of position data obtained from global navigation satellite systems (GNSS). This technique can reduce or eliminate significant correlation errors via the enhancement of the base station observation data. However, observations received by the base station are often interrupted, delayed, and/or discontinuous, and in the absence of base station observation data the corresponding positioning accuracy of a rover declines rapidly. With the strategies proposed till date, the positioning accuracy can only be maintained at the centimeter-level for a short span of time, no more than three min. To address this, a novel asynchronous RTK method (that addresses asynchronous errors) that can bridge significant gaps in the observations at the base station is proposed. First, satellite clock and orbital errors are eliminated using the products of the final precise ephemeris during post-processing or the ultra-rapid precise ephemeris during real-time processing. Then the tropospheric error is corrected using the Saastamoinen model and the asynchronous ionospheric delay is corrected using the carrier phase measurements from the rover receiver. Finally, a straightforward first-degree polynomial function is used to predict the residual asynchronous error. Experimental results demonstrate that the proposed approach can achieve centimeter-level accuracy for as long as 15 min during interruptions in both real-time and post-processing scenarios, and that the accuracy of the real-time scheme can be maintained for 15 min even when a large systematic error is projected in the U direction.

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Asynchronous RTK precise DGNSS positioning method for deriving a low-latency high-rate output

Cited by 23 publications

References 20 publications

UAV-Based Photogrammetric Tree Height Measurement for Intensive Forest Monitoring

UAV-Based Photogrammetric Tree Height Measurement for Intensive Forest Monitoring

Asynchronous RTK Method for Detecting the Stability of the Reference Station in GNSS Deformation Monitoring

A New Asynchronous RTK Method to Mitigate Base Station Observation Outages

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